Retrieval of radiative and microphysical properties of clouds from multispectral infrared measurements

NASA Astrophysics Data System (ADS)

Iwabuchi, Hironobu; Saito, Masanori; Tokoro, Yuka; Putri, Nurfiena Sagita; Sekiguchi, Miho

2016-12-01

Satellite remote sensing of the macroscopic, microphysical, and optical properties of clouds are useful for studying spatial and temporal variations of clouds at various scales and constraining cloud physical processes in climate and weather prediction models. Instead of using separate independent algorithms for different cloud properties, a unified, optimal estimation-based cloud retrieval algorithm is developed and applied to moderate resolution imaging spectroradiometer (MODIS) observations using ten thermal infrared bands. The model considers sensor configurations, background surface and atmospheric profile, and microphysical and optical models of ice and liquid cloud particles and radiative transfer in a plane-parallel, multilayered atmosphere. Measurement and model errors are thoroughly quantified from direct comparisons of clear-sky observations over the ocean with model calculations. Performance tests by retrieval simulations show that ice cloud properties are retrieved with high accuracy when cloud optical thickness (COT) is between 0.1 and 10. Cloud-top pressure is inferred with uncertainty lower than 10 % when COT is larger than 0.3. Applying the method to a tropical cloud system and comparing the results with the MODIS Collection 6 cloud product shows good agreement for ice cloud optical thickness when COT is less than about 5. Cloud-top height agrees well with estimates obtained by the CO2 slicing method used in the MODIS product. The present algorithm can detect optically thin parts at the edges of high clouds well in comparison with the MODIS product, in which these parts are recognized as low clouds by the infrared window method. The cloud thermodynamic phase in the present algorithm is constrained by cloud-top temperature, which tends not to produce results with an ice cloud that is too warm and liquid cloud that is too cold.

Evaluating the impact of aerosol particles above cloud on cloud optical depth retrievals from MODIS

NASA Astrophysics Data System (ADS)

Alfaro-Contreras, Ricardo; Zhang, Jianglong; Campbell, James R.; Holz, Robert E.; Reid, Jeffrey S.

2014-05-01

Using two different operational Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical depth (COD) retrievals (0.86 versus 1.6 µm), we evaluate the impact of above-cloud smoke aerosol particles on near-IR (0.86 µm) COD retrievals. Aerosol Index (AI) from the collocated Ozone Monitoring Instrument (OMI) are used to identify above-cloud aerosol particle loading over the southern Atlantic Ocean, including both smoke and dust from the African subcontinent. Collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation data constrain cloud phase and provide contextual above-cloud aerosol optical depth. The frequency of occurrence of above-cloud aerosol events is depicted on a global scale for the spring and summer seasons from OMI and Cloud Aerosol Lidar with Orthogonal Polarization. Seasonal frequencies for smoke-over-cloud off the southwestern Africa coastline reach 20-50% in boreal summer. We find a corresponding low COD bias of 10-20% for standard MODIS COD retrievals when averaged OMI AI are larger than 1. No such bias is found over the Saharan dust outflow region off northern Africa, since both MODIS 0.86 and 1.6 µm channels are vulnerable to radiance attenuation due to dust particles. A similar result is found for a smaller domain, in the Gulf of Tonkin region, from smoke advection over marine stratocumulus clouds and outflow into the northern South China Sea in spring. This study shows the necessity of accounting for the above-cloud aerosol events for future studies using standard MODIS cloud products in biomass burning outflow regions, through the use of collocated OMI AI and supplementary MODIS 1.6 µm COD products.

Global Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Ackerman, Steven A.; Menzel, W. Paul; Riedi, Jerome C.; Baum, Bryan A.

2003-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4,2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has 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 cloud properties being analyzed on a global basis from both Terra and Aqua, and will show characteristics of cloud optical and microphysical properties as a function of latitude for land and ocean separately, and contrast the statistical properties of similar cloud types in various parts of the world.

Remote Sensing of Radiative and Microphysical Properties of Clouds During TC (sup 4): Results from MAS, MASTER, MODIS, and MISR

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Wind, Galina; Arnold, G. Thomas; Dominguez, Roseanne T.

2010-01-01

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.

View angle dependence of cloud optical thicknesses retrieved by MODIS

NASA Technical Reports Server (NTRS)

Marshak, Alexander; Varnai, Tamas

2005-01-01

This study examines whether cloud inhomogeneity influences the view angle dependence of MODIS cloud optical thickness (tau) retrieval results. The degree of cloud inhomogeneity is characterized through the local gradient in 11 microns brightness temperature. The analysis of liquid phase clouds in a one year long global dataset of Collection 4 MODIS data reveals that while optical thickness retrievals give remarkably consistent results for all view directions if clouds are homogeneous, they give much higher tau-values for oblique views than for overhead views if clouds are inhomogeneous and the sun is fairly oblique. For solar zenith angles larger than 55deg, the mean optical thickness retrieved for the most inhomogeneous third of cloudy pixels is more than 30% higher for oblique views than for overhead views. After considering a variety of possible scenarios, the paper concludes that the most likely reason for the increase lies in three-dimensional radiative interactions that are not considered in current, one-dimensional retrieval algorithms. Namely, the radiative effect of cloud sides viewed at oblique angles seems to contribute most to the enhanced tau-values. The results presented here will help understand cloud retrieval uncertainties related to cloud inhomogeneity. They complement the uncertainty estimates that will start accompanying MODIS cloud products in Collection 5 and may eventually help correct for the observed view angle dependent biases.

Multispectral Cloud Retrievals from MODIS on Terra and Aqua

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Ackerman, Steven A.; Menzel, W. Paul; Gray, Mark A.; Moody, Eric G.

2002-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and the Aqua spacecraft on April 26, 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from each polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

New Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Tsay, Si-Chee; Ackerman, Steven A.; Menzel, W. Paul; Gray, Mark A.; Moody, Eric G.; Li, Jason Y.; Arnold, G. Thomas

2001-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun- synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (two bands), 500 m (five bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples from MODIS Collection 6

NASA Technical Reports Server (NTRS)

Platnick, Steven; Wind, Galina; Zhang, Zhibo; Ackerman, Steven A.; Maddux, Brent

2012-01-01

The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate effective radii results using the l.6, 2.1, and 3.7 m spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "notclear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 MODIS retrieval algorithm removed pixels associated with cloud'edges as well as ocean pixels with partly cloudy elements in the 250m MODIS cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the ID cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.

Evaluating the impact of above-cloud aerosols on cloud optical depth retrievals from MODIS

NASA Astrophysics Data System (ADS)

Alfaro, Ricardo

Using two different operational Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical depth (COD) retrievals (visible and shortwave infrared), the impacts of above-cloud absorbing aerosols on the standard COD retrievals are evaluated. For fine-mode aerosol particles, aerosol optical depth (AOD) values diminish sharply from the visible to the shortwave infrared channels. Thus, a suppressed above-cloud particle radiance aliasing effect occurs for COD retrievals using shortwave infrared channels. Aerosol Index (AI) from the spatially and temporally collocated Ozone Monitoring Instrument (OMI) are used to identify above-cloud aerosol particle loading over the southern Atlantic Ocean, including both smoke and dust from the African sub-continent. MODIS and OMI Collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are used to constrain cloud phase and provide contextual above-cloud AOD values. The frequency of occurrence of above-cloud aerosols is depicted on a global scale for the spring and summer seasons from OMI and CALIOP, thus indicating the significance of the problem. Seasonal frequencies for smoke-over-cloud off the southwestern Africa coastline reach 20--50% in boreal summer. We find a corresponding low COD bias of 10--20% for standard MODIS COD retrievals when averaged OMI AI are larger than 1.0. No such bias is found over the Saharan dust outflow region off northern Africa, since both MODIS visible and shortwave in channels are vulnerable to dust particle aliasing, and thus a COD impact cannot be isolated with this method. A similar result is found for a smaller domain, in the Gulf of Tonkin region, from smoke advection over marine stratocumulus clouds and outflow into the northern South China Sea in spring. This study shows the necessity of accounting for the above-cloud aerosol events for future studies using standard MODIS cloud products in biomass burning outflow regions, through the use of collocated OMI AI and supplementary MODIS shortwave infrared COD products.

A multi-spectral approach to simultaneously retrieve above-cloud smoke optical depth and the optical and microphysical properties of underlying marine stratocumulus clouds using MODIS

NASA Astrophysics Data System (ADS)

Meyer, K.; Platnick, S. E.; Zhang, Z.

2013-12-01

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer (MBL) clouds over the southeastern Atlantic Ocean, which underlie a near-persistent smoke layer produced from extensive biomass burning throughout the southern African savanna during austral winter. The absorption of the above-cloud smoke layer, which increases with decreasing wavelength, can introduce biases into the standard MODIS cloud optical and microphysical property retrievals of the underlying MBL clouds. This effect is more pronounced in the cloud optical thickness retrievals, which over ocean are derived from the wavelength channel centered near 0.86 μm (effective particle size retrievals are derived from the short and mid-wave IR channels at 1.6, 2.1, and 3.7 μm). Here, a new method is introduced to simultaneously retrieve the above-cloud smoke aerosol optical depth (AOD) and the unbiased cloud optical thickness (COT) and effective radius (CER) using multiple MODIS spectral channels in the visible and near- and shortwave-infrared. Preliminary retrieval results are shown, as are comparisons with other A-Train sensors.

New Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; Tsay, Si-Chee; Ackerman, Steven A.; Gray, Mark A.; Moody, Eric G.; Li, Jason Y.; Arnold, G. T.; King, Michael D. (Technical Monitor)

2000-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this paper I will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of cloud drops and ice crystals. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation

NASA Technical Reports Server (NTRS)

Platnick, Steven E.

2011-01-01

The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.

MODIS Retrievals of Cloud Optical Thickness and Particle Radius

NASA Technical Reports Server (NTRS)

Platnick, S.; King, M. D.; Ackerman, S. A.; Gray, M.; Moody, E.; Arnold, G. T.; Einaudi, Franco (Technical Monitor)

2000-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides an unprecedented opportunity for global cloud studies with 36 spectral bands from the visible through the infrared, and spatial resolution from 250 m to 1 km at nadir. In particular, all solar window bands useful for simultaneous retrievals of cloud optical thickness and particle size (0.67, 0.86, 1.2, 1.6, 2.1, and 3.7 micron bands) are now available on a single satellite instrument/platform for the first time. An operational algorithm for the retrieval of these optical and cloud physical properties (including water path) have been developed for both liquid and ice phase clouds. The product is archived into two categories: pixel-level retrievals at 1 km spatial resolution (referred to as a Level-2 product) and global gridded statistics (Level-3 product). An overview of the MODIS cloud retrieval algorithm and early level-2 and -3 results will be presented. A number of MODIS cloud validation activities are being planned, including the recent Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign conducted in August/September 2000. The later part of the experiment concentrated on MODIS validation in the Namibian stratocumulus regime off the southwest coast of Africa. Early retrieval results from this regime will be discussed.

Extending 'Deep Blue' aerosol retrieval coverage to cases of absorbing aerosols above clouds: sensitivity analysis and first case studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sayer, Andrew M.; Hsu, C.; Bettenhausen, Corey

Cases of absorbing aerosols above clouds (AAC), such as smoke or mineral dust, are omitted from most routinely-processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar

Infrared Retrievals of Ice Cloud Properties and Uncertainties with an Optimal Estimation Retrieval Method

NASA Astrophysics Data System (ADS)

Wang, C.; Platnick, S. E.; Meyer, K.; Zhang, Z.

2014-12-01

We developed an optimal estimation (OE)-based method using infrared (IR) observations to retrieve ice cloud optical thickness (COT), cloud effective radius (CER), and cloud top height (CTH) simultaneously. The OE-based retrieval is coupled with a fast IR radiative transfer model (RTM) that simulates observations of different sensors, and corresponding Jacobians in cloudy atmospheres. Ice cloud optical properties are calculated using the MODIS Collection 6 (C6) ice crystal habit (severely roughened hexagonal column aggregates). The OE-based method can be applied to various IR space-borne and airborne sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the enhanced MODIS Airborne Simulator (eMAS), by optimally selecting IR bands with high information content. Four major error sources (i.e., the measurement error, fast RTM error, model input error, and pre-assumed ice crystal habit error) are taken into account in our OE retrieval method. We show that measurement error and fast RTM error have little impact on cloud retrievals, whereas errors from the model input and pre-assumed ice crystal habit significantly increase retrieval uncertainties when the cloud is optically thin. Comparisons between the OE-retrieved ice cloud properties and other operational cloud products (e.g., the MODIS C6 and CALIOP cloud products) are shown.

Comparisons of Satellite-Deduced Overlapping Cloud Properties and CALIPSO CloudSat Data

NASA Technical Reports Server (NTRS)

Chang, Fu-Lung; Minnis, Patrick; Lin, Bing; Sun-Mack, Sunny

2010-01-01

Introduction to the overlapped cloud properties derived from polar-orbiting (MODIS) and geostationary (GOES-12, -13, Meteosat-8, -9, etc.) meteorological satellites, which are produced at the NASA Langley Research Center (LaRC) cloud research & development team (NASA lead scientist: Dr. Patrick Minnis). Comparison of the LaRC CERES MODIS Edition-3 overlapped cloud properties to the CALIPSO and the CloudSat active sensing data. High clouds and overlapped clouds occur frequently as deduced by CALIPSO (44 & 25%), CloudSat (25 & 4%), and MODIS (37 & 6%). Large fractions of optically-thin cirrus and overlapped clouds are deduced from CALIPSO, but much smaller fractions are from CloudSat and MODIS. For overlapped clouds, the averaged upper-layer CTHs are about 12.8 (CALIPSO), 10.9 (CloudSat) and 10 km (MODIS), and the averaged lower-layer CTHs are about 3.6 (CALIPSO), 3.2 (CloudSat) and 3.9 km (MODIS). Based on comparisons of upper and lower-layer cloud properties as deduced from the MODIS, CALIPSO and CloudSat data, more enhanced passive satellite methods for retrieving thin cirrus and overlapped cloud properties are needed and are under development.

Cloud Retrieval Intercomparisons Between SEVIRI, MODIS and VIIRS with CHIMAERA PGE06 Data Collection 6 Products

NASA Technical Reports Server (NTRS)

Wind, Galina; Riedi, Jerome; Platnick, Steven; Heidinger, Andrew

2014-01-01

The Cross-platform HIgh resolution Multi-instrument AtmosphEric Retrieval Algorithms (CHIMAERA) system allows us to perform MODIS-like cloud top, optical and microphysical properties retrievals on any sensor that possesses a minimum set of common spectral channels. The CHIMAERA system uses a shared-core architecture that takes retrieval method out of the equation when intercomparisons are made. Here we show an example of such retrieval and a comparison of simultaneous retrievals done using SEVIRI, MODIS and VIIRS sensors. All sensor retrievals are performed using CLAVR-x (or CLAVR-x based) cloud top properties algorithm. SEVIRI uses the SAF_NWC cloud mask. MODIS and VIIRS use the IFF-based cloud mask that is a shared algorithm between MODIS and VIIRS. The MODIS and VIIRS retrievals are performed using a VIIRS branch of CHIMAERA that limits available MODIS channel set. Even though in that mode certain MODIS products such as multilayer cloud map are not available, the cloud retrieval remains fully equivalent to operational Data Collection 6.

Estimate of the Impact of Absorbing Aerosol Over Cloud on the MODIS Retrievals of Cloud Optical Thickness and Effective Radius Using Two Independent Retrievals of Liquid Water Path

NASA Technical Reports Server (NTRS)

Wilcox, Eric M.; Harshvardhan; Platnick, Steven

2009-01-01

Two independent satellite retrievals of cloud liquid water path (LWP) from the NASA Aqua satellite are used to diagnose the impact of absorbing biomass burning aerosol overlaying boundary-layer marine water clouds on the Moderate Resolution Imaging Spectrometer (MODIS) retrievals of cloud optical thickness (tau) and cloud droplet effective radius (r(sub e)). In the MODIS retrieval over oceans, cloud reflectance in the 0.86-micrometer and 2.13-micrometer bands is used to simultaneously retrieve tau and r(sub e). A low bias in the MODIS tau retrieval may result from reductions in the 0.86-micrometer reflectance, which is only very weakly absorbed by clouds, owing to absorption by aerosols in cases where biomass burning aerosols occur above water clouds. MODIS LWP, derived from the product of the retrieved tau and r(sub e), is compared with LWP ocean retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E), determined from cloud microwave emission that is transparent to aerosols. For the coastal Atlantic southern African region investigated in this study, a systematic difference between AMSR-E and MODIS LWP retrievals is found for stratocumulus clouds over three biomass burning months in 2005 and 2006 that is consistent with above-cloud absorbing aerosols. Biomass burning aerosol is detected using the ultraviolet aerosol index from the Ozone Monitoring Instrument (OMI) on the Aura satellite. The LWP difference (AMSR-E minus MODIS) increases both with increasing tau and increasing OMI aerosol index. During the biomass burning season the mean LWP difference is 14 g per square meters, which is within the 15-20 g per square meter range of estimated uncertainties in instantaneous LWP retrievals. For samples with only low amounts of overlaying smoke (OMI AI less than or equal to 1) the difference is 9.4, suggesting that the impact of smoke aerosols on the mean MODIS LWP is 5.6 g per square meter. Only for scenes with OMI aerosol index greater than 2 does the average LWP difference and the estimated bias in MODIS cloud optical thickness attributable to the impact of overlaying biomass burning aerosol exceed the instantaneous uncertainty in the retrievals.

Ice Cloud Backscatter Study and Comparison with CALIPSO and MODIS Satellite Data

NASA Technical Reports Server (NTRS)

Ding, Jiachen; Yang, Ping; Holz, Robert E.; Platnick, Steven; Meyer, Kerry G.; Vaughan, Mark A.; Hu, Yongxiang; King, Michael D.

2016-01-01

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 percent and 9 percent for tropical and mid-latitude ice clouds, respectively.

Ten Years of Cloud Optical and Microphysical Retrievals from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Galina; Hubanks, Paul; Arnold, G. Thomas; Amarasinghe, Nandana

2010-01-01

The MODIS cloud optical properties algorithm (MOD06/MYD06 for Terra and Aqua MODIS, respectively) has undergone extensive improvements and enhancements since the launch of Terra. These changes have included: improvements in the cloud thermodynamic phase algorithm; substantial changes in the ice cloud light scattering look up tables (LUTs); a clear-sky restoral algorithm for flagging heavy aerosol and sunglint; greatly improved spectral surface albedo maps, including the spectral albedo of snow by ecosystem; inclusion of pixel-level uncertainty estimates for cloud optical thickness, effective radius, and water path derived for three error sources that includes the sensitivity of the retrievals to solar and viewing geometries. To improve overall retrieval quality, we have also implemented cloud edge removal and partly cloudy detection (using MOD35 cloud mask 250m tests), added a supplementary cloud optical thickness and effective radius algorithm over snow and sea ice surfaces and over the ocean, which enables comparison with the "standard" 2.1 11m effective radius retrieval, and added a multi-layer cloud detection algorithm. We will discuss the status of the MOD06 algorithm and show examples of pixellevel (Level-2) cloud retrievals for selected data granules, as well as gridded (Level-3) statistics, notably monthly means and histograms (lD and 2D, with the latter giving correlations between cloud optical thickness and effective radius, and other cloud product pairs).

OMMYDCLD: a New A-train Cloud Product that Co-locates OMI and MODIS Cloud and Radiance Parameters onto the OMI Footprint

NASA Technical Reports Server (NTRS)

Fisher, Brad; Joiner, Joanna; Vasilkov, Alexander; Veefkind, Pepijn; Platnick, Steven; Wind, Galina

2014-01-01

Clouds cover approximately 60% of the earth's surface. When obscuring the satellite's field of view (FOV), clouds complicate the retrieval of ozone, trace gases and aerosols from data collected by earth observing satellites. Cloud properties associated with optical thickness, cloud pressure, water phase, drop size distribution (DSD), cloud fraction, vertical and areal extent can also change significantly over short spatio-temporal scales. The radiative transfer models used to retrieve column estimates of atmospheric constituents typically do not account for all these properties and their variations. The OMI science team is preparing to release a new data product, OMMYDCLD, which combines the cloud information from sensors on board two earth observing satellites in the NASA A-Train: Aura/OMI and Aqua/MODIS. OMMYDCLD co-locates high resolution cloud and radiance information from MODIS onto the much larger OMI pixel and combines it with parameters derived from the two other OMI cloud products: OMCLDRR and OMCLDO2. The product includes histograms for MODIS scientific data sets (SDS) provided at 1 km resolution. The statistics of key data fields - such as effective particle radius, cloud optical thickness and cloud water path - are further separated into liquid and ice categories using the optical and IR phase information. OMMYDCLD offers users of OMI data cloud information that will be useful for carrying out OMI calibration work, multi-year studies of cloud vertical structure and in the identification and classification of multi-layer clouds.

Simultaneously inferring above-cloud absorbing aerosol optical thickness and underlying liquid phase cloud optical and microphysical properties using MODIS

NASA Astrophysics Data System (ADS)

Meyer, Kerry; Platnick, Steven; Zhang, Zhibo

2015-06-01

The regional haze over the southeast (SE) Atlantic Ocean induced by biomass burning in southern Africa can be problematic for passive imager-based retrievals of the underlying quasi-permanent marine boundary layer (MBL) clouds and for estimates of top-of-atmosphere (TOA) aerosol direct radiative effect (DRE). Here an algorithm is introduced to simultaneously retrieve above-cloud aerosol optical thickness (AOT), the cloud optical thickness (COT), and cloud effective particle radius (CER) of the underlying MBL clouds while also providing pixel-level estimates of retrieval uncertainty. This approach utilizes reflectance measurements at six Moderate Resolution Imaging Spectroradiometer (MODIS) channels from the visible to the shortwave infrared. Retrievals are run under two aerosol model assumptions on 8 years (2006-2013) of June-October Aqua MODIS data over the SE Atlantic, from which a regional cloud and above-cloud aerosol climatology is produced. The cloud retrieval methodology is shown to yield COT and CER consistent with those from the MODIS operational cloud product (MOD06) when forcing AOT to zero, while the full COT-CER-AOT retrievals that account for the above-cloud aerosol attenuation increase regional monthly mean COT and CER by up to 9% and 2%, respectively. Retrieved AOT is roughly 3 to 5 times larger than the collocated 532 nm Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrievals, though closer agreement is observed with the CALIOP 1064 nm retrievals, a result consistent with previous case study analyses. Regional cloudy-sky above-cloud aerosol DRE calculations are also performed that illustrate the importance of the aerosol model assumption and underlying cloud retrievals.

Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples from MODIS Collection 6

NASA Astrophysics Data System (ADS)

Platnick, S.; Wind, G.; Zhang, Z.; Ackerman, S. A.; Maddux, B. C.

2012-12-01

The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate effective radii results using the 1.6, 2.1, and 3.7 μm spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "not-clear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 MODIS retrieval algorithm removed pixels associated with cloud edges (defined by immediate adjacency to "clear" MOD/MYD35 pixels) as well as ocean pixels with partly cloudy elements in the 250m MODIS cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the 1D cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.

Comparison between MODIS-derived day and night cloud cover and surface observations over the North China Plain

NASA Astrophysics Data System (ADS)

Zhang, Xiao; Tan, Saichun; Shi, Guangyu

2018-02-01

Satellite and human visual observation are two of the most important observation approaches for cloud cover. In this study, the total cloud cover (TCC) observed by MODIS onboard the Terra and Aqua satellites was compared with Synop meteorological station observations over the North China Plain and its surrounding regions for 11 years during daytime and 7 years during nighttime. The Synop data were recorded eight times a day at 3-h intervals. Linear interpolation was used to interpolate the Synop data to the MODIS overpass time in order to reduce the temporal deviation between the satellite and Synop observations. Results showed that MODIS-derived TCC had good consistency with the Synop observations; the correlation coefficients ranged from 0.56 in winter to 0.73 in summer for Terra MODIS, and from 0.55 in winter to 0.71 in summer for Aqua MODIS. However, they also had certain differences. On average, the MODIS-derived TCC was 15.16% higher than the Synop data, and this value was higher at nighttime (15.58%-16.64%) than daytime (12.74%-14.14%). The deviation between the MODIS and Synop TCC had large seasonal variation, being largest in winter (29.53%-31.07%) and smallest in summer (4.46%-6.07%). Analysis indicated that cloud with low cloud-top height and small cloud optical thickness was more likely to cause observation bias. Besides, an increase in the satellite view zenith angle, aerosol optical depth, or snow cover could lead to positively biased MODIS results, and this affect differed among different cloud types.

Validating MODIS above-cloud aerosol optical depth retrieved from "color ratio" algorithm using direct measurements made by NASA's airborne AATS and 4STAR sensors

NASA Astrophysics Data System (ADS)

Jethva, Hiren; Torres, Omar; Remer, Lorraine; Redemann, Jens; Livingston, John; Dunagan, Stephen; Shinozuka, Yohei; Kacenelenbogen, Meloe; Segal Rosenheimer, Michal; Spurr, Rob

2016-10-01

We present the validation analysis of above-cloud aerosol optical depth (ACAOD) retrieved from the "color ratio" method applied to MODIS cloudy-sky reflectance measurements using the limited direct measurements made by NASA's airborne Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) sensors. A thorough search of the airborne database collection revealed a total of five significant events in which an airborne sun photometer, coincident with the MODIS overpass, observed partially absorbing aerosols emitted from agricultural biomass burning, dust, and wildfires over a low-level cloud deck during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS 2013 campaigns, respectively. The co-located satellite-airborne matchups revealed a good agreement (root-mean-square difference < 0.1), with most matchups falling within the estimated uncertainties associated the MODIS retrievals (about -10 to +50 %). The co-retrieved cloud optical depth was comparable to that of the MODIS operational cloud product for ACE-ASIA and SEAC4RS, however, higher by 30-50 % for the SAFARI-2000 case study. The reason for this discrepancy could be attributed to the distinct aerosol optical properties encountered during respective campaigns. A brief discussion on the sources of uncertainty in the satellite-based ACAOD retrieval and co-location procedure is presented. Field experiments dedicated to making direct measurements of aerosols above cloud are needed for the extensive validation of satellite-based retrievals.

Validating MODIS Above-Cloud Aerosol Optical Depth Retrieved from Color Ratio Algorithm Using Direct Measurements Made by NASA's Airborne AATS and 4STAR Sensors

NASA Technical Reports Server (NTRS)

Jethva, Hiren; Torres, Omar; Remer, Lorraine; Redemann, Jens; Livingston, John; Dunagan, Stephen; Shinozuka, Yohei; Kacenelenbogen, Meloe; Segal Rozenhaimer, Michal; Spurr, Rob

2016-01-01

We present the validation analysis of above-cloud aerosol optical depth (ACAOD) retrieved from the color ratio method applied to MODIS cloudy-sky reflectance measurements using the limited direct measurements made by NASAs airborne Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) sensors. A thorough search of the airborne database collection revealed a total of five significant events in which an airborne sun photometer, coincident with the MODIS overpass, observed partially absorbing aerosols emitted from agricultural biomass burning, dust, and wildfires over a low-level cloud deck during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS 2013 campaigns, respectively. The co-located satellite-airborne match ups revealed a good agreement (root-mean-square difference less than 0.1), with most match ups falling within the estimated uncertainties associated with the MODIS retrievals (about -10 to +50 ). The co-retrieved cloud optical depth was comparable to that of the MODIS operational cloud product for ACE-ASIA and SEAC4RS, however, higher by 30-50% for the SAFARI-2000 case study. The reason for this discrepancy could be attributed to the distinct aerosol optical properties encountered during respective campaigns. A brief discussion on the sources of uncertainty in the satellite-based ACAOD retrieval and co-location procedure is presented. Field experiments dedicated to making direct measurements of aerosols above cloud are needed for the extensive validation of satellite based retrievals.

Above-Cloud Precipitable Water Retrievals using the MODIS 0.94 micron Band with Applications for Multi-Layer Cloud Detection

NASA Technical Reports Server (NTRS)

Platnick, S.; Wind, G.

2004-01-01

In order to perform satellite retrievals of cloud properties, it is important to account for the effect of the above-cloud atmosphere on the observations. The solar bands used in the operational MODIS Terra and Aqua cloud optical and microphysical algorithms (visible, NIR, and SWIR spectral windows) are primarily affected by water vapor, and to a lesser extent by well-mixed gases. For water vapor, the above-cloud column amount, or precipitable water, provides adequate information for an atmospheric correction; details of the vertical vapor distribution are not typically necessary for the level of correction required. Cloud-top pressure has a secondary effect due to pressure broadening influences. For well- mixed gases, cloud-top pressure is also required for estimates of above-cloud abundances. We present a method for obtaining above-cloud precipitable water over dark Ocean surfaces using the MODIS 0.94 pm vapor absorption band. The retrieval includes an iterative procedure for establishing cloud-top temperature and pressure, and is useful for both single layer water and ice clouds. Knowledge of cloud thermodynamic phase is fundamental in retrieving cloud optical and microphysical properties. However, in cases of optically thin cirrus overlapping lower water clouds, the concept of a single unique phase is ill- defined and depends, at least, on the spectral region of interest. We will present a method for multi-layer and multi-phase cloud detection which uses above-cloud precipitable water retrievals along with several existing MODIS operational cloud products (cloud-top pressure derived from a C02 slicing algorithm, IR and SWIR phase retrievals). Results are catagorized by whether the radiative signature in the MODIS solar bands is primarily that of a water cloud with ice cloud contamination, or visa-versa. Examples in polar and mid-latitude regions will be shown.

Marine Boundary Layer Cloud Property Retrievals from High-Resolution ASTER Observations: Case Studies and Comparison with Terra MODIS

NASA Technical Reports Server (NTRS)

Werner, Frank; Wind, Galina; Zhang, Zhibo; Platnick, Steven; Di Girolamo, Larry; Zhao, Guangyu; Amarasinghe, Nandana; Meyer, Kerry

2016-01-01

A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTERspecific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in Zhao and Di Girolamo (2006). To validate and evaluate the cloud optical thickness (tau) and cloud effective radius (r(sub eff)) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000m resolution as MODIS. Subsequently, tau(sub aA) and r(sub eff, aA) retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R greater than 0.970. However, for partially cloudy pixels there are significant differences between r(sub eff, aA) and the MODIS results which can exceed 10 micrometers. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.

Marine boundary layer cloud property retrievals from high-resolution ASTER observations: case studies and comparison with Terra MODIS

NASA Astrophysics Data System (ADS)

Werner, Frank; Wind, Galina; Zhang, Zhibo; Platnick, Steven; Di Girolamo, Larry; Zhao, Guangyu; Amarasinghe, Nandana; Meyer, Kerry

2016-12-01

A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTER-specific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in [Zhao and Di Girolamo(2006)]. To validate and evaluate the cloud optical thickness (τ) and cloud effective radius (reff) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000 m resolution as MODIS. Subsequently, τaA and reff, aA retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R > 0.970. However, for partially cloudy pixels there are significant differences between reff, aA and the MODIS results which can exceed 10 µm. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.

Remote Sensing of Cloud, Aerosol, and Land Properties from MODIS: Applications to the East Asia Region

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Moody, Eric G.

2002-01-01

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999 and the Aqua satellite in May 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this paper we will describe the various methods being used for the remote sensing of cloud, aerosol, and surface properties using MODIS data, focusing primarily on (i) the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, (ii) cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals, (iii) aerosol optical thickness and size characteristics both over land and ocean, and (iv) ecosystem classification and surface spectral reflectance. The physical principles behind the determination of each of these products will be described, together with an example of their application using MODIS observations to the east Asian region. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 min (Level-3 products).

Modis Collection 6 Shortwave-Derived Cloud Phase Classification Algorithm and Comparisons with CALIOP

NASA Technical Reports Server (NTRS)

Marchant, Benjamin; Platnick, Steven; Meyer, Kerry; Arnold, George Thomas; Riedi, Jerome

2016-01-01

Cloud thermodynamic phase (e.g., ice, liquid) classification is an important first step for cloud retrievals from passive sensors such as MODIS (Moderate-Resolution Imaging Spectroradiometer). Because ice and liquid phase clouds have very different scattering and absorbing properties, an incorrect cloud phase decision can lead to substantial errors in the cloud optical and microphysical property products such as cloud optical thickness or effective particle radius. Furthermore, it is well established that ice and liquid clouds have different impacts on the Earth's energy budget and hydrological cycle, thus accurately monitoring the spatial and temporal distribution of these clouds is of continued importance. For MODIS Collection 6 (C6), the shortwave-derived cloud thermodynamic phase algorithm used by the optical and microphysical property retrievals has been completely rewritten to improve the phase discrimination skill for a variety of cloudy scenes (e.g., thin/thick clouds, over ocean/land/desert/snow/ice surface, etc). To evaluate the performance of the C6 cloud phase algorithm, extensive granule-level and global comparisons have been conducted against the heritage C5 algorithm and CALIOP. A wholesale improvement is seen for C6 compared to C5.

Zonal Aerosol Direct and Indirect Radiative Forcing using Combined CALIOP, CERES, CloudSat, and CERES Data

NASA Astrophysics Data System (ADS)

Miller, W. F.; Kato, S.; Rose, F. G.; Sun-Mack, S.

2009-12-01

Under the NASA Energy and Water Cycle System (NEWS) program, cloud and aerosol properties derived from CALIPSO, CloudSat, and MODIS data then matched to the CERES footprint are used for irradiance profile computations. Irradiance profiles are included in the publicly available product, CCCM. In addition to the MODIS and CALIPSO generated aerosol, aerosol optical thickness is calculated over ocean by processing MODIS radiance through the Stowe-Ignatov algorithm. The CERES cloud mask and properties algorithm are use with MODIS radiance to provide additional cloud information to accompany the actively sensed data. The passively sensed data is the only input to the standard CERES radiative flux products. The combined information is used as input to the NASA Langley Fu-Liou radiative transfer model to determine vertical profiles and Top of Atmosphere shortwave and longwave flux for pristine, all-sky, and aerosol conditions for the special data product. In this study, the three sources of aerosol optical thickness will be compared directly and their influence on the calculated and measured TOA fluxes. Earlier studies indicate that the largest uncertainty in estimating direct aerosol forcing using aerosol optical thickness derived from passive sensors is caused by cloud contamination. With collocated CALIPSO data, we are able to estimate frequency of occurrence of cloud contamination, effect on the aerosol optical thickness and direct radiative effect estimates.

Seasonal Bias of Retrieved Ice Cloud Optical Properties Based on MISR and MODIS Measurements

NASA Astrophysics Data System (ADS)

Wang, Y.; Hioki, S.; Yang, P.; Di Girolamo, L.; Fu, D.

2017-12-01

The precise estimation of two important cloud optical and microphysical properties, cloud particle optical thickness and cloud particle effective radius, is fundamental in the study of radiative energy budget and hydrological cycle. In retrieving these two properties, an appropriate selection of ice particle surface roughness is important because it substantially affects the single-scattering properties. At present, using a predetermined ice particle shape without spatial and temporal variations is a common practice in satellite-based retrieval. This approach leads to substantial uncertainties in retrievals. The cloud radiances measured by each of the cameras of the Multi-angle Imaging SpectroRadiometer (MISR) instrument are used to estimate spherical albedo values at different scattering angles. By analyzing the directional distribution of estimated spherical albedo values, the degree of ice particle surface roughness is estimated. With an optimal degree of ice particle roughness, cloud optical thickness and effective radius are retrieved based on a bi-spectral shortwave technique in conjunction with two Moderate Resolution Imaging Spectroradiometer (MODIS) bands centered at 0.86 and 2.13 μm. The seasonal biases of retrieved cloud optical and microphysical properties, caused by the uncertainties in ice particle roughness, are investigated by using one year of MISR-MODIS fused data.

Estimating optically-thin cirrus cloud induced cold bias on infrared radiometric satellite sea surface temperature retrieval in the tropics

NASA Astrophysics Data System (ADS)

Marquis, Jared Wayne

Passive longwave infrared radiometric satellite-based retrievals of sea surface temperature (SST) at instrument nadir are investigated for cold bias caused by unscreened optically-thin cirrus (OTC) clouds (cloud optical depth ≤ 0.3; COD). Level 2 split-window SST retrievals over tropical oceans (30° S - 30° N) from Moderate Resolution Imaging Spectroradiometer (MODIS) radiances collected aboard the NASA Aqua satellite (Aqua-MODIS) are collocated with cloud profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, mounted on the independent NASA CALIPSO satellite. OTC are present in approximately 25% of tropical quality-assured (QA) Aqua-MODIS Level-2 data, representing over 99% of all contaminating cirrus found. This results in cold-biased SST retrievals using either split- (MODIS, AVHRR and VIIRS) or triple-window (AVHRR and VIIRS only) retrieval methods. SST retrievals are modeled based on operational algorithms using radiative transfer model simulations conducted with a hypothetical 1.5 km thick OTC cloud placed incrementally from 10.0 - 18.0 km above mean sea level for cloud optical depths (COD) between 0.0 - 0.3. Corresponding cold bias estimates for each sensor are estimated using relative Aqua-MODIS cloud contamination frequencies as a function of cloud top height and COD (assuming them consistent across each platform) integrated within each corresponding modeled cold bias matrix. Split-window relative OTC cold biases, for any single observation, range from 0.40° - 0.49° C for the three sensors, with an absolute (bulk mean) bias between 0.10° - 0.13° C. Triple-window retrievals are more resilient, ranging from 0.03° - 0.04° C relative and 0.11° - 0.16° C absolute. Cold biases are constant across the Pacific and Indian Ocean domains. Absolute bias is smaller over the Atlantic, but relative bias is larger due to different cloud properties indicating that this issue persists globally.

Sensitivity Study of IROE Cloud Retrievals Using VIIRS M-Bands and Combined VIIRS/CrIS IR Observations

NASA Astrophysics Data System (ADS)

Wang, C.; Platnick, S. E.; Meyer, K.; Ackerman, S. A.; Holz, R.; Heidinger, A.

2017-12-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi-NPP spacecraft is considered as the next generation of instrument providing operational moderate resolution imaging capabilities after the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. However, cloud-top property (CTP) retrieval algorithms designed for the two instruments cannot be identical because of the absence of CO2 bands on VIIRS. In this study, we conduct a comprehensive sensitivity study of cloud retrievals utilizing a IR-Optimal Estimation (IROE) based algorithm. With a fast IR radiative transfer model, the IROE simultaneously retrieves cloud-top height (CTH), cloud optical thickness (COT), cloud effective radius (CER) and corresponding uncertainties using a set of IR bands. Three retrieval runs are implemented for this sensitivity study: retrievals using 1) three native VIIRS M-Bands at 750m resolution (8.5-, 11-, and 12-μm), 2) three native VIIRS M-Bands with spectrally integrated CO2 bands from the Cross-Track Infrared Sounder (CrIS), and 3) six MODIS IR bands (8.5-, 11-, 12-, 13.3-, 13.6-, and 13.9-μm). We select a few collocated MODIS and VIIRS granules for pixel-level comparison. Furthermore, aggregated daily and monthly cloud properties from the three runs are also compared. It shows that, the combined VIIRS/CrIS run agrees well with the MODIS-only run except for pixels near cloud edges. The VIIRS-only run is close to its counterparts when clouds are optically thick. However, for optically thin clouds, the VIIRS-only run can be readily influenced by the initial guess. Large discrepancies and uncertainties can be found for optically thin clouds from the VIIRS-only run.

Synergistic Use of MODIS and AIRS in a Variational Retrieval of Cloud Parameters.

NASA Astrophysics Data System (ADS)

Li, Jun; Menzel, W. Paul; Zhang, Wenjian; Sun, Fengying; Schmit, Timothy J.; Gurka, James J.; Weisz, Elisabeth

2004-11-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS's) Aqua satellite enable global monitoring of the distribution of clouds. MODIS is able to provide a cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size, and cloud optical thickness at high spatial resolution (1 5 km). The combined MODIS AIRS system offers the opportunity for improved cloud products, better than from either system alone; this improvement is demonstrated in this paper with both simulated and real radiances. A one-dimensional variational (1DVAR) methodology is used to retrieve the CTP and ECA from AIRS longwave (650 790 cm-1 or 15.38 12.65 μm) cloudy radiance measurements (hereinafter referred to as MODIS AIRS 1DVAR). The MODIS AIRS 1DVAR cloud properties show significant improvement over the MODIS-alone cloud properties and slight improvement over AIRS-alone cloud properties in a simulation study, while MODIS AIRS 1DVAR is much more computationally efficient than the AIRS-alone 1DVAR; comparisons with radiosonde observations show that CTPs improve by 10 40 hPa for MODIS AIRS CTPs over those from MODIS alone. The 1DVAR approach is applied to process the AIRS longwave cloudy radiance measurements; results are compared with MODIS and Geostationary Operational Environmental Satellite sounder cloud products. Data from ground-based instrumentation at the Atmospheric Radiation Measurement Program Cloud and Radiation Test Bed in Oklahoma are used for validation; results show that MODIS AIRS improves the MODIS CTP, especially in low-level clouds. The operational use of a high-spatial-resolution imager, along with information from a high-spectral-resolution sounder will be possible with instruments planned for the next-generation geostationary operational instruments.

Spatial and Temporal Distribution of Clouds as Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Menzel, Paul; Ackerman, Steven A.

2006-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24,2000 for Terra and June 24,2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has 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, and 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. Over the last year, extensive improvements and enhancements in the global cloud products have been implemented, and reprocessing of all MODIS data on Terra has commenced since first light in February 2000. In the cloud mask algorithm, the most extensive improvements were in distinguishing clouds at nighttime, including the challenging polar darkness regions of the world. Additional improvements have been made to properly distinguish sunglint from clouds in the tropical ocean regions, and to improve the identification of clouds from snow during daytime in Polar Regions. We will show global monthly mean cloud fraction for both Terra and Aqua, and show how similar the global daytime cloud fraction is from these morning and afternoon orbits, respectively. We will also show the zonal distribution of cloud fraction over land and ocean regions for both Terra and Aqua, and show the time series of global cloud fraction from July 2002 through June 2006.

Estimating the Direct Radiative Effect of Absorbing Aerosols Overlying Marine Boundary Layer Clouds in the Southeast Atlantic Using MODIS and CALIOP

NASA Technical Reports Server (NTRS)

Meyer, Kerry; Platnick, Steven; Oreopoulos, Lazaros; Lee, Dongmin

2013-01-01

Absorbing aerosols such as smoke strongly absorb solar radiation, particularly at ultraviolet and visible/near-infrared (VIS/NIR) wavelengths, and their presence above clouds can have considerable implications. It has been previously shown that they have a positive (i.e., warming) direct aerosol radiative effect (DARE) when overlying bright clouds. Additionally, they can cause biased passive instrument satellite retrievals in techniques that rely on VIS/NIR wavelengths for inferring the cloud optical thickness (COT) and effective radius (re) of underlying clouds, which can in turn yield biased above-cloud DARE estimates. Here we investigate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical property retrieval biases due to overlying absorbing aerosols observed by Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and examine the impact of these biases on above-cloud DARE estimates. The investigation focuses on a region in the southeast Atlantic Ocean during August and September (2006-2011), where smoke from biomass burning in southern Africa overlies persistent marine boundary layer stratocumulus clouds. Adjusting for above-cloud aerosol attenuation yields increases in the regional mean liquid COT (averaged over all ocean-only liquid clouds) by roughly 6%; mean re increases by roughly 2.6%, almost exclusively due to the COT adjustment in the non-orthogonal retrieval space. It is found that these two biases lead to an underestimate of DARE. For liquid cloud Aqua MODIS pixels with CALIOP-observed above-cloud smoke, the regional mean above-cloud radiative forcing efficiency (DARE per unit aerosol optical depth (AOD)) at time of observation (near local noon for Aqua overpass) increases from 50.9Wm(sup-2)AOD(sup-1) to 65.1Wm(sup-2)AOD(sup -1) when using bias-adjusted instead of nonadjusted MODIS cloud retrievals.

Spatial and Temporal Distribution of Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Menzel, W. Paul; Ackerman, Steven A.; Hubanks, Paul A.

2012-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched aboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. A comprehensive set of remote sensing algorithms for the retrieval of cloud physical and optical properties have enabled over twelve years of continuous observations of cloud properties from Terra and over nine years from Aqua. The archived products from these algorithms include 1 km pixel-level (Level-2) and global gridded Level-3 products. 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. Results include the latitudinal distribution of cloud optical and radiative properties for both liquid water and ice clouds, as well as latitudinal distributions of cloud top pressure and cloud top temperature. MODIS finds the cloud fraction, as derived by the cloud mask, is nearly identical during the day and night, with only modest diurnal variation. Globally, the cloud fraction derived by the MODIS cloud mask is approx.67%, with somewhat more clouds over land during the afternoon and less clouds over ocean in the afternoon, with very little difference in global cloud cover between Terra and Aqua. Overall, cloud fraction over land is approx.55%, with a distinctive seasonal cycle, whereas the ocean cloudiness is much higher, around 72%, with much reduced seasonal variation. Cloud top pressure and temperature have distinct spatial and temporal patterns, and clearly reflect our understanding of the global cloud distribution. High clouds are especially prevalent over the northern hemisphere continents between 30 and 50 . Aqua and Terra have comparable zonal cloud top pressures, with Aqua having somewhat higher clouds (cloud top pressures lower by 100 hPa) over land due to afternoon deep convection. The coldest cloud tops (colder than 230 K) generally occur over Antarctica and the high clouds in the tropics (ITCZ and the deep convective clouds over the western tropical Pacific and Indian sub-continent).

MODIS Direct Broadcast and Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee

2004-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard both Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). Equipped with direct broadcast capability, the MODIS measurements can be received worldwide real time. There are 82 ingest sites (over 900 users, listed on the Direct Readout Portal) around the world for Terra/Aqua-MODIS Direct Broadcast DB) downlink. This represents 27 (6 from EOS science team members) science research organizations for DB land, ocean and atmospheric processing, and 53 companies that base their application algorithms and value added products on DB data. In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of aerosol/cloud optical properties, especially optical thickness and effective particle size. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Preliminary results will be presented and discussed their implications in regional-to-global climatic effects.

Remote sensing of cirrus cloud vertical size profile using MODIS data

NASA Astrophysics Data System (ADS)

Wang, Xingjuan; Liou, K. N.; Ou, Steve S. C.; Mace, G. G.; Deng, M.

2009-05-01

This paper describes an algorithm for inferring cirrus cloud top and cloud base effective particle sizes and cloud optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS) 0.645, 1.64 and 2.13, and 3.75 μm band reflectances/radiances. This approach uses a successive minimization method based on a look-up library of precomputed reflectances/radiances from an adding-doubling radiative transfer program, subject to corrections for Rayleigh scattering at the 0.645 μm band, above-cloud water vapor absorption, and 3.75 μm thermal emission. The algorithmic accuracy and limitation of the retrieval method were investigated by synthetic retrievals subject to the instrument noise and the perturbation of input parameters. The retrieval algorithm was applied to three MODIS cirrus scenes over the Atmospheric Radiation Measurement Program's southern Great Plain site, north central China, and northeast Asia. The reliability of retrieved cloud optical thicknesses and mean effective particle sizes was evaluated by comparison with MODIS cloud products and qualitatively good correlations were obtained for all three cases, indicating that the performance of the vertical sizing algorithm is comparable with the MODIS retrieval program. Retrieved cloud top and cloud base ice crystal effective sizes were also compared with those derived from the collocated ground-based millimeter wavelength cloud radar for the first case and from the Cloud Profiling Radar onboard CloudSat for the other two cases. Differences between retrieved and radar-derived cloud properties are discussed in light of assumptions made in the collocation process and limitations in radar remote sensing characteristics.

Fast Simulators for Satellite Cloud Optical Centroid Pressure Retrievals, 1. Evaluation of OMI Cloud Retrievals

NASA Technical Reports Server (NTRS)

Joiner, J.; Vasilkov, A.; Gupta, P.; Bhartia, P. K.; Veefkind, P.; Sneep, M.; de Haan, J.; Polonsky, I.; Spurr, R.

2012-01-01

The cloud Optical Centroid Pressure (OCP), also known as the effective cloud pressure, is a satellite-derived parameter that is commonly used in trace-gas retrievals to account for the effects of clouds on near-infrared through ultraviolet radiance measurements. Fast simulators are desirable to further expand the use of cloud OCP retrievals into the operational and climate communities for applications such as data assimilation and evaluation of cloud vertical structure in general circulation models. In this paper, we develop and validate fast simulators that provide estimates of the cloud OCP given a vertical profile of optical extinction. We use a pressure-weighting scheme where the weights depend upon optical parameters of clouds and/or aerosol. A cloud weighting function is easily extracted using this formulation. We then use fast simulators to compare two different satellite cloud OCP retrievals from the Ozone Monitoring Instrument (OMI) with estimates based on collocated cloud extinction profiles from a combination of CloudS at radar and MODIS visible radiance data. These comparisons are made over a wide range of conditions to provide a comprehensive validation of the OMI cloud OCP retrievals. We find generally good agreement between OMI cloud OCPs and those predicted by CloudSat. However, the OMI cloud OCPs from the two independent algorithms agree better with each other than either does with the estimates from CloudSat/MODIS. Differences between OMI cloud OCPs and those based on CloudSat/MODIS may result from undetected snow/ice at the surface, cloud 3-D effects, low altitude clouds missed by CloudSat, and the fact that CloudSat only observes a relatively small fraction of an OMI field-of-view.

Spatial and Temporal Distribution of Tropospheric Clouds and Aerosols Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Menzel, W. Paul; Ackerman, Steven A.; Remer, Lorraine A.

2006-01-01

Remote sensing of cloud and aerosol optical properties is routinely obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites. Instruments that are being used to enhance our ability to characterize the global distribution of cloud and aerosol properties include well-calibrated multispectral radiometers that measure in the visible, near-infrared, and thermal infrared. The availability of thermal channels to enhance detection of cloud when estimating aerosol properties is an important improvement. In this paper, we describe the radiative properties of clouds as currently determined from satellites (cloud fraction, optical thickness, cloud top pressure, and cloud particle effective radius) and highlight the global/regional cloud microphysical properties currently available for assessing climate variability and forcing. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective particle radius for selected geographical locations around the world. In addition, we will illustrate the radiative and microphysical properties of aerosol particles (in cloud free regions) that are currently available from space-based observations, and show the latitudinal distribution of aerosol optical properties over both land and ocean surfaces.

3D Aerosol-Cloud Radiative Interaction Observed in Collocated MODIS and ASTER Images of Cumulus Cloud Fields

NASA Technical Reports Server (NTRS)

Wen, Guoyong; Marshak, Alexander; Cahalan, Robert F.; Remer, Lorraine A.; Kleidman, Richard G.

2007-01-01

3D aerosol-cloud interaction is examined by analyzing two images containing cumulus clouds in biomass burning regions in Brazil. The research consists of two parts. The first part focuses on identifying 3D clo ud impacts on the reflectance of pixel selected for the MODIS aerosol retrieval based purely on observations. The second part of the resea rch combines the observations with radiative transfer computations to identify key parameters in 3D aerosol-cloud interaction. We found that 3D cloud-induced enhancement depends on optical properties of nearb y clouds as well as wavelength. The enhancement is too large to be ig nored. Associated biased error in 1D aerosol optical thickness retrie val ranges from 50% to 140% depending on wavelength and optical prope rties of nearby clouds as well as aerosol optical thickness. We caution the community to be prudent when applying 1D approximations in comp uting solar radiation in dear regions adjacent to clouds or when usin g traditional retrieved aerosol optical thickness in aerosol indirect effect research.

The Operational MODIS Cloud Optical and Microphysical Property Product: Overview of the Collection 6 Algorithm and Preliminary Results

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Galina; Amarasinghe, Nandana; Marchant, Benjamin; Arnold, G. Thomas

2012-01-01

Operational Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of cloud optical and microphysical properties (part of the archived products MOD06 and MYD06, for MODIS Terra and Aqua, respectively) are currently being reprocessed along with other MODIS Atmosphere Team products. The latest "Collection 6" processing stream, which is expected to begin production by summer 2012, includes updates to the previous cloud retrieval algorithm along with new capabilities. The 1 km retrievals, based on well-known solar reflectance techniques, include cloud optical thickness, effective particle radius, and water path, as well as thermodynamic phase derived from a combination of solar and infrared tests. Being both global and of high spatial resolution requires an algorithm that is computationally efficient and can perform over all surface types. Collection 6 additions and enhancements include: (i) absolute effective particle radius retrievals derived separately from the 1.6 and 3.7 !-lm bands (instead of differences relative to the standard 2.1 !-lm retrieval), (ii) comprehensive look-up tables for cloud reflectance and emissivity (no asymptotic theory) with a wind-speed interpolated Cox-Munk BRDF for ocean surfaces, (iii) retrievals for both liquid water and ice phases for each pixel, and a subsequent determination of the phase based, in part, on effective radius retrieval outcomes for the two phases, (iv) new ice cloud radiative models using roughened particles with a specified habit, (v) updated spatially-complete global spectral surface albedo maps derived from MODIS Collection 5, (vi) enhanced pixel-level uncertainty calculations incorporating additional radiative error sources including the MODIS L1 B uncertainty index for assessing band and scene-dependent radiometric uncertainties, (v) and use of a new 1 km cloud top pressure/temperature algorithm (also part of MOD06) for atmospheric corrections and low cloud non-unity emissivity temperature adjustments.

MODIS comparisons with northeastern Pacific in situ stratocumulus microphysics

NASA Astrophysics Data System (ADS)

Noble, Stephen R.; Hudson, James G.

2015-08-01

Vertical sounding measurements within stratocumuli during two aircraft field campaigns, Marine Stratus/stratocumulus Experiment (MASE) and Physics of Stratocumulus Top (POST), are used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical thickness (COT), cloud liquid water path (LWP), and cloud effective radius (re). In situ COT, LWP, and re were calculated using 5 m vertically averaged droplet probe measurements of complete vertical cloud penetrations. MODIS COT, LWP, and re 1 km pixels were averaged along these penetrations. COT comparisons in POST showed strong correlations and a near 1:1 relationship. In MASE, comparisons showed strong correlations; however, MODIS COT exceeded in situ COT, likely due to larger temporal differences between MODIS and in situ measurements. LWP comparisons between two cloud probes show good agreement for POST but not MASE, giving confidence to POST data. Both projects provided strong LWP correlations but MODIS exceeded in situ by 14-36%. MODIS in situ re correlations were strong, but MODIS 2.1 µm re exceeded in situ re, which contributed to LWP bias; in POST, MODIS re was 20-30% greater than in situ re. Maximum in situ re near cloud top showed comparisons nearer 1:1. Other MODIS re bands (3.7 µm and 1.6 µm) showed similar comparisons. Temporal differences between MODIS and in situ measurements, airplane speed differences, and cloud probe artifacts were likely causes of weaker MASE correlations. POST COT comparison was best for temporal differences under 20 min. POST data validate MODIS COT but it also implies a positive MODIS re bias that propagates to LWP while still capturing variability.

AIRS Subpixel Cloud Characterization Using MODIS Cloud Products.

NASA Astrophysics Data System (ADS)

Li, Jun; Menzel, W. Paul; Sun, Fengying; Schmit, Timothy J.; Gurka, James

2004-08-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS's) Aqua satellite enable improved global monitoring of the distribution of clouds. MODIS is able to provide, at high spatial resolution (1 5 km), a cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), and cloud optical thickness (COT). AIRS is able to provide CTP, ECA, CPS, and COT at coarser spatial resolution (13.5 km at nadir) but with much better accuracy using its high-spectral-resolution measurements. The combined MODIS AIRS system offers the opportunity for improved cloud products over those possible from either system alone. The key steps for synergistic use of imager and sounder radiance measurements are 1) collocation in space and time and 2) imager cloud amount, type, and phase determination within the sounder pixel. The MODIS and AIRS measurements from the EOS Aqua satellite provide the opportunity to study the synergistic use of advanced imager and sounder measurements. As the first step, the MODIS classification procedure is applied to identify various surface and cloud types within an AIRS footprint. Cloud-layer information (lower, midlevel, or high clouds) and phase information (water, ice, or mixed-phase clouds) within the AIRS footprint are sorted and characterized using MODIS 1-km-spatial-resolution data. The combined MODIS and AIRS data for various scenes are analyzed to study the utility of the synergistic use of high-spatial-resolution imager products and high-spectral-resolution sounder radiance measurements. There is relevance to the optimal use of data from the Advanced Baseline Imager (ABI) and Hyperspectral Environmental Suite (HES) systems, which are to fly on the Geostationary Operational Environmental Satellite (GOES)-R.

Global monitoring of atmospheric properties by the EOS MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.

1993-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) being developed for the Earth Observing System (EOS) is well suited to the global monitoring of atmospheric properties from space. Among the atmospheric properties to be examined using MODIS observations, clouds are especially important, since they are a strong modulator of the shortwave and longwave components of the earth's radiation budget. A knowledge of cloud properties (such as optical thickness and effective radius) and their variation in space and time, which are our task objectives, is also crucial to studies of global climate change. In addition, with the use of related airborne instrumentation, such as the Cloud Absorption Radiometer (CAR) and MODIS Airborne Simulator (MAS) in intensive field experiments (both national and international campaigns, see below), various types of surface and cloud properties can be derived from the measured bidirectional reflectances. These missions have provided valuable experimental data to determine the capability of narrow bandpass channels in examining the Earth's atmosphere and to aid in defining algorithms and building an understanding of the ability of MODIS to remotely sense atmospheric conditions for assessing global change. Therefore, the primary task objective is to extend and expand our algorithm for retrieving the optical thickness and effective radius of clouds from radiation measurements to be obtained from MODIS. The secondary objective is to obtain an enhanced knowledge of surface angular and spectral properties that can be inferred from airborne directional radiance measurements.

A comparison of Aqua MODIS ice and liquid water cloud physical and optical properties between collection 6 and collection 5.1: Pixel-to-pixel comparisons

NASA Astrophysics Data System (ADS)

Yi, Bingqi; Rapp, Anita D.; Yang, Ping; Baum, Bryan A.; King, Michael D.

2017-04-01

We compare differences in ice and liquid water cloud physical and optical properties between Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 (C6) and collection 5.1 (C51). The C6 cloud products changed significantly due to improved calibration, improvements based on comparisons with the Cloud-Aerosol Lidar with Orthogonal Polarization, treatment of subpixel liquid water clouds, introduction of a roughened ice habit for C6 rather than the use of smooth ice particles in C51, and more. The MODIS cloud products form a long-term data set for analysis, modeling, and various purposes. Thus, it is important to understand the impact of the changes. Two cases are considered for C6 to C51 comparisons. Case 1 considers pixels with valid cloud retrievals in both C6 and C51, while case 2 compares all valid cloud retrievals in each collection. One year (2012) of level-2 MODIS cloud products are examined, including cloud effective radius (CER), optical thickness (COT), water path, cloud top pressure (CTP), cloud top temperature, and cloud fraction. Large C6-C51 differences are found in the ice CER (regionally, as large as 15 μm) and COT (decrease in annual average by approximately 25%). Liquid water clouds have higher CTP in marine stratocumulus regions in C6 but lower CTP globally (-5 hPa), and there are 66% more valid pixels in C6 (case 2) due to the treatment of pixels with subpixel clouds. Simulated total cloud radiative signatures from C51 and C6 are compared to Clouds and the Earth's Radiant Energy System Energy Balanced And Filled (EBAF) product. The C6 CREs compare more closely with the EBAF than the C51 counterparts.

Spatial and Temporal Distribution of Tropospheric Clouds and Aerosols Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Remer, Lorraine A.; Kaufman, Yoram J.

2004-01-01

Remote sensing of cloud and aerosol optical properties is routinely obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites. Techniques that are being used to enhance our ability to characterize the global distribution of cloud and aerosol properties include well-calibrated multispectral radiometers that rely on visible, near-infrared, and thermal infrared channels. The availability of thermal channels to aid in cloud screening for aerosol properties is an important additional piece of information that has not always been incorporated into sensor designs. In this paper, we describe the radiative properties of clouds as currently determined from satellites (cloud fraction, optical thickness, cloud top pressure, and cloud effective radius), and highlight the global and regional cloud microphysical properties currently available for assessing climate variability and forcing. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world. In addition, we will illustrate the radiative and microphysical properties of aerosol particles that are currently available from space-based observations, and show selected cases in which aerosol particles are observed to modify the cloud optical properties.

Comparison of CALIPSO-Like, LaRC, and MODIS Retrievals of Ice Cloud Properties over SIRTA in France and Florida during CRYSTAL-FACE

NASA Technical Reports Server (NTRS)

Chiriaco, M.; Chepfer, H.; Haeffelin, M.; Minnis, P.; Noel, V.; Platnick, S.; McGill, M.; Baumgardner, D.; Dubuisson, P.; Pelon, J.;

Spatial and Temporal Distribution of Cloud Properties Observed by MODIS: Preliminary Level-3 Results from the Collection 5 Reprocessing

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Hubanks, Paul; Pincus, Robert

2006-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of operational algorithms for the retrieval of cloud physical and optical properties (optical thickness, effective particle radius, water path, thermodynamic phase) have recently been updated and are being used in the new "Collection 5" processing stream being produced by the MODIS Adaptive Processing System (MODAPS) at NASA GSFC. All Terra and Aqua data are undergoing Collection 5 reprocessing with an expected completion date by the end of 2006. The archived products from these algorithms include 1 km pixel-level (Level-2) and global gridded Level-3 products. The cloud products have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In this talk, we will summarize the available Level-3 cloud properties and their associated statistical data sets, and show preliminary Terra and Aqua results from the available Collection 5 reprocessing effort. Anticipated results include the latitudinal distribution of cloud optical and radiative properties for both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

Intercomparisons of marine boundary layer cloud properties from the ARM CAP-MBL campaign and two MODIS cloud products

NASA Astrophysics Data System (ADS)

Zhang, Zhibo; Dong, Xiquan; Xi, Baike; Song, Hua; Ma, Po-Lun; Ghan, Steven J.; Platnick, Steven; Minnis, Patrick

2017-02-01

From April 2009 to December 2010, the Department of Energy Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) clouds over the Azores region. In this paper, we present an intercomparison of the MBL cloud properties, namely, cloud liquid water path (LWP), cloud optical thickness (COT), and cloud-droplet effective radius (CER), among retrievals from the ARM mobile facility and two Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products (Goddard Space Flight Center (GSFC)-MODIS and Clouds and Earth's Radiant Energy System-MODIS). A total of 63 daytime single-layer MBL cloud cases are selected for intercomparison. Comparison of collocated retrievals indicates that the two MODIS cloud products agree well on both COT and CER retrievals, with the correlation coefficient R > 0.95, despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 µm band (CER2.1) are significantly larger than those based on the 3.7 µm band (CER3.7). The GSFC-MODIS cloud product is collocated and compared with ground-based ARM observations at several temporal-spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL cloud cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER3.7 and CER2.1 retrievals have a lower correlation (R 0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 µm and 3.0 µm, respectively. Taking into account that the MODIS CER retrievals are only sensitive to cloud top reduces the bias only by 0.5 µm.

Multilayer Cloud Detection with the MODIS Near-Infrared Water Vapor Absorption Band

NASA Technical Reports Server (NTRS)

Wind, Galina; Platnick, Steven; King, Michael D.; Hubanks, Paul A,; Pavolonis, Michael J.; Heidinger, Andrew K.; Yang, Ping; Baum, Bryan A.

2009-01-01

Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard 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 presents difficulties for retrieving cloud effective radius using single layer plane-parallel cloud models. The algorithm uses the MODIS 0.94 micron 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 micron 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

Abstract Art or Arbiters of Energy?

NASA Technical Reports Server (NTRS)

2002-01-01

More than just the idle stuff of daydreams, clouds help control the flow of radiant energy around our world. Clouds are plentiful and widespread throughout Earth's atmosphere-covering up to 75 percent of our planet at any given time-so they play a dominant role in determining how much sunlight reaches the surface, how much sunlight is reflected back into space, how and where warmth is spread around the globe, and how much heat escapes from the surface and atmosphere back into space. Clouds are also highly variable. Clouds' myriad variations through time and space make them one of the greatest areas of uncertainty in scientists' understanding and predictions of climate change. In short, they play a central role in our world's climate system. The false-color image above shows a one-month composite of cloud optical thickness measured by the Moderate-resolution Imaging Spectroradiometer (MODIS) and averaged globally for April 2001. Optical thickness is a measure of how much solar radiation is not allowed to travel through a column of atmosphere. Areas colored red and yellow indicate very cloudy skies, on average, while areas colored green and light blue show moderately cloudy skies. Dark blue regions show where there is little or no cloud cover. This data product is an important new tool for helping scientists understand the roles clouds play in our global climate system. MODIS gives scientists new capabilities for measuring the structure and composition of clouds. MODIS observes the entire Earth almost every day in 36 spectral bands ranging from visible to thermal infrared wavelengths, enabling it to quantify a wide suite of clouds' physical and radiative properties. Specifically, MODIS can determine whether a cloud is composed of ice or water particles (or some combination of the two), it can measure the effective radius of the particles within a cloud, it can determine the temperature and altitude of cloud tops, and it can observe how much sunlight passes through a cloud. MODIS is one of five sensors flying aboard NASA's Terra satellite, the flagship in NASA's Earth Observing System, launched in December 1999. For more information about this and other new MODIS products, read NASA Unveils Spectacular Suite of New Global Data Products from MODIS. Image courtesy MODIS Atmosphere Group, NASA GSFC

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations: 1. Forward model, error analysis, and information content

NASA Astrophysics Data System (ADS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-05-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (τ), effective radius (reff), and cloud top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary data sets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations. Part I: Forward model, error analysis, and information content.

PubMed

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-05-27

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness ( τ ), effective radius ( r eff ), and cloud-top height ( h ). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

MODIS comparisons with northeastern Pacific in situ stratocumulus microphysics

PubMed Central

Noble, Stephen R.

2015-01-01

Abstract Vertical sounding measurements within stratocumuli during two aircraft field campaigns, Marine Stratus/stratocumulus Experiment (MASE) and Physics of Stratocumulus Top (POST), are used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical thickness (COT), cloud liquid water path (LWP), and cloud effective radius (r e). In situ COT, LWP, and r e were calculated using 5 m vertically averaged droplet probe measurements of complete vertical cloud penetrations. MODIS COT, LWP, and r e 1 km pixels were averaged along these penetrations. COT comparisons in POST showed strong correlations and a near 1:1 relationship. In MASE, comparisons showed strong correlations; however, MODIS COT exceeded in situ COT, likely due to larger temporal differences between MODIS and in situ measurements. LWP comparisons between two cloud probes show good agreement for POST but not MASE, giving confidence to POST data. Both projects provided strong LWP correlations but MODIS exceeded in situ by 14–36%. MODIS in situ r e correlations were strong, but MODIS 2.1 µm r e exceeded in situ r e, which contributed to LWP bias; in POST, MODIS r e was 20–30% greater than in situ r e. Maximum in situ r e near cloud top showed comparisons nearer 1:1. Other MODIS r e bands (3.7 µm and 1.6 µm) showed similar comparisons. Temporal differences between MODIS and in situ measurements, airplane speed differences, and cloud probe artifacts were likely causes of weaker MASE correlations. POST COT comparison was best for temporal differences under 20 min. POST data validate MODIS COT but it also implies a positive MODIS r e bias that propagates to LWP while still capturing variability. PMID:27708990

MODIS comparisons with northeastern Pacific in situ stratocumulus microphysics

DOE PAGES

Noble, Stephen R.; Hudson, James G.

2015-07-22

Here, vertical sounding measurements within stratocumuli during two aircraft field campaigns, Marine Stratus/stratocumulus Experiment (MASE) and Physics of Stratocumulus Top (POST), are used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical thickness (COT), cloud liquid water path (LWP), and cloud effective radius (r e). In situ COT, LWP, and r e were calculated using 5 m vertically averaged droplet probe measurements of complete vertical cloud penetrations. MODIS COT, LWP, and r e 1 km pixels were averaged along these penetrations. COT comparisons in POST showed strong correlations and a near 1:1 relationship. In MASE, comparisons showed strong correlations; however,more » MODIS COT exceeded in situ COT, likely due to larger temporal differences between MODIS and in situ measurements. LWP comparisons between two cloud probes show good agreement for POST but not MASE, giving confidence to POST data. Both projects provided strong LWP correlations but MODIS exceeded in situ by 14–36%. MODIS in situ r e correlations were strong, but MODIS 2.1 µm r e exceeded in situ r e, which contributed to LWP bias; in POST, MODIS r e was 20–30% greater than in situ r e. Maximum in situ r e near cloud top showed comparisons nearer 1:1. Other MODIS r e bands (3.7 µm and 1.6 µm) showed similar comparisons. Temporal differences between MODIS and in situ measurements, airplane speed differences, and cloud probe artifacts were likely causes of weaker MASE correlations. POST COT comparison was best for temporal differences under 20 min. POST data validate MODIS COT but it also implies a positive MODIS r e bias that propagates to LWP while still capturing variability.« less

Intercomparisons of Marine Boundary Layer Cloud Properties from the ARM CAP-MBL Campaign and Two MODIS Cloud Products

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Dong, Xiquan; Xi, Baike; Song, Hua; Ma, Po-Lun; Ghan, Steven J.; Platnick, Steven; Minnis, Patrick

2017-01-01

From April 2009 to December 2010, the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) clouds over the Azores region. In this paper, we present an inter-comparison of the MBL cloud properties, namely, cloud liquid water path (LWP), cloud optical thickness (COT) and cloud-droplet effective radius (CER), among retrievals from the ARM mobile facility (AMF) and two Moderate Resolution Spectroradiometer (MODIS) cloud products (GSFC-MODIS and CERES-MODIS). A total of 63 daytime single-layer MBL cloud cases are selected for inter-comparison. Comparison of collocated retrievals indicates that the two MODIS cloud products agree well on both COT and CER retrievals, with the correlation coefficient R greater than 0.95 despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 micrometers band (CER(sub 2.1)) is significantly smaller than that based on the 3.7 micrometers band (CER(sub 3.7)). The GSFC-MODIS cloud product is collocated and compared with ground-based ARM observations at several temporal spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL cloud cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER(sub 3.7) and CER(sub 2.1) retrievals have a lower correlation (R is approximately 0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 micrometers and 3.0 micrometers, respectively. Taking into account that the MODIS CER retrievals are only sensitive to cloud top reduces the bias only by 0.5 micrometers.

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-cloud Aerosols over Ocean Using CALIOP and MODIS Data

NASA Technical Reports Server (NTRS)

Zhang, Z.; Meyer, K.; Platnick, S.; Oreopoulos, L.; Lee, D.; Yu, H.

2013-01-01

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It accounts for the overlapping of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure. Effects of sub-grid scale cloud and aerosol variations on DRE are accounted for. It is computationally efficient through using grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table in radiative transfer calculations. We verified that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous shortwave DRE that generally agrees with more rigorous pixel-level computation within 4%. We have also computed the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global ocean based on 4 yr of CALIOP and MODIS data. We found that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds.

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

NASA Technical Reports Server (NTRS)

Zhang, Z.; Meyer, K.; Platnick, S.; Oreopoulos, L.; Lee, D.; Yu, H.

2014-01-01

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It accounts for the overlapping of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure. Effects of sub-grid scale cloud and aerosol variations on DRE are accounted for. It is computationally efficient through using grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table in radiative transfer calculations. We verified that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous shortwave DRE that generally agrees with more rigorous pixel-level computation within 4. We have also computed the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global ocean based on 4 yr of CALIOP and MODIS data. We found that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds.

MOD06 Optical and Microphysical Retrievals

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Arnold, G. T.; Dinsick, J.; Gatebe, C. K.; Gray, M. A.; Hubanks, P. A.; Moody, E. G.; Wind, B.; Wind, G.

2003-01-01

Major efforts over the past six months included: (1) submission of MOD06 Optical and Microphysical Retrieval recompetition proposal, (2) delivery of a MODIS Atmosphere Level-3 update, (3) delivery of the MODIS Atmosphere s new combined Level-2 product, (4) development of an above-cloud precipitable water research algorithm and a multi-layer cloud detection algorithm, (5) continued development of a Fortran 90 version of the retrieval code for use with MAS as well as operational MODIS processing, (6) preliminary analysis of CRYSTAL-FACE field experiment in July 2002, (7) continued analysis of data obtained during the SAFARI 2000 dry season campaign in southern Africa, and the Arctic FIRE-ACE experiment.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noble, Stephen R.; Hudson, James G.

Here, vertical sounding measurements within stratocumuli during two aircraft field campaigns, Marine Stratus/stratocumulus Experiment (MASE) and Physics of Stratocumulus Top (POST), are used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical thickness (COT), cloud liquid water path (LWP), and cloud effective radius (r e). In situ COT, LWP, and r e were calculated using 5 m vertically averaged droplet probe measurements of complete vertical cloud penetrations. MODIS COT, LWP, and r e 1 km pixels were averaged along these penetrations. COT comparisons in POST showed strong correlations and a near 1:1 relationship. In MASE, comparisons showed strong correlations; however,more » MODIS COT exceeded in situ COT, likely due to larger temporal differences between MODIS and in situ measurements. LWP comparisons between two cloud probes show good agreement for POST but not MASE, giving confidence to POST data. Both projects provided strong LWP correlations but MODIS exceeded in situ by 14–36%. MODIS in situ r e correlations were strong, but MODIS 2.1 µm r e exceeded in situ r e, which contributed to LWP bias; in POST, MODIS r e was 20–30% greater than in situ r e. Maximum in situ r e near cloud top showed comparisons nearer 1:1. Other MODIS r e bands (3.7 µm and 1.6 µm) showed similar comparisons. Temporal differences between MODIS and in situ measurements, airplane speed differences, and cloud probe artifacts were likely causes of weaker MASE correlations. POST COT comparison was best for temporal differences under 20 min. POST data validate MODIS COT but it also implies a positive MODIS r e bias that propagates to LWP while still capturing variability.« less

Comparison of the MODIS Multilayer Cloud Detection and Thermodynamic Phase Products with CALIPSO and CloudSat

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Gala; Holz, Robert E.; Ackerman, Steven A.; Nagle, Fred W.

2008-01-01

CALIPSO and CloudSat, launched in June 2006, provide global active remote sensing measurements of clouds and aerosols that can be used for validation of a variety of passive imager retrievals derived from instruments flying on the Aqua spacecraft and other A-Train platforms. The most recent processing effort for the MODIS Atmosphere Team, referred to as the "Collection 5" stream, includes a research-level multilayer cloud detection algorithm that uses both thermodynamic phase information derived from a combination of solar and thermal emission bands to discriminate layers of different phases, as well as true layer separation discrimination using a moderately absorbing water vapor band. The multilayer detection algorithm is designed to provide a means of assessing the applicability of 1D cloud models used in the MODIS cloud optical and microphysical product retrieval, which are generated at a 1 h resolution. Using pixel-level collocations of MODIS Aqua, CALIOP, and CloudSat radar measurements, we investigate the global performance of the thermodynamic phase and multilayer cloud detection algorithms.

Retrieval, Inter-Comparison, and Validation of Above-Cloud Aerosol Optical Depth from A-train Sensors

NASA Technical Reports Server (NTRS)

Jethva, Hiren; Torres, Omar; Bhartia, Pawan K.; Remer, Lorraine; Redemann, Jens; Dunagan, Stephen E.; Livingston, John; Shinozuka, Yohei; Kacenelenbogen, Meloe; Segal-Rosenbeimer, Michal;

Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals

NASA Astrophysics Data System (ADS)

Holz, R. E.; Platnick, S.; Meyer, K.; Vaughan, M.; Heidinger, A.; Yang, P.; Wind, G.; Dutcher, S.; Ackerman, S.; Amarasinghe, N.; Nagle, F.; Wang, C.

2015-10-01

Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (< 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of two bias between the MODIS and CALIOP IOT retrievals. This bias is investigated using an infrared (IR) radiative closure approach that compares both products with MODIS IR cirrus retrievals developed for this assessment. The analysis finds that both the MODIS C5 and the unconstrained CALIOP V3 retrievals are biased (high and low, respectively) relative to the IR IOT retrievals. Based on this finding, the MODIS and CALIOP algorithms are investigated with the goal of explaining and minimizing the biases relative to the IR. For MODIS we find that the assumed ice single scattering properties used for the C5 retrievals are not consistent with the mean IR COT distribution. The C5 ice scattering database results in the asymmetry parameter (g) varying as a function of effective radius with mean values that are too large. The MODIS retrievals have been brought into agreement with the IR by adopting a new ice scattering model for Collection 6 (C6) consisting of a modified gamma distribution comprised of a single habit (severely roughened aggregated columns); the C6 ice cloud optical property models have a constant g ~ 0.75 in the mid-visible spectrum, 5-15 % smaller than C5. For CALIOP, the assumed lidar ratio for unconstrained retrievals is fixed at 25 sr for the V3 data products. This value is found to be inconsistent with the constrained (predominantly nighttime) CALIOP retrievals. An experimental data set was produced using a modified lidar ratio of 32 sr for the unconstrained retrievals (an increase of 28 %), selected to provide consistency with the constrained V3 results. These modifications greatly improve the agreement with the IR and provide consistency between the MODIS and CALIOP products. Based on these results the recently released MODIS C6 optical products use the single habit distribution given above, while the upcoming CALIOP V4 unconstrained algorithm will use higher lidar ratios for unconstrained retrievals.

Resolving Ice Cloud Optical Thickness Biases Between CALIOP and MODIS Using Infrared Retrievals

NASA Technical Reports Server (NTRS)

Holz, R. E.; Platnick, S.; Meyer, K.; Vaughan, M.; Heidinger, A.; Yang, P.; Wind, G.; Dutcher, S.; Ackerman, S.; Amarasinghe, N.;

Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals

NASA Astrophysics Data System (ADS)

Holz, Robert E.; Platnick, Steven; Meyer, Kerry; Vaughan, Mark; Heidinger, Andrew; Yang, Ping; Wind, Gala; Dutcher, Steven; Ackerman, Steven; Amarasinghe, Nandana; Nagle, Fredrick; Wang, Chenxi

2016-04-01

Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light-scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (< 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of 2 bias between the MODIS and CALIOP IOT retrievals. This bias is investigated using an infrared (IR) radiative closure approach that compares both products with MODIS IR cirrus retrievals developed for this assessment. The analysis finds that both the MODIS C5 and the unconstrained CALIOP V3 retrievals are biased (high and low, respectively) relative to the IR IOT retrievals. Based on this finding, the MODIS and CALIOP algorithms are investigated with the goal of explaining and minimizing the biases relative to the IR. For MODIS we find that the assumed ice single-scattering properties used for the C5 retrievals are not consistent with the mean IR COT distribution. The C5 ice scattering database results in the asymmetry parameter (g) varying as a function of effective radius with mean values that are too large. The MODIS retrievals have been brought into agreement with the IR by adopting a new ice scattering model for Collection 6 (C6) consisting of a modified gamma distribution comprised of a single habit (severely roughened aggregated columns); the C6 ice cloud optical property models have a constant g ≈ 0.75 in the mid-visible spectrum, 5-15 % smaller than C5. For CALIOP, the assumed lidar ratio for unconstrained retrievals is fixed at 25 sr for the V3 data products. This value is found to be inconsistent with the constrained (predominantly nighttime) CALIOP retrievals. An experimental data set was produced using a modified lidar ratio of 32 sr for the unconstrained retrievals (an increase of 28 %), selected to provide consistency with the constrained V3 results. These modifications greatly improve the agreement with the IR and provide consistency between the MODIS and CALIOP products. Based on these results the recently released MODIS C6 optical products use the single-habit distribution given above, while the upcoming CALIOP V4 unconstrained algorithm will use higher lidar ratios for unconstrained retrievals.

Temporal and Spatial Distribution of Liquid Water and Ice Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, S.; Gray, M. A.; Hubanks, P. A.

2004-01-01

The Moderate Resolution Imaging Spectroradiometer (MODE) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and the Aqua spacecraft on April 26,2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from each polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 pm with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). In this paper, we describe the radiative properties of clouds as currently determined from satellites (cloud fraction, optical thickness, cloud top pressure, and cloud effective radius), and highlight the global and regional cloud microphysical properties currently available for assessing climate variability and forcing. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the globe.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations. Part I: Forward model, error analysis, and information content

PubMed Central

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2018-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (τ), effective radius (reff), and cloud-top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available. PMID:29707470

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations. Part I: Forward Model, Error Analysis, and Information Content

NASA Technical Reports Server (NTRS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (tau), effective radius (r(sub eff)), and cloud-top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations. Part I: Forward Model, Error Analysis, and Information Content

NASA Technical Reports Server (NTRS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (tau), effective radius (r(sub eff)), and cloud top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary data sets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Overview of the CERES Edition-4 Multilayer Cloud Property Datasets

NASA Astrophysics Data System (ADS)

Chang, F. L.; Minnis, P.; Sun-Mack, S.; Chen, Y.; Smith, R. A.; Brown, R. R.

2014-12-01

Knowledge of the cloud vertical distribution is important for understanding the role of clouds on earth's radiation budget and climate change. Since high-level cirrus clouds with low emission temperatures and small optical depths can provide a positive feedback to a climate system and low-level stratus clouds with high emission temperatures and large optical depths can provide a negative feedback effect, the retrieval of multilayer cloud properties using satellite observations, like Terra and Aqua MODIS, is critically important for a variety of cloud and climate applications. For the objective of the Clouds and the Earth's Radiant Energy System (CERES), new algorithms have been developed using Terra and Aqua MODIS data to allow separate retrievals of cirrus and stratus cloud properties when the two dominant cloud types are simultaneously present in a multilayer system. In this paper, we will present an overview of the new CERES Edition-4 multilayer cloud property datasets derived from Terra as well as Aqua. Assessment of the new CERES multilayer cloud datasets will include high-level cirrus and low-level stratus cloud heights, pressures, and temperatures as well as their optical depths, emissivities, and microphysical properties.

A study of the 3D radiative transfer effect in cloudy atmospheres

NASA Astrophysics Data System (ADS)

Okata, M.; Teruyuki, N.; Suzuki, K.

2015-12-01

Evaluation of the effect of clouds in the atmosphere is a significant problem in the Earth's radiation budget study with their large uncertainties of microphysics and the optical properties. In this situation, we still need more investigations of 3D cloud radiative transer problems using not only models but also satellite observational data.For this purpose, we have developed a 3D-Monte-Carlo radiative transfer code that is implemented with various functions compatible with the OpenCLASTR R-Star radiation code for radiance and flux computation, i.e. forward and backward tracing routines, non-linear k-distribution parameterization (Sekiguchi and Nakajima, 2008) for broad band solar flux calculation, and DM-method for flux and TMS-method for upward radiance (Nakajima and Tnaka 1998). We also developed a Minimum cloud Information Deviation Profiling Method (MIDPM) as a method for a construction of 3D cloud field with MODIS/AQUA and CPR/CloudSat data. We then selected a best-matched radar reflectivity factor profile from the library for each of off-nadir pixels of MODIS where CPR profile is not available, by minimizing the deviation between library MODIS parameters and those at the pixel. In this study, we have used three cloud microphysical parameters as key parameters for the MIDPM, i.e. effective particle radius, cloud optical thickness and top of cloud temperature, and estimated 3D cloud radiation budget. We examined the discrepancies between satellite observed and mode-simulated radiances and three cloud microphysical parameter's pattern for studying the effects of cloud optical and microphysical properties on the radiation budget of the cloud-laden atmospheres.

Quantifying Above-Cloud Aerosols through Integrating Multi-Sensor Measurements from A-Train Satellites

NASA Technical Reports Server (NTRS)

Zhang, Yan

2012-01-01

Quantifying above-cloud aerosols can help improve the assessment of aerosol intercontinental transport and climate impacts. Large-scale measurements of aerosol above low-level clouds had been generally unexplored until very recently when CALIPSO lidar started to acquire aerosol and cloud profiles in June 2006. Despite CALIPSO s unique capability of measuring above-cloud aerosol optical depth (AOD), such observations are substantially limited in spatial coverage because of the lidar s near-zero swath. We developed an approach that integrates measurements from A-Train satellite sensors (including CALIPSO lidar, OMI, and MODIS) to extend CALIPSO above-cloud AOD observations to substantially larger areas. We first examine relationships between collocated CALIPSO above-cloud AOD and OMI absorbing aerosol index (AI, a qualitative measure of AOD for elevated dust and smoke aerosol) as a function of MODIS cloud optical depth (COD) by using 8-month data in the Saharan dust outflow and southwest African smoke outflow regions. The analysis shows that for a given cloud albedo, above-cloud AOD correlates positively with AI in a linear manner. We then apply the derived relationships with MODIS COD and OMI AI measurements to derive above-cloud AOD over the whole outflow regions. In this talk, we will present spatial and day-to-day variations of the above-cloud AOD and the estimated direct radiative forcing by the above-cloud aerosols.

Differences in liquid cloud droplet effective radius and number concentration estimates between MODIS Collections 5.1 and 6 over global oceans.

PubMed

Rausch, John; Meyer, Kerry; Bennartz, Ralf; Platnick, Steven

2017-01-01

Differences in cloud droplet effective radius and cloud droplet number concentration (CDNC) estimates inferred from the Aqua MODIS Collections 5.1 and 6 cloud products (MYD06) are examined for warm clouds over global oceans for the year 2008. Individual pixel level retrievals for both collections are aggregated to 1° × 1° and compared globally and regionally for the three main spectral channel pairs used for MODIS cloud optical property retrievals. Comparisons between both collections are performed for cases in which all three effective radii retrievals are classified by the MODIS Cloud Product as valid. The contribution to the observed differences of several key MYD06 Collection 6 algorithm updates are also explored, with a focus on changes to the surface reflectance model, assumed solar irradiance, above cloud emission, cloud top pressure, and pixel registration. Global results show a neutral to positive (> 50 cm -3 ) change for C6-derived CDNC relative to C5.1 for the 1.6 µm and 2.1 µm channel retrievals, corresponding to a neutral to -2 µm difference in droplet effective radius. For 3.7 µm retrievals, CDNC results show a negative change in the tropics, with differences transitioning toward positive values with increasing latitude spanning -25 to +50 cm -3 related to a +2.5 to -1 µm transition in effective radius. Cloud optical thickness differences were small relative to effective radius, and found to not significantly impact CDNC estimates. Regionally, the magnitude and behavior of the annual CDNC cycle are compared for each effective radius retrieval. Results from this study indicate significant intercollection differences in aggregated values of effective radius due to changes to the pre-computed retrieval lookup tables for ocean scenes, changes to retrieved cloud top pressure, solar irradiance, or above cloud thermal emission, depending upon spectral channel. The observed differences between collections may have implications for existing MODIS derived climatologies and validation studies of effective radius and CDNC.

Comparison of the MODIS Collection 5 Multilayer Cloud Detection Product with CALIPSO

NASA Technical Reports Server (NTRS)

Platnick, Steven; Wind, Gala; King, Michael D.; Holz, Robert E.; Ackerman, Steven A.; Nagle, Fred W.

2010-01-01

CALIPSO, launched in June 2006, provides global active remote sensing measurements of clouds and aerosols that can be used for validation of a variety of passive imager retrievals derived from instruments flying on the Aqua spacecraft and other A-Train platforms. The most recent processing effort for the MODIS Atmosphere Team, referred to as the Collection 5 scream, includes a research-level multilayer cloud detection algorithm that uses both thermodynamic phase information derived from a combination of solar and thermal emission bands to discriminate layers of different phases, as well as true layer separation discrimination using a moderately absorbing water vapor band. The multilayer detection algorithm is designed to provide a means of assessing the applicability of 1D cloud models used in the MODIS cloud optical and microphysical product retrieval, which are generated at a 1 km resolution. Using pixel-level collocations of MODIS Aqua, CALIOP, we investigate the global performance of multilayer cloud detection algorithms (and thermodynamic phase).

Remote Sensing of Cloud, Aerosol, and Land Properties from MODIS: Applications to the East Asia Region

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Chu, D. Allen; Moody, Eric G.

2001-01-01

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns 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 processes. In this presentation we review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of (i) developing a cloud mask for distinguishing clear sky from clouds, (ii) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (iii) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (iv) determining atmospheric profiles of moisture and temperature, and (v) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations to the east Asian region in Spring 2001. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 degree (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented.

Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Menzel, W. Paul; Kaufman, Yoram J.; Ackerman, Steven A.; Tanre, Didier; Gao, Bo-Cai

2001-01-01

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar orbiting, sun-synchronous, platform at an altitude of 705 kilometers, and provides images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resolutions of 250 meters (2 bands), 500 meters (5 bands) and 1000 meters (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation we review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of (i) developing a cloud mask for distinguishing clear sky from clouds, (ii) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (iii) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (iv) determining atmospheric profiles of moisture and temperature, and (v) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 degree (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented.

Estimating the top altitude of optically thick ice clouds from thermal infrared satellite observations using CALIPSO data

NASA Astrophysics Data System (ADS)

Minnis, Patrick; Yost, Chris R.; Sun-Mack, Sunny; Chen, Yan

2008-06-01

The difference between cloud-top altitude Z top and infrared effective radiating height Z eff for optically thick ice clouds is examined using April 2007 data taken by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and the Moderate-Resolution Imaging Spectroradiometer (MODIS). For even days, the difference ΔZ between CALIPSO Z top and MODIS Z eff is 1.58 +/- 1.26 km. The linear fit between Z top and Z eff , applied to odd-day data, yields a difference of 0.03 +/- 1.21 km and can be used to estimate Z top from any infrared-based Z eff for thick ice clouds. Random errors appear to be due primarily to variations in cloud ice-water content (IWC). Radiative transfer calculations show that ΔZ corresponds to an optical depth of ~1, which based on observed ice-particle sizes yields an average cloud-top IWC of ~0.015 gm-3, a value consistent with in situ measurements. The analysis indicates potential for deriving cloud-top IWC using dual-satellite data.

Using MODIS Cloud Regimes to Sort Diagnostic Signals of Aerosol-Cloud-Precipitation Interactions

PubMed Central

Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin

2018-01-01

Coincident multi-year measurements of aerosol, cloud, precipitation and radiation at near-global scales are analyzed to diagnose their apparent relationships as suggestive of interactions previously proposed based on theoretical, observational, and model constructs. Specifically, we examine whether differences in aerosol loading in separate observations go along with consistently different precipitation, cloud properties, and cloud radiative effects. Our analysis uses a cloud regime (CR) framework to dissect and sort the results. The CRs come from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and are defined as distinct groups of cloud systems with similar co-variations of cloud top pressure and cloud optical thickness. Aerosol optical depth used as proxy for aerosol loading comes from two sources, MODIS observations, and the MERRA-2 re-analysis, and its variability is defined with respect to local seasonal climatologies. The choice of aerosol dataset impacts our results substantially. We also find that the responses of the marine and continental component of a CR are frequently quite disparate. Overall, CRs dominated by warm clouds tend to exhibit less ambiguous signals, but also have more uncertainty with regard to precipitation changes. Finally, we find weak, but occasionally systematic co-variations of select meteorological indicators and aerosol, which serves as a sober reminder that ascribing changes in cloud and cloud-affected variables solely to aerosol variations is precarious. PMID:29651373

Using MODIS Cloud Regimes to Sort Diagnostic Signals of Aerosol-Cloud-Precipitation Interactions.

PubMed

Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin

2017-05-27

Coincident multi-year measurements of aerosol, cloud, precipitation and radiation at near-global scales are analyzed to diagnose their apparent relationships as suggestive of interactions previously proposed based on theoretical, observational, and model constructs. Specifically, we examine whether differences in aerosol loading in separate observations go along with consistently different precipitation, cloud properties, and cloud radiative effects. Our analysis uses a cloud regime (CR) framework to dissect and sort the results. The CRs come from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and are defined as distinct groups of cloud systems with similar co-variations of cloud top pressure and cloud optical thickness. Aerosol optical depth used as proxy for aerosol loading comes from two sources, MODIS observations, and the MERRA-2 re-analysis, and its variability is defined with respect to local seasonal climatologies. The choice of aerosol dataset impacts our results substantially. We also find that the responses of the marine and continental component of a CR are frequently quite disparate. Overall, CRs dominated by warm clouds tend to exhibit less ambiguous signals, but also have more uncertainty with regard to precipitation changes. Finally, we find weak, but occasionally systematic co-variations of select meteorological indicators and aerosol, which serves as a sober reminder that ascribing changes in cloud and cloud-affected variables solely to aerosol variations is precarious.

A Study of Uncertainties for MODIS Cloud Retrievals of Optical Thickness and Effective Radius

NASA Technical Reports Server (NTRS)

Platnick, Steven; Pincus, Robert

2002-01-01

The investigation spanned four linked components as summarized in section III, each relating to some aspect of uncertainty assessment in the retrieval of cloud optical and microphysical properties using solar reflectance algorithms such as the MODIS operational cloud product (product IDS MOD06, MDY06 for Terra and Aqua, respectively). As discussed, three of these components have been fully completed (items (l), (2), and (3) while item (4) has been partially completed. These efforts have resulted in peer-reviewed publications and/or information delivered to the MODIS P.I. (M. D. King) for inclusion in the cloud product Quality Assessment (QA) output, a portion of the product output used, in part, for retrieval error assignments. This final report begins with a synopsis of the proposed investigation (section III) followed by a summary of work performed up through the last report including updates (section IV). Section V describes new activities. Publications from the efforts are listed in section VI. Figures (available in powerpoint format) are found in section VII.

Retrievals and Comparisons of Various MODIS-Spectrum Inferred Water Cloud Droplet Effective Radii

NASA Technical Reports Server (NTRS)

Fu-Lung, Chang; Minnis, Patrick; Lin, Bin; Sunny, Sun-Mack; Khaiyer, Mandana M.

2007-01-01

Cloud droplet effective radius retrievals from different Aqua MODIS nearinfrared channels (2.1- micrometer, 3.7- micrometer, and 1.6- micrometer) show considerable differences even among most confident QC pixels. Both Collection 004 and Collection 005 MOD06 show smaller mean effective radii at 3.7- micrometer wavelength than at 2.1- micrometer and 1.6- micrometer wavelengths. Differences in effective radius retrievals between Collection 004 and Collection 005 may be affected by cloud top height/temperature differences, which mainly occur for optically thin clouds. Changes in cloud top height and temperature for thin clouds have different impacts on the effective radius retrievals from 2.1- micrometer, 3.7- micrometer, and 1.6- micrometer channels. Independent retrievals (this study) show, on average, more consistency in the three effective radius retrievals. This study is for Aqua MODIS only.

Assessment of the NPOESS/VIIRS Nighttime Infrared Cloud Optical Properties Algorithms

NASA Astrophysics Data System (ADS)

Wong, E.; Ou, S. C.

2008-12-01

In this paper we will describe two NPOESS VIIRS IR algorithms used to retrieve microphysical properties for water and ice clouds during nighttime conditions. Both algorithms employ four VIIRS IR channels: M12 (3.7 μm), M14 (8.55 μm), M15 (10.7 μm) and M16 (12 μm). The physical basis for the two algorithms is similar in that while the Cloud Top Temperature (CTT) is derived from M14 and M16 for ice clouds the Cloud Optical Thickness (COT) and Cloud Effective Particle Size (CEPS) are derived from M12 and M15. The two algorithms depart in the different radiative transfer parameterization equations used for ice and water clouds. Both the VIIRS nighttime IR algorithms and the CERES split-window method employ the 3.7 μm and 10.7 μm bands for cloud optical properties retrievals, apparently based on similar physical principles but with different implementations. It is reasonable to expect that the VIIRS and CERES IR algorithms produce comparable performance and similar limitations. To demonstrate the VIIRS nighttime IR algorithm performance, we will select a number of test cases using NASA MODIS L1b radiance products as proxy input data for VIIRS. The VIIRS retrieved COT and CEPS will then be compared to cloud products available from the MODIS, NASA CALIPSO, CloudSat and CERES sensors. For the MODIS product, the nighttime cloud emissivity will serve as an indirect comparison to VIIRS COT. For the CALIPSO and CloudSat products, the layered COT will be used for direct comparison. Finally, the CERES products will provide direct comparison with COT as well as CEPS. This study can only provide a qualitative assessment of the VIIRS IR algorithms due to the large uncertainties in these cloud products.

Cirrus Heterogeneity Effects on Cloud Optical Properties Retrieved with an Optimal Estimation Method from MODIS VIS to TIR Channels.

NASA Technical Reports Server (NTRS)

Fauchez, T.; Platnick, S.; Meyer, K.; Sourdeval, O.; Cornet, C.; Zhang, Z.; Szczap, F.

2016-01-01

This study presents preliminary results on the effect of cirrus heterogeneities on top-of-atmosphere (TOA) simulated radiances or reflectances for MODIS channels centered at 0.86, 2.21, 8.56, 11.01 and 12.03 micrometers , and on cloud optical properties retrieved with a research-level optimal estimation method (OEM). Synthetic cirrus cloud fields are generated using a 3D cloud generator (3DCLOUD) and radiances/reflectances are simulated using a 3D radiative transfer code (3DMCPOL). We find significant differences between the heterogeneity effects on either visible and near-infrared (VNIR) or thermal infrared (TIR) radiances. However, when both wavelength ranges are combined, heterogeneity effects are dominated by the VNIR horizontal radiative transport effect. As a result, small optical thicknesses are overestimated and large ones are underestimated. Retrieved effective diameter are found to be slightly affected, contrarily to retrievals using TIR channels only.

Aerosol Direct Radiative Effect at the Top of the Atmosphere Over Cloud Free Ocean Derived from Four Years of MODIS Data

NASA Technical Reports Server (NTRS)

Remer, L. A.; Kaufman, Y. J.

2006-01-01

A four year record of MODIS spaceborne data provides a new measurement tool to assess the aerosol direct radiative effect at the top of the atmosphere. MODIS derives the aerosol optical thickness and microphysical properties from the scattered sunlight at 0.55-2.1 microns. The monthly MODIS data used here are accumulated measurements across a wide range of view and scattering angles and represent the aerosol s spectrally resolved angular properties. We use these data consistently to compute with estimated accuracy of +/-0.6W/sq m the reflected sunlight by the aerosol over global oceans in cloud free conditions. The MODIS high spatial resolution (0.5 km) allows observation of the aerosol impact between clouds that can be missed by other sensors with larger footprints. We found that over the clear-sky global ocean the aerosol reflected 5.3+/-0.6W/sq m with an average radiative efficiency of 49+/-2W/sq m per unit optical thickness. The seasonal and regional distribution of the aerosol radiative effects are discussed. The analysis adds a new measurement perspective to a climate change problem dominated so far by models.

Determination of Ice Cloud Models Using MODIS and MISR Data

NASA Technical Reports Server (NTRS)

Xie, Yu; Yang, Ping; Kattawar, George W.; Minnis, Patrick; Hu, Yongxiang; Wu, Dong L.

2012-01-01

Representation of ice clouds in radiative transfer simulations is subject to uncertainties associated with the shapes and sizes of ice crystals within cirrus clouds. In this study, we examined several ice cloud models consisting of smooth, roughened, homogeneous and inhomogeneous hexagonal ice crystals with various aspect ratios. The sensitivity of the bulk scattering properties and solar reflectances of cirrus clouds to specific ice cloud models is investigated using the improved geometric optics method (IGOM) and the discrete ordinates radiative transfer (DISORT) model. The ice crystal habit fractions in the ice cloud model may significantly affect the simulations of cloud reflectances. A new algorithm was developed to help determine an appropriate ice cloud model for application to the satellite-based retrieval of ice cloud properties. The ice cloud particle size retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) data, collocated with Multi-angle Imaging Spectroradiometer (MISR) observations, is used to infer the optical thicknesses of ice clouds for nine MISR viewing angles. The relative differences between view-dependent cloud optical thickness and the averaged value over the nine MISR viewing angles can vary from -0.5 to 0.5 and are used to evaluate the ice cloud models. In the case for 2 July 2009, the ice cloud model with mixed ice crystal habits is the best fit to the observations (the root mean square (RMS) error of cloud optical thickness reaches 0.365). This ice cloud model also produces consistent cloud property retrievals for the nine MISR viewing configurations within the measurement uncertainties.

Detection of Multi-Layer and Vertically-Extended Clouds Using A-Train Sensors

NASA Technical Reports Server (NTRS)

Joiner, J.; Vasilkov, A. P.; Bhartia, P. K.; Wind, G.; Platnick, S.; Menzel, W. P.

2010-01-01

The detection of mUltiple cloud layers using satellite observations is important for retrieval algorithms as well as climate applications. In this paper, we describe a relatively simple algorithm to detect multiple cloud layers and distinguish them from vertically-extended clouds. The algorithm can be applied to coincident passive sensors that derive both cloud-top pressure from the thermal infrared observations and an estimate of solar photon pathlength from UV, visible, or near-IR measurements. Here, we use data from the A-train afternoon constellation of satellites: cloud-top pressure, cloud optical thickness, the multi-layer flag from the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the optical centroid cloud pressure from the Aura Ozone Monitoring Instrument (OMI). For the first time, we use data from the CloudSat radar to evaluate the results of a multi-layer cloud detection scheme. The cloud classification algorithms applied with different passive sensor configurations compare well with each other as well as with data from CloudSat. We compute monthly mean fractions of pixels containing multi-layer and vertically-extended clouds for January and July 2007 at the OMI spatial resolution (l2kmx24km at nadir) and at the 5kmx5km MODIS resolution used for infrared cloud retrievals. There are seasonal variations in the spatial distribution of the different cloud types. The fraction of cloudy pixels containing distinct multi-layer cloud is a strong function of the pixel size. Globally averaged, these fractions are approximately 20% and 10% for OMI and MODIS, respectively. These fractions may be significantly higher or lower depending upon location. There is a much smaller resolution dependence for fractions of pixels containing vertically-extended clouds (approx.20% for OMI and slightly less for MODIS globally), suggesting larger spatial scales for these clouds. We also find higher fractions of vertically-extended clouds over land as compared with ocean, particularly in the tropics and summer hemisphere.

Detection of ground fog in mountainous areas from MODIS (Collection 051) daytime data using a statistical approach

NASA Astrophysics Data System (ADS)

Schulz, Hans Martin; Thies, Boris; Chang, Shih-Chieh; Bendix, Jörg

2016-03-01

The mountain cloud forest of Taiwan can be delimited from other forest types using a map of the ground fog frequency. In order to create such a frequency map from remotely sensed data, an algorithm able to detect ground fog is necessary. Common techniques for ground fog detection based on weather satellite data cannot be applied to fog occurrences in Taiwan as they rely on several assumptions regarding cloud properties. Therefore a new statistical method for the detection of ground fog in mountainous terrain from MODIS Collection 051 data is presented. Due to the sharpening of input data using MODIS bands 1 and 2, the method provides fog masks in a resolution of 250 m per pixel. The new technique is based on negative correlations between optical thickness and terrain height that can be observed if a cloud that is relatively plane-parallel is truncated by the terrain. A validation of the new technique using camera data has shown that the quality of fog detection is comparable to that of another modern fog detection scheme developed and validated for the temperate zones. The method is particularly applicable to optically thinner water clouds. Beyond a cloud optical thickness of ≈ 40, classification errors significantly increase.

Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.

2001-01-01

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands from 0.415 to 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation I will review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of: (1) developing a cloud mask for distinguishing clear sky from clouds, (2) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (3) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (4) determining atmospheric profiles of moisture and temperature, and (5) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 deg (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented. Finally, I will present some highlights from the land and ocean algorithms developed for processing global MODIS observations, including: (1) surface reflectance, (2) vegetation indices, leaf area index, and FPAR, (3) albedo and nadir BRDF-adjusted reflectance, (4) normalized water-leaving radiance, (5) chlorophyll-a concentration, and (6) sea surface temperature.

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations: 2. Retrieval Evaluation

NASA Technical Reports Server (NTRS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Wind, Galina; Yang, Ping

2016-01-01

An infrared-based optimal estimation (OE-IR) algorithm for retrieving ice cloud properties is evaluated. Specifically, the implementation of the algorithm with MODerate resolution Imaging Spectroradiometer (MODIS) observations is assessed in comparison with the operational retrieval products from MODIS on the Aqua satellite (MYD06), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and the Imaging Infrared Radiometer (IIR); the latter two instruments fly on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite in the Afternoon Constellation (A-Train) with Aqua. The results show that OE-IR cloud optical thickness (tau) and effective radius (r(sub eff)) retrievals perform best for ice clouds having 0.5 < tau< 7 and r(sub eff) < 50microns. For global ice clouds, the averaged retrieval uncertainties of tau and r(sub eff) are 19% and 33%, respectively. For optically thick ice clouds with tau larger than 10, however, the tau and r(sub eff) retrieval uncertainties can exceed 30% and 50%, respectively. For ice cloud top height (h), the averaged global uncertainty is 0.48km. Relatively large h uncertainty (e.g., > 1km) occurs for tau < 0.5. Analysis of 1month of the OE-IR retrievals shows large tau and r(sub eff) uncertainties in storm track regions and the southern oceans where convective clouds are frequently observed, as well as in high-latitude regions where temperature differences between the surface and cloud top are more ambiguous. Generally, comparisons between the OE-IR and the operational products show consistent tau and h retrievals. However, obvious differences between the OE-IR and the MODIS Collection 6 r(sub eff) are found.

Global cloud database from VIRS and MODIS for CERES

NASA Astrophysics Data System (ADS)

Minnis, Patrick; Young, David F.; Wielicki, Bruce A.; Sun-Mack, Sunny; Trepte, Qing Z.; Chen, Yan; Heck, Patrick W.; Dong, Xiquan

2003-04-01

The NASA CERES Project has developed a combined radiation and cloud property dataset using the CERES scanners and matched spectral data from high-resolution imagers, the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. The diurnal cycle can be well-characterized over most of the globe using the combinations of TRMM, Aqua, and Terra data. The cloud properties are derived from the imagers using state-of-the-art methods and include cloud fraction, height, optical depth, phase, effective particle size, emissivity, and ice or liquid water path. These cloud products are convolved into the matching CERES fields of view to provide simultaneous cloud and radiation data at an unprecedented accuracy. Results are available for at least 3 years of VIRS data and 1 year of Terra MODIS data. The various cloud products are compared with similar quantities from climatological sources and instantaneous active remote sensors. The cloud amounts are very similar to those from surface observer climatologies and are 6-7% less than those from a satellite-based climatology. Optical depths are 2-3 times smaller than those from the satellite climatology, but are within 5% of those from the surface remote sensing. Cloud droplet sizes and liquid water paths are within 10% of the surface results on average for stratus clouds. The VIRS and MODIS retrievals are very consistent with differences that usually can be explained by sampling, calibration, or resolution differences. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.

Effect of Thin Cirrus Clouds on Dust Optical Depth Retrievals From MODIS Observations

NASA Technical Reports Server (NTRS)

Feng, Qian; Hsu, N. Christina; Yang, Ping; Tsay, Si-Chee

2011-01-01

The effect of thin cirrus clouds in retrieving the dust optical depth from MODIS observations is investigated by using a simplified aerosol retrieval algorithm based on the principles of the Deep Blue aerosol property retrieval method. Specifically, the errors of the retrieved dust optical depth due to thin cirrus contamination are quantified through the comparison of two retrievals by assuming dust-only atmospheres and the counterparts with overlapping mineral dust and thin cirrus clouds. To account for the effect of the polarization state of radiation field on radiance simulation, a vector radiative transfer model is used to generate the lookup tables. In the forward radiative transfer simulations involved in generating the lookup tables, the Rayleigh scattering by atmospheric gaseous molecules and the reflection of the surface assumed to be Lambertian are fully taken into account. Additionally, the spheroid model is utilized to account for the nonsphericity of dust particles In computing their optical properties. For simplicity, the single-scattering albedo, scattering phase matrix, and optical depth are specified a priori for thin cirrus clouds assumed to consist of droxtal ice crystals. The present results indicate that the errors in the retrieved dust optical depths due to the contamination of thin cirrus clouds depend on the scattering angle, underlying surface reflectance, and dust optical depth. Under heavy dusty conditions, the absolute errors are comparable to the predescribed optical depths of thin cirrus clouds.

Detection and Retrieval of Multi-Layered Cloud Properties Using Satellite Data

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Sun-Mack, Sunny; Chen, Yan; Yi, Helen; Huang, Jian-Ping; Nguyen, Louis; Khaiyer, Mandana M.

2005-01-01

Four techniques for detecting multilayered clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. A new technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other methods examined here use atmospheric sounding data (CO2-slicing, CO2), BTD, or microwave data. The CO2 and BTD methods are limited to optically thin cirrus over low clouds, while the MWR methods are limited to ocean areas only. This paper explores the use of the BTD and CO2 methods as applied to Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer EOS (AMSR-E) data taken from the Aqua satellite over ocean surfaces. Cloud properties derived from MODIS data for the Clouds and the Earth's Radiant Energy System (CERES) Project are used to classify cloud phase and optical properties. The preliminary results focus on a MODIS image taken off the Uruguayan coast. The combined MW visible infrared (MVI) method is assumed to be the reference for detecting multilayered ice-over-water clouds. The BTD and CO2 techniques accurately match the MVI classifications in only 51 and 41% of the cases, respectively. Much additional study is need to determine the uncertainties in the MVI method and to analyze many more overlapped cloud scenes.

Detection and retrieval of multi-layered cloud properties using satellite data

NASA Astrophysics Data System (ADS)

Minnis, Patrick; Sun-Mack, Sunny; Chen, Yan; Yi, Helen; Huang, Jianping; Nguyen, Louis; Khaiyer, Mandana M.

2005-10-01

Four techniques for detecting multilayered clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. A new technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other methods examined here use atmospheric sounding data (CO2-slicing, CO2), BTD, or microwave data. The CO2 and BTD methods are limited to optically thin cirrus over low clouds, while the MWR methods are limited to ocean areas only. This paper explores the use of the BTD and CO2 methods as applied to Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer EOS (AMSR-E) data taken from the Aqua satellite over ocean surfaces. Cloud properties derived from MODIS data for the Clouds and the Earth's Radiant Energy System (CERES) Project are used to classify cloud phase and optical properties. The preliminary results focus on a MODIS image taken off the Uruguayan coast. The combined MW visible infrared (MVI) method is assumed to be the reference for detecting multilayered ice-over-water clouds. The BTD and CO2 techniques accurately match the MVI classifications in only 51 and 41% of the cases, respectively. Much additional study is need to determine the uncertainties in the MVI method and to analyze many more overlapped cloud scenes.

Cirrus Cloud Optical Thickness and Effective Diameter Retrieved by MODIS: Impacts of Single Habit Assumption, 3-D Radiative Effects, and Cloud Inhomogeneity

NASA Astrophysics Data System (ADS)

Zhou, Yongbo; Sun, Xuejin; Mielonen, Tero; Li, Haoran; Zhang, Riwei; Li, Yan; Zhang, Chuanliang

2018-01-01

For inhomogeneous cirrus clouds, cloud optical thickness (COT) and effective diameter (De) provided by the Moderate Resolution Imaging Spectrometer (MODIS) Collection 6 cloud products are associated with errors due to the single habit assumption (SHA), independent pixel assumption (IPA), photon absorption effect (PAE), and plane-parallel assumption (PPA). SHA means that every cirrus cloud is assumed to have the same shape habit of ice crystals. IPA errors are caused by three-dimensional (3D) radiative effects. PPA and PAE errors are caused by cloud inhomogeneity. We proposed a method to single out these different errors. These errors were examined using the Spherical Harmonics Discrete Ordinate Method simulations done for the MODIS 0.86 μm and 2.13 μm bands. Four midlatitude and tropical cirrus cases were studied. For the COT retrieval, the impacts of SHA and IPA were especially large for optically thick cirrus cases. SHA errors in COT varied distinctly with scattering angles. For the De retrieval, SHA decreased De under most circumstances. PAE decreased De for optically thick cirrus cases. For the COT and De retrievals, the dominant error source was SHA for overhead sun whereas for oblique sun, it could be any of SHA, IPA, and PAE, varying with cirrus cases and sun-satellite viewing geometries. On the domain average, the SHA errors in COT (De) were within -16.1%-42.6% (-38.7%-2.0%), whereas the 3-D radiative effects- and cloud inhomogeneity-induced errors in COT (De) were within -5.6%-19.6% (-2.9%-8.0%) and -2.6%-0% (-3.7%-9.8%), respectively.

Cloud Inhomogeneity from MODIS

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Cahalan, Robert F.

2004-01-01

Two full months (July 2003 and January 2004) of MODIS Atmosphere Level-3 data from the Terra and Aqua satellites are analyzed in order to characterize the horizontal variability of cloud optical thickness and water path at global scales. Various options to derive cloud variability parameters are discussed. The climatology of cloud inhomogeneity is built by first calculating daily parameter values at spatial scales of l degree x 1 degree, and then at zonal and global scales, followed by averaging over monthly time scales. Geographical, diurnal, and seasonal changes of inhomogeneity parameters are examined separately for the two cloud phases, and separately over land and ocean. We find that cloud inhomogeneity is weaker in summer than in winter, weaker over land than ocean for liquid clouds, weaker for local morning than local afternoon, about the same for liquid and ice clouds on a global scale, but with wider probability distribution functions (PDFs) and larger latitudinal variations for ice, and relatively insensitive to whether water path or optical thickness products are used. Typical mean values at hemispheric and global scales of the inhomogeneity parameter nu (roughly the mean over the standard deviation of water path or optical thickness), range from approximately 2.5 to 3, while for the inhomogeneity parameter chi (the ratio of the logarithmic to linear mean) from approximately 0.7 to 0.8. Values of chi for zonal averages can occasionally fall below 0.6 and for individual gridpoints below 0.5. Our results demonstrate that MODIS is capable of revealing significant fluctuations in cloud horizontal inhomogenity and stress the need to model their global radiative effect in future studies.

Optical properties of aerosol contaminated cloud derived from MODIS instrument

NASA Astrophysics Data System (ADS)

Mei, Linlu; Rozanov, Vladimir; Lelli, Luca; Vountas, Marco; Burrows, John P.

2016-04-01

The presence of absorbing aerosols above/within cloud can reduce the amount of up-welling radiation in visible (VIS) and short-wave infrared and darken the spectral reflectance when compared with a spectrum of a clean cloud observed by satellite instruments (Jethva et al., 2013). Cloud properties retrieval for aerosol contaminated cases is a great challenge. Even small additional injection of aerosol particles into clouds in the cleanest regions of Earth's atmosphere will cause significant effect on those clouds and on climate forcing (Koren et al., 2014; Rosenfeld et al., 2014) because the micro-physical cloud process are non-linear with respect to the aerosol loading. The current cloud products like Moderate Resolution Imaging Spectroradiometer (MODIS) ignoring the aerosol effect for the retrieval, which may cause significant error in the satellite-derived cloud properties. In this paper, a new cloud properties retrieval method, considering aerosol effect, based on the weighting-function (WF) method, is presented. The retrieval results shows that the WF retrieved cloud properties (e.g COT) agrees quite well with MODIS COT product for relative clear atmosphere (AOT ≤ 0.4) while there is a large difference for large aerosol loading. The MODIS COT product is underestimated for at least 2 - 3 times for AOT>0.4, and this underestimation increases with the increase of AOT.

Reconciling biases and uncertainties of AIRS and MODIS ice cloud properties

NASA Astrophysics Data System (ADS)

Kahn, B. H.; Gettelman, A.

2015-12-01

We will discuss comparisons of collocated Atmospheric Infrared Sounder (AIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) ice cloud optical thickness (COT), effective radius (CER), and cloud thermodynamic phase retrievals. The ice cloud comparisons are stratified by retrieval uncertainty estimates, horizontal inhomogeneity at the pixel-scale, vertical cloud structure, and other key parameters. Although an estimated 27% globally of all AIRS pixels contain ice cloud, only 7% of them are spatially uniform ice according to MODIS. We find that the correlations of COT and CER between the two instruments are strong functions of horizontal cloud heterogeneity and vertical cloud structure. The best correlations are found in single-layer, horizontally homogeneous clouds over the low-latitude tropical oceans with biases and scatter that increase with scene complexity. While the COT comparisons are unbiased in homogeneous ice clouds, a bias of 5-10 microns remains in CER within the most homogeneous scenes identified. This behavior is entirely consistent with known sensitivity differences in the visible and infrared bands. We will use AIRS and MODIS ice cloud properties to evaluate ice hydrometeor output from climate model output, such as the CAM5, with comparisons sorted into different dynamical regimes. The results of the regime-dependent comparisons will be described and implications for model evaluation and future satellite observational needs will be discussed.

Deriving Aerosol Characteristics Over the Ocean from MODIS: Are We There Yet?

NASA Astrophysics Data System (ADS)

Remer, L. A.; Tanre, D.

2006-12-01

The MODerate resolution Imaging Spectroradiometer (MODIS) has been successfully retrieving aerosol characteristics over the ocean since shortly after the launch of the Terra satellite at the end of 1999. With its wide spectral range (0.47 to 2.13 μm) MODIS is able to derive spectral aerosol optical depth and information on the size of the aerosol particles. The products were quickly validated, the validation confirmed, and the products are now in wide use across the scientific community. The MODIS aerosol products over ocean are an outstanding success story, but are we done? As the years progress and we gain experience in using the products, evaluating them and nudging even greater information from them, we discover new challenges. Firstly, we continue to find issues affecting the integrity of the products we now produce. We need to find methods to reduce the uncertainty introduced by clouds that go beyond the classical concept of cloud masking and cloud contamination. Some of these novel cloud effects on aerosol retrieval include 3D scattering of light from cloud sides. Another issue that needs resolution is the uncertainty introduced by nonspherical particle shapes. Secondly, when MODIS was new we were excited to have spectral optical depth and particle size information. Now we find that aerosol characterization is still incomplete. We need more information. Are we there yet? Well, no, but we can see the future. To meet these new challenges we will need information beyond the spectral radiances that MODIS measures. We can see the future of satellite derivation of aerosol characteristics, and it looks more and more like a multi-sensor future.

Determination of ice water path in ice-over-water cloud systems using combined MODIS and AMSR-E measurements

NASA Astrophysics Data System (ADS)

Huang, Jianping; Minnis, Patrick; Lin, Bing; Yi, Yuhong; Fan, T.-F.; Sun-Mack, Sunny; Ayers, J. K.

2006-11-01

To provide more accurate ice cloud microphysical properties, the multi-layered cloud retrieval system (MCRS) is used to retrieve ice water path (IWP) in ice-over-water cloud systems globally over oceans using combined instrument data from Aqua. The liquid water path (LWP) of lower-layer water clouds is estimated from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) measurements. The properties of the upper-level ice clouds are then derived from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements by matching simulated radiances from a two-cloud-layer radiative transfer model. The results show that the MCRS can significantly improve the accuracy and reduce the over-estimation of optical depth and IWP retrievals for ice-over-water cloud systems. The mean daytime ice cloud optical depth and IWP for overlapped ice-over-water clouds over oceans from Aqua are 7.6 and 146.4 gm-2, respectively, down from the initial single-layer retrievals of 17.3 and 322.3 gm-2. The mean IWP for actual single-layer clouds is 128.2 gm-2.

Cloud and Radiation Studies during SAFARI 2000

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, M. D.; Hobbs, P. V.; Osborne, S.; Piketh, S.; Bruintjes, R.; Lau, William K. M. (Technical Monitor)

2001-01-01

Though the emphasis of the Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign was largely on emission sources and transport, the assemblage of aircraft (including the high altitude NASA ER-2 remote sensing platform and the University of Washington CV-580, UK MRF C130, and South African Weather Bureau JRA in situ aircrafts) provided a unique opportunity for cloud studies. Therefore, as part of the SAFARI initiative, investigations were undertaken to assess regional aerosol-cloud interactions and cloud remote sensing algorithms. In particular, the latter part of the experiment concentrated on marine boundary layer stratocumulus clouds off the southwest coast of Africa. Associated with cold water upwelling along the Benguela current, the Namibian stratocumulus regime has received limited attention but appears to be unique for several reasons. During the dry season, outflow of continental fires and industrial pollution over this area can be extreme. From below, upwelling provides a rich nutrient source for phytoplankton (a source of atmospheric sulphur through DMS production as well as from decay processes). The impact of these natural and anthropogenic sources on the microphysical and optical properties of the stratocumulus is unknown. Continental and Indian Ocean cloud systems of opportunity were also studied during the campaign. Aircraft flights were coordinated with NASA Terra Satellite overpasses for synergy with the Moderate Resolution Imaging Spectroradiometer (MODIS) and other Terra instruments. An operational MODIS algorithm for the retrieval of cloud optical and physical properties (including optical thickness, effective particle radius, and water path) has been developed. Pixel-level MODIS retrievals (11 km spatial resolution at nadir) and gridded statistics of clouds in th SAFARI region will be presented. In addition, the MODIS Airborne Simulator flown on the ER-2 provided high spatial resolution retrievals (50 m at nadir). These retrievals will be discussed and compared with in situ observations.

An Examination of the Nature of Global MODIS Cloud Regimes

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Kato, Seiji; Huffman, George J.

2014-01-01

We introduce global cloud regimes (previously also referred to as "weather states") derived from cloud retrievals that use measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Aqua and Terra satellites. The regimes are obtained by applying clustering analysis on joint histograms of retrieved cloud top pressure and cloud optical thickness. By employing a compositing approach on data sets from satellites and other sources, we examine regime structural and thermodynamical characteristics. We establish that the MODIS cloud regimes tend to form in distinct dynamical and thermodynamical environments and have diverse profiles of cloud fraction and water content. When compositing radiative fluxes from the Clouds and the Earth's Radiant Energy System instrument and surface precipitation from the Global Precipitation Climatology Project, we find that regimes with a radiative warming effect on the atmosphere also produce the largest implied latent heat. Taken as a whole, the results of the study corroborate the usefulness of the cloud regime concept, reaffirm the fundamental nature of the regimes as appropriate building blocks for cloud system classification, clarify their association with standard cloud types, and underscore their distinct radiative and hydrological signatures.

Radiative Susceptibility of Cloudy Atmospheres to Droplet Number Perturbations: 2. Global analysis from MODIS

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Platnick, Steven

2008-01-01

Global distributions of albedo susceptibility for areas covered by liquid clouds are presented for 4 months in 2005. The susceptibility estimates are based on expanded definitions presented in a companion paper and include relative cloud droplet number concentration (CDNC) changes, perturbations in cloud droplet asymmetry parameter and single-scattering albedo, atmospheric/surface effects, and incorporation of the full solar spectrum. The cloud properties (optical thickness and effective radius) used as input in the susceptibility calculations come from MODIS Terra and Aqua Collection 5 gridded data. Geographical distributions of susceptibility corresponding to absolute ( absolute cloud susceptibility ) and relative ( relative cloud susceptibility ) CDNC changes are markedly different indicating that the detailed nature of the cloud microphysical perturbation is important for determining the radiative forcing associated with the first indirect aerosol effect. However, both types of susceptibility exhibit common characteristics such as significant reductions when perturbations in single-scattering properties are omitted, significant increases when atmospheric absorption and surface albedo effects are ignored, and the tendency to decrease with latitude, to be higher over ocean than over land, and to be statistically similar between the morning and afternoon MODIS overpasses. The satellite-based susceptibility analysis helps elucidate the role of present-day cloud and land surface properties in indirect aerosol forcing responses. Our realistic yet moderate CDNC perturbations yield forcings on the order of 1-2 W/sq m for cloud optical property distributions and land surface spectral albedos observed by MODIS. Since susceptibilities can potentially be computed from model fields, these results have practical application in assessing the reasonableness of model-generated estimates of the aerosol indirect radiative forcing.

MODIS Cloud Products Derived from Terra and Aqua During CRYSTAL-FACE

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, S.; Riedi, J. C.; Ackerman, S. A.; Menzel, W. P.

2003-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS), developed as part of the Earth Observing System (EOS) and launched on Terra in December 1999 and Aqua in May 2002, is designed to meet the scientific needs for satellite remote sensing of clouds, aerosols, water vapor, and land and ocean surface properties. During the CRYSTAL-FACE experiment, numerous aircraft coordinated both in situ and remote sensing observations with the Terra and Aqua spacecraft. In this paper we will emphasize the optical, microphysical, and physical properties of both liquid water and ice clouds obtained from an analysis of the satellite observations over Florida and the Gulf of Mexico during July 2002. We will present the frequency distribution of liquid water and ice cloud microphysical properties throughout the region, separating the results over land and ocean. Probability distributions of effective radius and cloud optical thickness will also be shown.

Differences in liquid cloud droplet effective radius and number concentration estimates between MODIS Collections 5.1 and 6 over global oceans

PubMed Central

Rausch, John; Meyer, Kerry; Bennartz, Ralf; Platnick, Steven

2017-01-01

Differences in cloud droplet effective radius and cloud droplet number concentration (CDNC) estimates inferred from the Aqua MODIS Collections 5.1 and 6 cloud products (MYD06) are examined for warm clouds over global oceans for the year 2008. Individual pixel level retrievals for both collections are aggregated to 1° × 1° and compared globally and regionally for the three main spectral channel pairs used for MODIS cloud optical property retrievals. Comparisons between both collections are performed for cases in which all three effective radii retrievals are classified by the MODIS Cloud Product as valid. The contribution to the observed differences of several key MYD06 Collection 6 algorithm updates are also explored, with a focus on changes to the surface reflectance model, assumed solar irradiance, above cloud emission, cloud top pressure, and pixel registration. Global results show a neutral to positive (> 50 cm−3) change for C6-derived CDNC relative to C5.1 for the 1.6 µm and 2.1 µm channel retrievals, corresponding to a neutral to −2 µm difference in droplet effective radius. For 3.7 µm retrievals, CDNC results show a negative change in the tropics, with differences transitioning toward positive values with increasing latitude spanning −25 to +50 cm−3 related to a +2.5 to −1 µm transition in effective radius. Cloud optical thickness differences were small relative to effective radius, and found to not significantly impact CDNC estimates. Regionally, the magnitude and behavior of the annual CDNC cycle are compared for each effective radius retrieval. Results from this study indicate significant intercollection differences in aggregated values of effective radius due to changes to the pre-computed retrieval lookup tables for ocean scenes, changes to retrieved cloud top pressure, solar irradiance, or above cloud thermal emission, depending upon spectral channel. The observed differences between collections may have implications for existing MODIS derived climatologies and validation studies of effective radius and CDNC. PMID:29098040

Differences in Liquid Cloud Droplet Effective Radius and Number Concentration Estimates Between MODIS Collections 5.1 and 6 Over Global Oceans

NASA Technical Reports Server (NTRS)

Rausch, John; Meyer, Kerry; Bennartz, Ralf; Platnick, Steven

2017-01-01

Differences in cloud droplet effective radius and cloud droplet number concentration (CDNC) estimates inferred from the Aqua MODIS Collections 5.1 and 6 cloud products (MYD06) are examined for warm clouds over global oceans for the year 2008. Individual pixel level retrievals for both collections are aggregated to 1 degree x 1 degree and compared globally and regionally for the three main spectral channel pairs used for MODIS cloud optical property retrievals. Comparisons between both collections are performed for cases in which all three effective radii retrievals are classified by the MODIS Cloud Product as valid. The contribution to the observed differences of several key MYD06 Collection 6 algorithm updates are also explored, with a focus on changes to the surface reflectance model, assumed solar irradiance, above cloud emission, cloud top pressure, and pixel registration. Global results show a neutral to positive ( greater than 50cm(exp. -3) change for C6-derived CDNC relative to C5.1 for the 1.6 micrometers and 2.1 micrometers channel retrievals, corresponding to a neutral to -2 micrometers difference in droplet effective radius. For 3.7 micrometer retrievals, CDNC results show a negative change in the tropics, with differences transitioning toward positive values with increasing latitude spanning -25 to +50 cm(exp. -3) related to a +2.5 to -1 micrometers transition in effective radius. Cloud optical thickness differences were small relative to effective radius, and found to not significantly impact CDNC estimates. Regionally, the magnitude and behavior of the annual CDNC cycle are compared for each effective radius retrieval. Results from this study indicate significant intercollection differences in aggregated values of effective radius due to changes to the pre-computed retrieval lookup tables for ocean scenes, changes to retrieved cloud top pressure, solar irradiance, or above cloud thermal emission, depending upon spectral channel. The observed differences between collections may have implications for existing MODIS derived climatologies and validation studies of effective radius and CDNC.

Lidar Ratios for Dust Aerosols Derived From Retrievals of CALIPSO Visible Extinction Profiles Constrained by Optical Depths from MODIS-Aqua and CALIPSO/CloudSat Ocean Surface Reflectance Measurements

NASA Technical Reports Server (NTRS)

Young, Stuart A.; Josset, Damien B.; Vaughan, Mark A.

2010-01-01

CALIPSO's (Cloud Aerosol Lidar Infrared Pathfinder Satellite Observations) analysis algorithms generally require the use of tabulated values of the lidar ratio in order to retrieve aerosol extinction and optical depth from measured profiles of attenuated backscatter. However, for any given time or location, the lidar ratio for a given aerosol type can differ from the tabulated value. To gain some insight as to the extent of the variability, we here calculate the lidar ratio for dust aerosols using aerosol optical depth constraints from two sources. Daytime measurements are constrained using Level 2, Collection 5, 550-nm aerosol optical depth measurements made over the ocean by the MODIS (Moderate Resolution Imaging Spectroradiometer) on board the Aqua satellite, which flies in formation with CALIPSO. We also retrieve lidar ratios from night-time profiles constrained by aerosol column optical depths obtained by analysis of CALIPSO and CloudSat backscatter signals from the ocean surface.

Evaluation of Multilayer Cloud Detection Using a MODIS CO2-Slicing Algorithm With CALIPSO-CloudSat Measurements

NASA Technical Reports Server (NTRS)

Viudez-Mora, Antonio; Kato, Seiji

2015-01-01

This work evaluates the multilayer cloud (MCF) algorithm based on CO2-slicing techniques against CALISPO-CloudSat (CLCS) measurement. This evaluation showed that the MCF underestimates the presence of multilayered clouds compared with CLCS and are retrained to cloud emissivities below 0.8 and cloud optical septs no larger than 0.3.

Possible influences of Asian dust aerosols on cloud properties and radiative forcing observed from MODIS and CERES

NASA Astrophysics Data System (ADS)

Huang, Jianping; Minnis, Patrick; Lin, Bing; Wang, Tianhe; Yi, Yuhong; Hu, Yongxiang; Sun-Mack, Sunny; Ayers, Kirk

2006-03-01

The effects of dust storms on cloud properties and Radiative Forcing (RF) are analyzed over Northwestern China from April 2001 to June 2004 using data collected by the MODerate Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth's Radiant Energy System (CERES) instruments on the Aqua and Terra satellites. On average, ice cloud effective particle diameter, optical depth and ice water path of cirrus clouds under dust polluted conditions are 11%, 32.8%, and 42% less, respectively, than those derived from ice clouds in dust-free atmospheric environments. Due to changes in cloud microphysics, the instantaneous net RF is increased from -161.6 W/m2 for dust-free clouds to -118.6 W/m2 for dust-contaminated clouds.

Effects of clouds on the surface shortwave radiation at a rural inland mid-latitude site

NASA Astrophysics Data System (ADS)

Salgueiro, Vanda; Costa, Maria João; Silva, Ana Maria; Bortoli, Daniele

2016-09-01

Seven years (2003-2010) of measured shortwave (SW) irradiances were used to obtain estimates of the 10 min averaged effective cloud optical thickness (ECOT) and of the shortwave cloud radiative effect (CRESW) at the surface in a mid-latitude site (Évora - south of Portugal), and its seasonal variability is presented. The ECOT, obtained using transmittance measurements at 415 nm, was compared with the correspondent MODIS cloud optical thickness (MODIS COT) for non-precipitating water clouds and cloud fractions higher than 0.25. This comparison showed that the ECOT represents well the cloud optical thickness over the study area. The CRESW, determined for two SW broadband ranges (300-1100 nm; 285-2800 nm), was normalized (NCRESW) and related with the obtained ECOT. A logarithmic relation between NCRESW and ECOT was found for both SW ranges, presenting lower dispersion for overcast-sky situations than for partially cloudy-sky situations. The NCRESW efficiency (NCRESW per unit of ECOT) was also related with the ECOT for overcast-sky conditions. The relation found is parameterized by a power law function showing that NCRESW efficiency decreases as the ECOT increases, approaching one for ECOT values higher than about 50.

Improving Scene Classifications with Combined Active/Passive Measurements

NASA Astrophysics Data System (ADS)

Hu, Y.; Rodier, S.; Vaughan, M.; McGill, M.

The uncertainties in cloud and aerosol physical properties derived from passive instruments such as MODIS are not insignificant And the uncertainty increases when the optical depths decrease Lidar observations do much better for the thin clouds and aerosols Unfortunately space-based lidar measurements such as the one onboard CALIPSO satellites are limited to nadir view only and thus have limited spatial coverage To produce climatologically meaningful thin cloud and aerosol data products it is necessary to combine the spatial coverage of MODIS with the highly sensitive CALIPSO lidar measurements Can we improving the quality of cloud and aerosol remote sensing data products by extending the knowledge about thin clouds and aerosols learned from CALIPSO-type of lidar measurements to a larger portion of the off-nadir MODIS-like multi-spectral pixels To answer the question we studied the collocated Cloud Physics Lidar CPL with Modis-Airborne-Simulation MAS observations and established an effective data fusion technique that will be applied in the combined CALIPSO MODIS cloud aerosol product algorithms This technique performs k-mean and Kohonen self-organized map cluster analysis on the entire swath of MAS data as well as on the combined CPL MAS data at the nadir track Interestingly the clusters generated from the two approaches are almost identical It indicates that the MAS multi-spectral data may have already captured most of the cloud and aerosol scene types such as cloud ice water phase multi-layer information aerosols

Radiative Susceptibility of Cloudy Atmospheres to Droplet Number Perturbations: 1. Theoretical Analysis and Examples from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; Oreopoulos, Lazaros

2008-01-01

Theoretical and satellite-based assessments of the sensitivity of broadband shortwave radiative fluxes in cloudy atmospheres to small perturbations in the cloud droplet number concentration (N) of liquid water clouds under constant water conditions are performed. Two approaches to study this sensitivity are adopted: absolute increases in N, for which the radiative response is referred to as absolute cloud susceptibility, and relative increases in N or relative cloud susceptibility. Estimating the former is more challenging as it requires an assumed value for either cloud liquid water content or geometrical thickness; both susceptibilities require an assumed relationship between the droplet volume and effective radius. Expanding upon previous susceptibility studies, present radiative calculations include the effect of AN perturbations on droplet asymmetry parameter and single-scattering albedo, in addition to extinction. Absolute cloud susceptibility has a strong nonlinear dependence on the droplet effective radius as expected, while relative cloud susceptibility is primarily dependent on optical thickness. Molecular absorption and reflecting surfaces both reduce the relative contribution of the cloud to the top-of-atmosphere (TOA) flux and therefore also reduce the TOA albedo susceptibility. Transmittance susceptibilities are negative with absolute values similar to albedo susceptibility, while atmospheric absorptance susceptibilities are about an order of magnitude smaller than albedo susceptibilities and can be either positive or negative. Observation-based susceptibility calculations are derived from MODIS pixel-level retrievals of liquid water cloud optical thickness, effective radius, and cloud top temperature; two data granule examples are shown. Susceptibility quantifies the aerosol indirect effect sensitivity in a way that can be easily computed from model fields. As such, susceptibilities derived from MODIS observations provide a higher-order test of model cloud properties used for indirect effect studies. MODIS-derived global distributions of cloud susceptibility and radiative forcing calculations are presented in a companion paper.

MODIS Cloud Microphysics Product (MOD_PR06OD) Data Collection 6 Updates

NASA Technical Reports Server (NTRS)

Wind, Gala; Platnick, Steven; King, Michael D.

2014-01-01

The MODIS Cloud Optical and Microphysical Product (MOD_PR060D) for Data Collection 6 has entered full scale production. Aqua reprocessing is almost completed and Terra reprocessing will begin shortly. Unlike previous collections, the CHIMAERA code base allows for simultaneous processing for multiple sensors and the operational CHIMAERA 6.0.76 stream is also available for VIIRS and SEVIRI sensors and for our E-MAS airborne platform.

Aerosol-cloud interaction determined by satellite data over the Baltic Sea countries

NASA Astrophysics Data System (ADS)

Saponaro, Giulia; Kolmonen, Pekka; Sogacheva, Larisa; de Leeuw, Gerrit

2015-04-01

The present study investigates the use of long-term satellite data to assess the influence of aerosols upon cloud parameters over the Baltic Sea region. This particular area offers the contrast of a very clean environment (Fennoscandia) against a more polluted one (Germany, Poland). The datasets consists of Collection 6 Level 3 daily observations from 2002 to 2014 collected by the NASA's Moderate-Resolution Imaging Spectrometer (MODIS) instrument on-board the Aqua platform. The MODIS aerosol optical depth (AOD) product is used as a proxy for the number concentration of aerosol particles while the cloud effective radius (CER) and cloud optical thickness (COT) describe cloud microphysical and optical properties respectively. Satellite data have certain limitations, such as the restriction to summer season due to solar zenith angle restrictions and the known problem of the ambiguity of the aerosol-cloud interface, for instance. Through the analysis of a 12-years dataset, distribution maps provide information on a regional scale about the first aerosol indirect effect (AIE) by determining the aerosol-cloud interaction (ACI). The ACI is defined as the change in cloud optical depth or effective radius as a function of aerosol load for a fixed liquid water path (LWP). The focusing point of the current study is the evaluation of regional trends of ACI over the observed area of the Baltic Sea.

Variability of Aerosol and its Impact on Cloud Properties Over Different Cities of Pakistan

NASA Astrophysics Data System (ADS)

Alam, Khan

Interaction between aerosols and clouds is the subject of considerable scientific research, due to the importance of clouds in controlling climate. Aerosols vary in time in space and can lead to variations in cloud microphysics. This paper is a pilot study to examine the temporal and spatial variation of aerosol particles and their impact on different cloud optical properties in the territory of Pakistan using the Moderate resolution Imaging Spectroradiometer (MODIS) on board NASA's Terra satellite data and Multi-angle Imaging Spectroradiometer (MISR) data. We also use Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model for trajectory analysis to obtain origin of air masses in order to understand the spatial and temporal variability of aerosol concentrations. We validate data of MODIS and MISR by using linear correlation and regression analysis, which shows that there is an excellent agreement between data of these instruments. Seasonal study of Aerosol Optical Depth (AOD) shows that maximum value is found in monsoon season (June-August) over all study areas. We analyze the relationships between aerosol optical depth (AOD) and some cloud parameters like water vapor (WV), cloud fraction (CF), cloud top temperature (CTT) and cloud top pressure (CTP). We construct the regional correlation maps and time series plots for aerosol and cloud parameters mandatory for the better understanding of aerosol-cloud interaction. Our analyses show that there is a strong positive correlation between AOD and water vapor in all cities. The correlation between AOD and CF is positive for the cities where the air masses are moist while the correlation is negative for cities where air masses are relatively dry and with lower aerosol abundance. It shows that these correlations depend on meteorological conditions. Similarly as AOD increases Cloud Top Pressure (CTP) is decreasing while Cloud Top Temperature (CTT) is increasing. Key Words: MODIS, MISR, HYSPLIT, AOD, CF, CTP, CTT

Remote Sensing of Liquid Water and Ice Cloud Optical Thickness and Effective Radius in the Arctic: Application of Airborne Multispectral MAS Data

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Yang, Ping; Arnold, G. Thomas; Gray, Mark A.; Riedi, Jerome C.; Ackerman, Steven A.; Liou, Kuo-Nan

2003-01-01

A multispectral scanning spectrometer was used to obtain measurements of the reflection function and brightness temperature of clouds, sea ice, snow, and tundra surfaces at 50 discrete wavelengths between 0.47 and 14.0 microns. These observations were obtained from the NASA ER-2 aircraft as part of the FIRE Arctic Clouds Experiment, conducted over a 1600 x 500 km region of the north slope of Alaska and surrounding Beaufort and Chukchi Seas between 18 May and 6 June 1998. Multispectral images of the reflection function and brightness temperature in 11 distinct bands of the MODIS Airborne Simulator (MAS) were used to derive a confidence in clear sky (or alternatively the probability of cloud), shadow, and heavy aerosol over five different 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 (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 Beaufort Sea. The cloud optical thickness and effective radius retrievals used 3 distinct bands of the MAS, with the newly developed 1.62 and 2.13 micron bands 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 micron.

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Meyer, Kerry G.; Platnick, Steven; Oreopoulos, Lazaros; Lee, Dongmin; Yu, Hongbin

2014-01-01

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It addresses the overlap of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure while also accounting for subgrid-scale variations of aerosols. The method is computationally efficient because of its use of grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table based on radiative transfer calculations. We verify that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous (approximately 1:30PM local time) shortwave DRE of above cloud aerosol (ACA) that generally agrees with more rigorous pixel-level computation within 4 percent. We also estimate the impact of potential CALIOP aerosol optical depth (AOD) retrieval bias of ACA on DRE. We find that the regional and seasonal mean instantaneous DRE of ACA over southeast Atlantic Ocean would increase, from the original value of 6.4 W m(-2) based on operational CALIOP AOD to 9.6 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 1.5 (Meyer et al., 2013) and further to 30.9 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 5 as suggested in (Jethva et al., 2014). In contrast, the instantaneous ACA radiative forcing efficiency (RFE) remains relatively invariant in all cases at about 53 W m(-2) AOD(-1), suggesting a near linear relation between the instantaneous RFE and AOD. We also compute the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global oceans based on 4 years of CALIOP and MODIS data. We find that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds. While we demonstrate our method using CALIOP and MODIS data, it can also be extended to other satellite data sets, as well as climate model outputs.

Multilayered Clouds Identification and Retrieval for CERES Using MODIS

NASA Technical Reports Server (NTRS)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Yi, Yuhong; Huang, Jainping; Lin, Bin; Fan, Alice; Gibson, Sharon; Chang, Fu-Lung

2006-01-01

Traditionally, analyses of satellite data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from satellite microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on Aqua, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to MODIS and AMSR-E data taken from the Aqua satellite over non-polar ocean surfaces.

Comparison of Monthly Mean Cloud Fraction and Cloud Optical depth Determined from Surface Cloud Radar, TOVS, AVHRR, and MODIS over Barrow, Alaska

NASA Technical Reports Server (NTRS)

Uttal, Taneil; Frisch, Shelby; Wang, Xuan-Ji; Key, Jeff; Schweiger, Axel; Sun-Mack, Sunny; Minnis, Patrick

2005-01-01

A one year comparison is made of mean monthly values of cloud fraction and cloud optical depth over Barrow, Alaska (71 deg 19.378 min North, 156 deg 36.934 min West) between 35 GHz radar-based retrievals, the TOVS Pathfinder Path-P product, the AVHRR APP-X product, and a MODIS based cloud retrieval product from the CERES-Team. The data sets represent largely disparate spatial and temporal scales, however, in this paper, the focus is to provide a preliminary analysis of how the mean monthly values derived from these different data sets compare, and determine how they can best be used separately, and in combination to provide reliable estimates of long-term trends of changing cloud properties. The radar and satellite data sets described here incorporate Arctic specific modifications that account for cloud detection challenges specific to the Arctic environment. The year 2000 was chosen for this initial comparison because the cloud radar data was particularly continuous and reliable that year, and all of the satellite retrievals of interest were also available for the year 2000. Cloud fraction was chosen as a comparison variable as accurate detection of cloud is the primary product that is necessary for any other cloud property retrievals. Cloud optical depth was additionally selected as it is likely the single cloud property that is most closely correlated to cloud influences on surface radiation budgets.

Multisensor Analysis of Ice Crystals Backscatter Peak From 5 Years of Collocated POLDER, MODIS and CALIOP Observations.

NASA Astrophysics Data System (ADS)

Riedi, J.; Labonnote, L. C.; Contaut, F.; Platnick, S. E.; Yang, P.

2016-12-01

Realistic assumptions for representation of ice crystal optical properties are key in deriving meaningful information on ice clouds from spaceborne observations. With the increasing number of multi-sensor analysis it is also of paramount importance that ice crystal models be consistents for the interpretation of both passive and active observations in the solar and thermal infrared spectral domains. There has been significant evidences in the past few years that roughened particles might represent an overall good proxy for ice crystal models being able to simultaneously explain visible and infrared observations obtained from either active or passive sensors (Holz et al, 2016). Nevertheless, details of the exact phase function remain very informative fingerprints of ice crystal shapes and can also be critical parameters for retrievals performed under specific viewing geometries. Analysis of lidar observation for instance remains very sensitive to details of phase function in and around the backscatter direction. The relative magnitude and width of the backscatter peak intensity that appears in phase functions of ice crystal has been shown to carry useful information for characterization of ice crystal habits (Zhou & Yang, 2015). Based on these theoretical results we are revisiting here our previous analysis of coincident POLDER, MODIS and CALIOP observations whereby we were able to study the angular variability of ice clouds reflectance in and around the exact backscatter direction. Statistics from 5 years of observations of peak intensities derived from POLDER have been established in relation to coincident MODIS cloud optical thickness and effective radius retrievals as well as CALIOP layer integrated depolarization ratio and attenuated backscatter. Those are analyzed in view of the theoretical results from Zhou & Yang (2015). In particular, correlation of peak intensity and width with particle size retrieved from MODIS will be presented and implications for ice cloud microphysical properties and remote sensing applications will be discussed. Chen Zhou and Ping Yang : Backscattering peak of ice cloud particles, Opt. Express 23, 11995-12003 (2015) Holz, R. E. et al : Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals, Atmos. Chem. Phys., 16, 5075-5090 (2016)

Estimating nocturnal opaque ice cloud optical depth from MODIS multispectral infrared radiances using a neural network method

NASA Astrophysics Data System (ADS)

Minnis, Patrick; Hong, Gang; Sun-Mack, Szedung; Smith, William L.; Chen, Yan; Miller, Steven D.

2016-05-01

Retrieval of ice cloud properties using IR measurements has a distinct advantage over the visible and near-IR techniques by providing consistent monitoring regardless of solar illumination conditions. Historically, the IR bands at 3.7, 6.7, 11.0, and 12.0 µm have been used to infer ice cloud parameters by various methods, but the reliable retrieval of ice cloud optical depth τ is limited to nonopaque cirrus with τ < 8. The Ice Cloud Optical Depth from Infrared using a Neural network (ICODIN) method is developed in this paper by training Moderate Resolution Imaging Spectroradiometer (MODIS) radiances at 3.7, 6.7, 11.0, and 12.0 µm against CloudSat-estimated τ during the nighttime using 2 months of matched global data from 2007. An independent data set comprising observations from the same 2 months of 2008 was used to validate the ICODIN. One 4-channel and three 3-channel versions of the ICODIN were tested. The training and validation results show that IR channels can be used to estimate ice cloud τ up to 150 with correlations above 78% and 69% for all clouds and only opaque ice clouds, respectively. However, τ for the deepest clouds is still underestimated in many instances. The corresponding RMS differences relative to CloudSat are ~100 and ~72%. If the opaque clouds are properly identified with the IR methods, the RMS differences in the retrieved optical depths are ~62%. The 3.7 µm channel appears to be most sensitive to optical depth changes but is constrained by poor precision at low temperatures. A method for estimating total optical depth is explored for estimation of cloud water path in the future. Factors affecting the uncertainties and potential improvements are discussed. With improved techniques for discriminating between opaque and semitransparent ice clouds, the method can ultimately improve cloud property monitoring over the entire diurnal cycle.

MODIS Microphysical Regimes for Examining Apparent Aerosol Effects on Clouds and Precipitation

NASA Astrophysics Data System (ADS)

Oreopoulos, L.; Cho, N.; Lee, D.; Kato, S.; Lebsock, M. D.; Yuan, T.; Huffman, G. J.

2014-12-01

We use a 10-year record of MODIS Terra and Aqua Level-3 joint histograms of cloud optical thickness (COT) and cloud effective radius (CER) to derive so-called cloud microphysical regimes by means of clustering analysis. The regimes reveal the dominant modes of COT and CER co-variations around the globe for both liquid and ice phases. The clustering analysis is capable of separating regimes so that each is dominated by one of the two water phases and can be associated with previously derived "dynamical" regimes. The microphysical regimes serve as an appropriate basis to study possible effects of aerosols on cloud microphysical changes and precipitation. To this end, we employ MODIS aerosol loading measurements either in terms of aerosol index or aerosol optical depth and spatiotemporally matched precipitation (from either GPCP, TRMM or CloudSat) to examine intra-regime variability, regime transitions from morning (Terra) to afternoon (Aqua), and regime precipitation characteristics for locally low, average, and high aerosol loadings. Breakdowns by ocean/land and geographical zone (e.g., tropics vs. midlatitudes) are essential for physical interpretation of the results. The analysis conducted so far reveals notable differences in apparent characteristics of low- and high-cloud dominated microphysical regimes when in different aerosol environments. The presentation will attempt to examine whether the picture painted by our work is consistent with prevailing expectations, rooted to either modeling or prior observational studies, on how clouds and precipitation respond to distinct aerosol environments.

Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud_cci project

NASA Astrophysics Data System (ADS)

Stengel, Martin; Stapelberg, Stefan; Sus, Oliver; Schlundt, Cornelia; Poulsen, Caroline; Thomas, Gareth; Christensen, Matthew; Carbajal Henken, Cintia; Preusker, Rene; Fischer, Jürgen; Devasthale, Abhay; Willén, Ulrika; Karlsson, Karl-Göran; McGarragh, Gregory R.; Proud, Simon; Povey, Adam C.; Grainger, Roy G.; Fokke Meirink, Jan; Feofilov, Artem; Bennartz, Ralf; Bojanowski, Jedrzej S.; Hollmann, Rainer

2017-11-01

New cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS are presented. Two retrieval systems were developed that include components for cloud detection and cloud typing followed by cloud property retrievals based on the optimal estimation (OE) technique. The OE-based retrievals are applied to simultaneously retrieve cloud-top pressure, cloud particle effective radius and cloud optical thickness using measurements at visible, near-infrared and thermal infrared wavelengths, which ensures spectral consistency. The retrieved cloud properties are further processed to derive cloud-top height, cloud-top temperature, cloud liquid water path, cloud ice water path and spectral cloud albedo. The Cloud_cci products are pixel-based retrievals, daily composites of those on a global equal-angle latitude-longitude grid, and monthly cloud properties such as averages, standard deviations and histograms, also on a global grid. All products include rigorous propagation of the retrieval and sampling uncertainties. Grouping the orbital properties of the sensor families, six datasets have been defined, which are named AVHRR-AM, AVHRR-PM, MODIS-Terra, MODIS-Aqua, ATSR2-AATSR and MERIS+AATSR, each comprising a specific subset of all available sensors. The individual characteristics of the datasets are presented together with a summary of the retrieval systems and measurement records on which the dataset generation were based. Example validation results are given, based on comparisons to well-established reference observations, which demonstrate the good quality of the data. In particular the ensured spectral consistency and the rigorous uncertainty propagation through all processing levels can be considered as new features of the Cloud_cci datasets compared to existing datasets. In addition, the consistency among the individual datasets allows for a potential combination of them as well as facilitates studies on the impact of temporal sampling and spatial resolution on cloud climatologies.

For each dataset a digital object identifier has been issued:

Cloud_cci AVHRR-AM: https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-AM/V002

Cloud_cci AVHRR-PM: https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-PM/V002

Cloud_cci MODIS-Terra: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MODIS-Terra/V002

Cloud_cci MODIS-Aqua: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MODIS-Aqua/V002

Cloud_cci ATSR2-AATSR: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V002

Cloud_cci MERIS+AATSR: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MERIS+AATSR/V002

Extending MODIS Cloud Top and Infrared Phase Climate Records with VIIRS and CrIS

NASA Astrophysics Data System (ADS)

Heidinger, A. K.; Platnick, S. E.; Ackerman, S. A.; Holz, R.; Meyer, K.; Frey, R.; Wind, G.; Li, Y.; Botambekov, D.

2015-12-01

The MODIS imagers on the NASA EOS Terra and Aqua satellites have generated accurate and well-used cloud climate data records for 15 years. Both missions are expected to continue until the end of this decade and perhaps beyond. The Visible and Infrared Imaging Radiometer Suite (VIIRS) imagers on the Suomi-NPP (SNPP) mission (launched in October 2011) and future NOAA Joint Polar Satellite System (JPSS) platforms are the successors for imager-based cloud climate records from polar orbiting satellites after MODIS. To ensure product continuity across a broad suite of EOS products, NASA has funded a SNPP science team to develop EOS-like algorithms that can be use with SNPP and JPSS observations, including two teams to work on cloud products. Cloud data record continuity between MODIS and VIIRS is particularly challenging due to the lack of VIIRS CO2-slicing channels, which reduces information content for cloud detection and cloud-top property products, as well as down-stream cloud optical products that rely on both. Here we report on our approach to providing continuity specifically for the MODIS/VIIRS cloud-top and infrared-derived thermodynamic phase products by combining elements of the NASA MODIS science team (MOD) and the NOAA Algorithm Working Group (AWG) algorithms. The combined approach is referred to as the MODAWG processing package. In collaboration with the NASA Atmospheric SIPS located at the University of Wisconsin Space Science and Engineering Center, the MODAWG code has been exercised on one year of SNPP VIIRS data. In addition to cloud-top and phase, MODAWG provides a full suite of cloud products that are physically consistent with MODIS and have a similar data format. Further, the SIPS has developed tools to allow use of Cross-track Infrared Sounder (CrIS) observations in the MODAWG processing that can ameliorate the loss of the CO2 absorption channels on VIIRS. Examples will be given that demonstrate the positive impact that the CrIS data can provide when combined with VIIRS for cloud height and IR-phase retrievals.

Uncertainties in Cloud Phase and Optical Thickness Retrievals from the Earth Polychromatic Imaging Camera (EPIC)

NASA Technical Reports Server (NTRS)

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2016-01-01

This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud-temperature-threshold-based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (less than 2 percent) due to the particle- size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10 percent, although for thin clouds (COT less than 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC)

PubMed Central

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2018-01-01

This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud temperature threshold based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (< 2%) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10%, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study. PMID:29619116

Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC).

PubMed

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2016-01-01

This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud temperature threshold based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (< 2%) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10%, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC)

NASA Astrophysics Data System (ADS)

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2016-04-01

This paper presents an investigation of the expected uncertainties of a single-channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud-temperature-threshold-based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC Sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single-channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single-channel COT retrieval is feasible for EPIC. For ice clouds, single-channel retrieval errors are minimal (< 2 %) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10 %, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

Passive and Active Detection of Clouds: Comparisons between MODIS and GLAS Observations

NASA Technical Reports Server (NTRS)

Mahesh, Ashwin; Gray, Mark A.; Palm, Stephen P.; Hart, William D.; Spinhirne, James D.

2003-01-01

The Geoscience Laser Altimeter System (GLAS), launched on board the Ice, Cloud and Land Elevation Satellite in January 2003 provides space-borne laser observations of atmospheric layers. GLAS provides opportunities to validate passive observations of the atmosphere for the first time from space with an active optical instrument. Data from the Moderate Resolution Imaging Spectrometer aboard the Aqua satellite is examined along with GLAS observations of cloud layers. In more than three-quarters of the cases, MODIS scene identification from spectral radiances agrees with GLAS. Disagreement between the two platforms is most significant over snow-covered surfaces in the northern hemisphere. Daytime clouds detected by GLAS are also more easily seen in the MODIS data as well, compared to observations made at night. These comparisons illustrate the capabilities of active remote sensing to validate and assess passive measurements, and also to complement them in studies of atmospheric layers.

Assessment of the Accuracy of the Conventional Ray-Tracing Technique: Implications in Remote Sensing and Radiative Transfer Involving Ice Clouds.

NASA Technical Reports Server (NTRS)

Bi, Lei; Yang, Ping; Liu, Chao; Yi, Bingqi; Baum, Bryan A.; Van Diedenhoven, Bastiaan; Iwabuchi, Hironobu

2014-01-01

A fundamental problem in remote sensing and radiative transfer simulations involving ice clouds is the ability to compute accurate optical properties for individual ice particles. While relatively simple and intuitively appealing, the conventional geometric-optics method (CGOM) is used frequently for the solution of light scattering by ice crystals. Due to the approximations in the ray-tracing technique, the CGOM accuracy is not well quantified. The result is that the uncertainties are introduced that can impact many applications. Improvements in the Invariant Imbedding T-matrix method (II-TM) and the Improved Geometric-Optics Method (IGOM) provide a mechanism to assess the aforementioned uncertainties. The results computed by the II-TMþIGOM are considered as a benchmark because the IITM solves Maxwell's equations from first principles and is applicable to particle size parameters ranging into the domain at which the IGOM has reasonable accuracy. To assess the uncertainties with the CGOM in remote sensing and radiative transfer simulations, two independent optical property datasets of hexagonal columns are developed for sensitivity studies by using the CGOM and the II-TMþIGOM, respectively. Ice cloud bulk optical properties obtained from the two datasets are compared and subsequently applied to retrieve the optical thickness and effective diameter from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. Additionally, the bulk optical properties are tested in broadband radiative transfer (RT) simulations using the general circulation model (GCM) version of the Rapid Radiative Transfer Model (RRTMG) that is adopted in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM, version 5.1). For MODIS retrievals, the mean bias of uncertainties of applying the CGOM in shortwave bands (0.86 and 2.13 micrometers) can be up to 5% in the optical thickness and as high as 20% in the effective diameter, depending on cloud optical thickness and effective diameter. In the MODIS infrared window bands centered at 8.5, 11, and 12 micrometers biases in the optical thickness and effective diameter are up to 12% and 10%, respectively. The CGOM-based simulation errors in ice cloud radiative forcing calculations are on the order of 10Wm(exp 2).

Information content of visible and midinfrared radiances for retrieving tropical ice cloud properties

NASA Astrophysics Data System (ADS)

Chang, Kai-Wei; L'Ecuyer, Tristan S.; Kahn, Brian H.; Natraj, Vijay

2017-05-01

Hyperspectral instruments such as Atmospheric Infrared Sounder (AIRS) have spectrally dense observations effective for ice cloud retrievals. However, due to the large number of channels, only a small subset is typically used. It is crucial that this subset of channels be chosen to contain the maximum possible information about the retrieved variables. This study describes an information content analysis designed to select optimal channels for ice cloud retrievals. To account for variations in ice cloud properties, we perform channel selection over an ensemble of cloud regimes, extracted with a clustering algorithm, from a multiyear database at a tropical Atmospheric Radiation Measurement site. Multiple satellite viewing angles over land and ocean surfaces are considered to simulate the variations in observation scenarios. The results suggest that AIRS channels near wavelengths of 14, 10.4, 4.2, and 3.8 μm contain the most information. With an eye toward developing a joint AIRS-MODIS (Moderate Resolution Imaging Spectroradiometer) retrieval, the analysis is also applied to combined measurements from both instruments. While application of this method to MODIS yields results consistent with previous channel sensitivity studies, the analysis shows that this combination may yield substantial improvement in cloud retrievals. MODIS provides most information on optical thickness and particle size, aided by a better constraint on cloud vertical placement from AIRS. An alternate scenario where cloud top boundaries are supplied by the active sensors in the A-train is also explored. The more robust cloud placement afforded by active sensors shifts the optimal channels toward the window region and shortwave infrared, further constraining optical thickness and particle size.

On the response of MODIS cloud coverage to global mean surface air temperature

NASA Astrophysics Data System (ADS)

Yue, Qing; Kahn, Brian H.; Fetzer, Eric J.; Wong, Sun; Frey, Richard; Meyer, Kerry G.

2017-01-01

The global surface temperature change (ΔTs) mediated cloud cover response is directly related to cloud-climate feedback. Using satellite remote sensing data to relate cloud and climate requires a well-calibrated, stable, and consistent long-term cloud data record. The Collection 5.1 (C5) Moderate Resolution Imaging Spectroradiometer (MODIS) cloud observations have been widely used for this purpose. However, the MODIS data quality varies greatly with the surface type, spectral region, cloud type, and time periods of study, which calls for additional caution when applying such data to studies on cloud cover temporal trends and variability. Using 15 years of cloud observations made by Terra and Aqua MODIS, we analyze the ΔTs-mediated cloud cover response for different cloud types by linearly regressing the monthly anomaly of cloud cover (ΔC) with the monthly anomaly of global Ts. The Collection 6 (C6) Aqua data exhibit a similar cloud response to the long-term counterpart simulated by advanced climate models. A robust increase in altitude with increasing ΔTs is found for high clouds, while a robust decrease of ΔC is noticed for optically thick low clouds. The large differences between C5 and C6 results are from improvements in calibration and cloud retrieval algorithms. The large positive cloud cover responses with data after 2010 and the strong sensitivity to time period obtained from the Terra (C5 and C6) data are likely due to calibration drift that has not been corrected, suggesting that the previous estimate of the short-term cloud cover response from the these data should be revisited.

Validating Above-cloud Aerosol Optical Depth Retrieved from MODIS using NASA Ames Airborne Sun-Tracking Photometric and Spectrometric (AATS and 4STAR) Measurements

NASA Astrophysics Data System (ADS)

Jethva, H. T.; Torres, O.; Remer, L. A.; Redemann, J.; Dunagan, S. E.; Livingston, J. M.; Shinozuka, Y.; Kacenelenbogen, M. S.; Segal-Rosenhaimer, M.

2014-12-01

Absorbing aerosols produced from biomass burning and dust outbreaks are often found to overlay the lower level cloud decks as evident in the satellite images. In contrast to the cloud-free atmosphere, in which aerosols generally tend to cool the atmosphere, the presence of absorbing aerosols above cloud poses greater potential of exerting positive radiative effects (warming) whose magnitude directly depends on the aerosol loading above cloud, optical properties of clouds and aerosols, and cloud fraction. In recent years, development of algorithms that exploit satellite-based passive measurements of ultraviolet (UV), visible, and polarized light as well as lidar-based active measurements constitute a major breakthrough in the field of remote sensing of aerosols. While the unprecedented quantitative information on aerosol loading above cloud is now available from NASA's A-train sensors, a greater question remains ahead: How to validate the satellite retrievals of above-cloud aerosols (ACA)? Direct measurements of ACA such as carried out by the NASA Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) can be of immense help in validating ACA retrievals. In this study, we validate the ACA optical depth retrieved using the 'color ratio' (CR) method applied to the MODIS cloudy-sky reflectance by using the airborne AATS and 4STAR measurements. A thorough search of the historic AATS-4STAR database collected during different field campaigns revealed five events where biomass burning, dust, and wildfire-emitted aerosols were found to overlay lower level cloud decks observed during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS-2013, respectively. The co-located satellite-airborne measurements revealed a good agreement (root-mean-square-error<0.1 for Aerosol Optical Depth (AOD) at 500 nm) with most matchups falling within the estimated uncertainties in the MODIS retrievals (-10% to +50%). An extensive validation of satellite-based ACA retrievals requires equivalent field measurements particularly over the regions where ACA are often observed from satellites, i.e., south-eastern Atlantic Ocean, tropical Atlantic Ocean, northern Arabian Sea, South-East and North-East Asia.

Near-Real Time Cloud Retrievals from Operational and Research Meteorological Satellites

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Nguyen, Louis; Palilonda, Rabindra; Heck, Patrick W.; Spangenberg, Douglas A.; Doelling, David R.; Ayers, J. Kirk; Smith, William L., Jr.; Khaiyer, Mandana M.; Trepte, Qing Z.;

XBAER-derived aerosol optical thickness from OLCI/Sentinel-3 observation

NASA Astrophysics Data System (ADS)

Mei, Linlu; Rozanov, Vladimir; Vountas, Marco; Burrows, John P.; Richter, Andreas

2018-02-01

A cloud identification algorithm used for cloud masking, which is based on the spatial variability of reflectances at the top of the atmosphere in visible wavelengths, has been developed for the retrieval of aerosol properties by MODIS. It is shown that the spatial pattern of cloud reflectance, as observed from space, is very different from that of aerosols. Clouds show a high spatial variability in the scale of a hundred metres to a few kilometres, whereas aerosols in general are homogeneous. The concept of spatial variability of reflectances at the top of the atmosphere is mainly applicable over the ocean, where the surface background is sufficiently homogeneous for the separation between aerosols and clouds. Aerosol retrievals require a sufficiently accurate cloud identification to be able to mask these ground scenes. However, a conservative mask will exclude strong aerosol episodes and a less conservative mask could introduce cloud contamination that biases the retrieved aerosol optical properties (e.g. aerosol optical depth and effective radii). A detailed study on the effect of cloud contamination on aerosol retrievals has been performed and parameters are established determining the threshold value for the MODIS aerosol cloud mask (3×3-STD) over the ocean. The 3×3-STD algorithm discussed in this paper is the operational cloud mask used for MODIS aerosol retrievals over the ocean.A prolonged pollution haze event occurred in the northeast part of China during the period 16-21 December 2016. To assess the impact of such events, the amounts and distribution of aerosol particles, formed in such events, need to be quantified. The newly launched Ocean Land Colour Instrument (OLCI) onboard Sentinel-3 is the successor of the MEdium Resolution Imaging Spectrometer (MERIS). It provides measurements of the radiance and reflectance at the top of the atmosphere, which can be used to retrieve the aerosol optical thickness (AOT) from synoptic to global scales. In this study, the recently developed AOT retrieval algorithm eXtensible Bremen AErosol Retrieval (XBAER) has been applied to data from the OLCI instrument for the first time to illustrate the feasibility of applying XBAER to the data from this new instrument. The first global retrieval results show similar patterns of aerosol optical thickness, AOT, to those from MODIS and MISR aerosol products. The AOT retrieved from OLCI is validated by comparison with AERONET observations and a correlation coefficient of 0.819 and bias (root mean square) of 0.115 is obtained. The haze episode is well captured by the OLCI-derived AOT product. XBAER is shown to retrieve AOT well from the observations of MERIS and OLCI.

Frequency and causes of failed MODIS cloud property retrievals for liquid phase clouds over global oceans.

PubMed

Cho, Hyoun-Myoung; Zhang, Zhibo; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S; Di Girolamo, Larry; C-Labonnote, Laurent; Cornet, Céline; Riedi, Jerome; Holz, Robert E

2015-05-16

Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves cloud droplet effective radius ( r e ) and optical thickness ( τ ) by projecting observed cloud reflectances onto a precomputed look-up table (LUT). When observations fall outside of the LUT, the retrieval is considered "failed" because no combination of τ and r e within the LUT can explain the observed cloud reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of Aqua MODIS Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 µm and 2.1 µm MODIS channel combination has an overall failure rate of about 16% (10% for the 0.86 µm and 3.7 µm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading type of failure is the " r e too large" failure accounting for 60%-85% of all failed retrievals. The rest is mostly due to the " r e too small" or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun-satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping, and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar reflectivity observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study.

Frequency and causes of failed MODIS cloud property retrievals for liquid phase clouds over global oceans

PubMed Central

Cho, Hyoun‐Myoung; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S.; Di Girolamo, Larry; C.‐Labonnote, Laurent; Cornet, Céline; Riedi, Jerome; Holz, Robert E.

2015-01-01

Abstract Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves cloud droplet effective radius (r e) and optical thickness (τ) by projecting observed cloud reflectances onto a precomputed look‐up table (LUT). When observations fall outside of the LUT, the retrieval is considered “failed” because no combination of τ and r e within the LUT can explain the observed cloud reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of Aqua MODIS Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 µm and 2.1 µm MODIS channel combination has an overall failure rate of about 16% (10% for the 0.86 µm and 3.7 µm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading type of failure is the “r e too large” failure accounting for 60%–85% of all failed retrievals. The rest is mostly due to the “r e too small” or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun‐satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping, and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar reflectivity observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study. PMID:27656330

Validation of Cloud Optical Parameters from Passive Remote Sensing in the Arctic by using the Aircraft Measurements

NASA Astrophysics Data System (ADS)

Chen, H.; Schmidt, S.; Coddington, O.; Wind, G.; Bucholtz, A.; Segal-Rosenhaimer, M.; LeBlanc, S. E.

2017-12-01

Cloud Optical Parameters (COPs: e.g., cloud optical thickness and cloud effective radius) and surface albedo are the most important inputs for determining the Cloud Radiative Effect (CRE) at the surface. In the Arctic, the COPs derived from passive remote sensing such as from the Moderate Resolution Imaging Spectroradiometer (MODIS) are difficult to obtain with adequate accuracy owing mainly to insufficient knowledge about the snow/ice surface, but also because of the low solar zenith angle. This study aims to validate COPs derived from passive remote sensing in the Arctic by using aircraft measurements collected during two field campaigns based in Fairbanks, Alaska. During both experiments, ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) and ARISE (Arctic Radiation-IceBridge Sea and Ice Experiment), the Solar Spectral Flux Radiometer (SSFR) measured upwelling and downwelling shortwave spectral irradiances, which can be used to derive surface and cloud albedo, as well as the irradiance transmitted by clouds. We assess the variability of the Arctic sea ice/snow surfaces albedo through these aircraft measurements and incorporate this variability into cloud retrievals for SSFR. We then compare COPs as derived from SSFR and MODIS for all suitable aircraft underpasses of the satellites. Finally, the sensitivities of the COPs to surface albedo and solar zenith angle are investigated.

Impact of MODIS SWIR Band Calibration Improvements on Level-3 Atmospheric Products

NASA Technical Reports Server (NTRS)

Wald, Andrew; Levy, Robert; Angal, Amit; Geng, Xu; Xiong, Jack; Hoffman, Kurt

2016-01-01

The spectral reflectance measured by the MODIS reflective solar bands (RSB) is used for retrieving many atmospheric science products. The accuracy of these products depends on the accuracy of the calibration of the RSB. To this end, the RSB of the MODIS instruments are primarily calibrated on-orbit using regular solar diffuser (SD) observations. For lambda < 0.94 microns the SDs on-orbit bi-directional reflectance factor (BRF) change is tracked using solar diffuser stability monitor (SDSM) observations. For lambda > 0.94 microns, the MODIS Characterization Support Team (MCST) developed, in MODIS Collection 6 (C6), a time-dependent correction using observations from pseudo-invariant earth-scene targets. This correction has been implemented in C6 for the Terra MODIS 1.24 micron band over the entire mission, and for the 1.375 micron band in the forward processing. As the instruments continue to operate beyond their design lifetime of six years, a similar correction is planned for other short-wave infrared (SWIR) bands as well. MODIS SWIR bands are used in deriving atmosphere products, including aerosol optical thickness, atmospheric total column water vapor, cloud fraction and cloud optical depth. The SD degradation correction in Terra bands 5 and 26 impact the spectral radiance and therefore the retrieval of these atmosphere products. Here, we describe the corrections to Bands 5 (1.24 microns) and 26 (1.375 microns), and produce three sets (B5, B26 correction on/on, on/off, and off/off) of Terra-MODIS Level 1B (calibrated radiance product) data. By comparing products derived from these corrected and uncorrected Terra MODIS Level 1B (L1B) calibrations, dozens of L3 atmosphere products are surveyed for changes caused by the corrections, and representative results are presented. Aerosol and water vapor products show only small local changes, while some cloud products can change locally by > 10%, which is a large change.

Evaluation of the OMI Cloud Pressures Derived from Rotational Raman Scattering by Comparisons with other Satellite Data and Radiative Transfer Simulations

NASA Technical Reports Server (NTRS)

Vasilkov, Alexander; Joiner, Joanna; Spurr, Robert; Bhartia, Pawan K.; Levelt, Pieternel; Stephens, Graeme

2009-01-01

In this paper we examine differences between cloud pressures retrieved from the Ozone Monitoring Instrument (OMI) using the ultraviolet rotational Raman scattering (RRS) algorithm and those from the thermal infrared (IR) Aqua/MODIS. Several cloud data sets are currently being used in OMI trace gas retrieval algorithms including climatologies based on IR measurements and simultaneous cloud parameters derived from OMI. From a validation perspective, it is important to understand the OMI retrieved cloud parameters and how they differ with those derived from the IR. To this end, we perform radiative transfer calculations to simulate the effects of different geophysical conditions on the OMI RRS cloud pressure retrievals. We also quantify errors related to the use of the Mixed Lambert-Equivalent Reflectivity (MLER) concept as currently implemented of the OMI algorithms. Using properties from the Cloudsat radar and MODIS, we show that radiative transfer calculations support the following: (1) The MLER model is adequate for single-layer optically thick, geometrically thin clouds, but can produce significant errors in estimated cloud pressure for optically thin clouds. (2) In a two-layer cloud, the RRS algorithm may retrieve a cloud pressure that is either between the two cloud decks or even beneath the top of the lower cloud deck because of scattering between the cloud layers; the retrieved pressure depends upon the viewing geometry and the optical depth of the upper cloud deck. (3) Absorbing aerosol in and above a cloud can produce significant errors in the retrieved cloud pressure. (4) The retrieved RRS effective pressure for a deep convective cloud will be significantly higher than the physical cloud top pressure derived with thermal IR.

Extending "Deep Blue" aerosol retrieval coverage to cases of absorbing aerosols above clouds: Sensitivity analysis and first case studies

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.

2016-05-01

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty ˜25-50% (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty ˜10-20%, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

Optical and Microphysical Retrievals of Marine Stratocumulus Clouds off the Coast of Namibia from Satellite and Aircraft

NASA Technical Reports Server (NTRS)

Platnick, Steven E.

2010-01-01

Though the emphasis of the Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign was largely on emission sources and transport, the assemblage of aircraft (including the high altitude NASA ER-2 remote sensing platform and the University of Washington CV-580, UK MRF C-130, and South African Weather Bureau JRA in situ aircrafts) provided a unique opportunity for cloud studies. Therefore, as part of the SAFARI initiative, investigations were undertaken to assess regional aerosol-cloud interactions and cloud remote sensing algorithms. In particular, the latter part of the experiment concentrated on marine boundary layer stratocumulus clouds off the southwest coast of Africa. Associated with cold water upwelling along the Benguela current, the Namibian stratocumulus regime has received limited attention but appears to be unique for several reasons. During the dry season, outflow of continental fires and industrial pollution over this area can be extreme. From below, upwelling provides a rich nutrient source for phytoplankton (a source of atmospheric sulfur through DMS production as well as from decay processes). The impact of these natural and anthropogenic sources on the microphysical and optical properties of the stratocumulus is unknown. Continental and Indian Ocean cloud systems of opportunity were also studied during the campaign. SAFARI 2000 aircraft flights off the coast of Namibia were coordinated with NASA Terra Satellite overpasses for synergy with the Moderate Resolution Imaging Spectroradiometer (MODIS) and other Terra instruments. MODIS was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 (and Aqua spacecraft on May 4, 2002). Among the remote sensing algorithms developed and applied to this sensor are cloud optical and microphysical properties that include cloud thermodynamic phase, optical thickness, and effective particle radius of both liquid water and ice clouds. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, and fundamental atmospheric research. The archived MODIS Collection 5 cloud products processing stream will be used to analyze low water cloud scenes off the Namibian and Angolan coasts during SAFARI 2000 time period, as well as other years. Pixel-level Terra and Aqua MODIS retrievals (l. km spatial resolution at nadir) and gridded (1' uniform grid) statistics of cloud optical thickness and effective particle radius will be presented, including joint probability distributions between the two quantities. In addition, perspectives from the MODIS Airborne Simulator, which flew on the ER-2 during SAFARI 2000 providing high spatial resolution retrievals (50 m at nadir), will be presented as appropriate. The H-SAF Program requires an experimental operational European-centric Satellite Precipitation Algorithm System (E-SPAS) that produces medium spatial resolution and high temporal resolution surface rainfall and snowfall estimates over the Greater European Region including the Greater Mediterranean Basin. Currently, there are various types of experimental operational algorithm methods of differing spatiotemporal resolutions that generate global precipitation estimates. This address will first assess the current status of these methods and then recommend a methodology for the H-SAF Program that deviates somewhat from the current approach under development but one that takes advantage of existing techniques and existing software developed for the TRMM Project and available through the public domain.

An Algorithm for the Retrieval of Droplet Number Concentration and Geometrical Thickness of Stratiform Marine Boundary Layer Clouds Applied to MODIS Radiometric Observations.

NASA Astrophysics Data System (ADS)

Schüller, Lothar; Bennartz, Ralf; Fischer, Jürgen; Brenguier, Jean-Louis

2005-01-01

Algorithms are now currently used for the retrieval of cloud optical thickness and droplet effective radius from multispectral radiance measurements. This paper extends their application to the retrieval of cloud droplet number concentration, cloud geometrical thickness, and liquid water path in shallow convective clouds, using an algorithm that was previously tested with airborne measurements of cloud radiances and validated against in situ measurements of the same clouds. The retrieval is based on a stratified cloud model of liquid water content and droplet spectrum. Radiance measurements in visible and near-infrared channels of the Moderate Resolution Imaging Spectroradiometer (MODIS), which is operated from the NASA platforms Terra and Aqua, are analyzed. Because of uncertainties in the simulation of the continental surface reflectance, the algorithm is presently limited to the monitoring of the microphysical structure of boundary layer clouds over the ocean. Two MODIS scenes of extended cloud fields over the North Atlantic Ocean trade wind region are processed. A transport and dispersion model (the Hybrid Single-Particle Lagrangian Integrated Trajectory Model, HYSPLIT4) is also used to characterize the origin of the air masses and hence their aerosol regimes. One cloud field formed in an air mass that was advected from southern Europe and North Africa. It shows high values of the droplet concentration when compared with the second cloud system, which developed in a more pristine environment. The more pristine case also exhibits a higher geometrical thickness and, thus, liquid water path, which counterbalances the expected cloud albedo increase of the polluted case. Estimates of cloud liquid water path are then compared with retrievals from the Special Sensor Microwave Imager (SSM/I). SSM/I-derived liquid water paths are in good agreement with the MODIS-derived values.

Optimal Exploitation of the Temporal and Spatial Resolution of SEVIRI for the Nowcasting of Clouds

NASA Astrophysics Data System (ADS)

Sirch, Tobias; Bugliaro, Luca

2015-04-01

Optimal Exploitation of the Temporal and Spatial Resolution of SEVIRI for the Nowcasting of Clouds An algorithm was developed to forecast the development of water and ice clouds for the successive 5-120 minutes separately using satellite data from SEVIRI (Spinning Enhanced Visible and Infrared Imager) aboard Meteosat Second Generation (MSG). In order to derive cloud cover, optical thickness and cloud top height of high ice clouds "The Cirrus Optical properties derived from CALIOP and SEVIRI during day and night" (COCS, Kox et al. [2014]) algorithm is applied. For the determination of the liquid water clouds the APICS ("Algorithm for the Physical Investigation of Clouds with SEVIRI", Bugliaro e al. [2011]) cloud algorithm is used, which provides cloud cover, optical thickness and effective radius. The forecast rests upon an optical flow method determining a motion vector field from two satellite images [Zinner et al., 2008.] With the aim of determining the ideal time separation of the satellite images that are used for the determination of the cloud motion vector field for every forecast horizon time the potential of the better temporal resolution of the Meteosat Rapid Scan Service (5 instead of 15 minutes repetition rate) has been investigated. Therefore for the period from March to June 2013 forecasts up to 4 hours in time steps of 5 min based on images separated by a time interval of 5 min, 10 min, 15 min, 30 min have been created. The results show that Rapid Scan data produces a small reduction of errors for a forecast horizon up to 30 minutes. For the following time steps forecasts generated with a time interval of 15 min should be used and for forecasts up to several hours computations with a time interval of 30 min provide the best results. For a better spatial resolution the HRV channel (High Resolution Visible, 1km instead of 3km maximum spatial resolution at the subsatellite point) has been integrated into the forecast. To detect clouds the difference of the measured albedo from SEVIRI and the clear-sky albedo provided by MODIS has been used and additionally the temporal development of this quantity. A pre-requisite for this work was an adjustment of the geolocation accuracy for MSG and MODIS by shifting the MODIS data and quantifying the correlation between both data sets.

Volcanic Ash Retrievals Using ORAC and Satellite Measurements in the Visible and IR

NASA Astrophysics Data System (ADS)

Mcgarragh, Gregory R.; Thomas, Gareth E.; Povey, Adam C.; Poulsen, Caroline A.; Grainger, Roy G.

2015-11-01

The Optimal Retrieval of Aerosol and Cloud (ORAC) is a generalized optimal estimation system that uses visible to infrared measurements from a wide range of instruments including AATSR, AVHRR, MODIS and SEVIRI. Recently, support to retrieve volcanic ash has been added for which it retrieves optical thickness, effective radius and cloud top pressure. In this proceeding we discuss the implementation of the volcanic ash retrieval in ORAC including the retrieval methodology, forward model, sources of uncertainty and the discrimination of ash from aerosol and cloud. Results are presented that are consistent with a well know eruption from both AATSR and MODIS while results of a full SEVIRI retrieval of ash, aerosol and cloud properties relative to the ash is are discussed.

A Neural Network Approach to Infer Optical Depth of Thick Ice Clouds at Night

NASA Technical Reports Server (NTRS)

Minnis, P.; Hong, G.; Sun-Mack, S.; Chen, Yan; Smith, W. L., Jr.

2016-01-01

One of the roadblocks to continuously monitoring cloud properties is the tendency of clouds to become optically black at cloud optical depths (COD) of 6 or less. This constraint dramatically reduces the quantitative information content at night. A recent study found that because of their diffuse nature, ice clouds remain optically gray, to some extent, up to COD of 100 at certain wavelengths. Taking advantage of this weak dependency and the availability of COD retrievals from CloudSat, an artificial neural network algorithm was developed to estimate COD values up to 70 from common satellite imager infrared channels. The method was trained using matched 2007 CloudSat and Aqua MODIS data and is tested using similar data from 2008. The results show a significant improvement over the use of default values at night with high correlation. This paper summarizes the results and suggests paths for future improvement.

Satellite remote sensing of dust aerosol indirect effects on ice cloud formation.

PubMed

Ou, Steve Szu-Cheng; Liou, Kuo-Nan; Wang, Xingjuan; Hansell, Richard; Lefevre, Randy; Cocks, Stephen

2009-01-20

We undertook a new approach to investigate the aerosol indirect effect of the first kind on ice cloud formation by using available data products from the Moderate-Resolution Imaging Spectrometer (MODIS) and obtained physical understanding about the interaction between aerosols and ice clouds. Our analysis focused on the examination of the variability in the correlation between ice cloud parameters (optical depth, effective particle size, cloud water path, and cloud particle number concentration) and aerosol optical depth and number concentration that were inferred from available satellite cloud and aerosol data products. Correlation results for a number of selected scenes containing dust and ice clouds are presented, and dust aerosol indirect effects on ice clouds are directly demonstrated from satellite observations.

Comparison of Marine Boundary Layer Cloud Properties from CERES-MODIS Edition 4 and DOE ARM AMF Measurements at the Azores

NASA Technical Reports Server (NTRS)

Xi, Baike; Dong, Xiquan; Minnis, Patrick; Sun-Mack, Sunny

2014-01-01

Marine boundary layer (MBL) cloud properties derived from the NASA Clouds and the Earth's Radiant Energy System (CERES) project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Department of Energy Atmospheric Radiation Measurement (ARM) Mobile Facility at the Azores (AMF-Azores) site from June 2009 through December 2010. Cloud properties derived from ARM ground-based observations were averaged over a 1 h interval centered at the satellite overpass time, while the CERES-MODIS (CM) results were averaged within a 30 km×30 km grid box centered over the Azores site. A total of 63 daytime and 92 nighttime single-layered overcast MBL cloud cases were selected from 19 months of ARM radar-lidar and satellite observations. The CM cloud top/base heights (Htop/Hbase) were determined from cloud top/base temperatures (Ttop/Tbase) using a regional boundary layer lapse rate method. For daytime comparisons, the CM-derived Htop (Hbase), on average, is 0.063 km (0.068 km) higher (lower) than its ARM radar-lidar-observed counterpart, and the CM-derived Ttop and Tbase are 0.9 K less and 2.5 K greater than the surface values with high correlations (R(sup 2) = 0.82 and 0.84, respectively). In general, the cloud top comparisons agree better than the cloud base comparisons, because the CM cloud base temperatures and heights are secondary products determined from cloud top temperatures and heights. No significant day-night difference was found in the analyses. The comparisons of MBL cloud microphysical properties reveal that when averaged over a 30 km× 30 km area, the CM-retrieved cloud droplet effective radius (re) at 3.7 micrometers is 1.3 micrometers larger than that from the ARM retrievals (12.8 micrometers), while the CM-retrieved cloud liquid water path (LWP) is 13.5 gm( exp -2) less than its ARM counterpart (114.2 gm( exp-2) due to its small optical depth (9.6 versus 13.7). The differences are reduced by 50% when the CM averages are computed only using the MODIS pixel nearest the AMF site. Using the effective radius retrieved using 2.1 micrometers channel to calculate LWP can reduce the difference between the CM and ARM microwave radiometer retrievals from 13.7 to 2.1 gm2. The 10% differences between the ARM and CERES-MODIS LWP and r(sub e) retrievals are within the uncertainties of the ARM LWP (approximately 20gm( exp -2)) and r(sub e) (approximately 10%) retrievals; however, the 30% difference in optical depth is significant. Possible reasons contributing to this discrepancy are increased sensitivities in optical depth from both surface retrievals when t is approximately 10 and topography. The t differences vary with wind direction and are consistent with the island orography.Much better agreement in t is obtained when using only those data taken when the wind is from the northeast, where topographical effects on the sampled clouds are minimal.

Comparison of marine boundary layer cloud properties from CERES-MODIS Edition 4 and DOE ARM AMF measurements at the Azores

NASA Astrophysics Data System (ADS)

Xi, Baike; Dong, Xiquan; Minnis, Patrick; Sun-Mack, Sunny

2014-08-01

Marine boundary layer (MBL) cloud properties derived from the NASA Clouds and the Earth's Radiant Energy System (CERES) project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Department of Energy Atmospheric Radiation Measurement (ARM) Mobile Facility at the Azores (AMF-Azores) site from June 2009 through December 2010. Cloud properties derived from ARM ground-based observations were averaged over a 1 h interval centered at the satellite overpass time, while the CERES-MODIS (CM) results were averaged within a 30 km × 30 km grid box centered over the Azores site. A total of 63 daytime and 92 nighttime single-layered overcast MBL cloud cases were selected from 19 months of ARM radar-lidar and satellite observations. The CM cloud top/base heights (Htop/Hbase) were determined from cloud top/base temperatures (Ttop/Tbase) using a regional boundary layer lapse rate method. For daytime comparisons, the CM-derived Htop (Hbase), on average, is 0.063 km (0.068 km) higher (lower) than its ARM radar-lidar-observed counterpart, and the CM-derived Ttop and Tbase are 0.9 K less and 2.5 K greater than the surface values with high correlations (R2 = 0.82 and 0.84, respectively). In general, the cloud top comparisons agree better than the cloud base comparisons, because the CM cloud base temperatures and heights are secondary products determined from cloud top temperatures and heights. No significant day-night difference was found in the analyses. The comparisons of MBL cloud microphysical properties reveal that when averaged over a 30 km × 30 km area, the CM-retrieved cloud droplet effective radius (re) at 3.7 µm is 1.3 µm larger than that from the ARM retrievals (12.8 µm), while the CM-retrieved cloud liquid water path (LWP) is 13.5 gm-2 less than its ARM counterpart (114.2 gm-2) due to its small optical depth (9.6 versus 13.7). The differences are reduced by 50% when the CM averages are computed only using the MODIS pixel nearest the AMF site. Using the effective radius retrieved using 2.1 µm channel to calculate LWP can reduce the difference between the CM and ARM microwave radiometer retrievals from -13.7 to 2.1 gm-2. The 10% differences between the ARM and CERES-MODIS LWP and re retrievals are within the uncertainties of the ARM LWP ( 20 gm-2) and re ( 10%) retrievals; however, the 30% difference in optical depth is significant. Possible reasons contributing to this discrepancy are increased sensitivities in optical depth from both surface retrievals when τ 10 and topography. The τ differences vary with wind direction and are consistent with the island orography. Much better agreement in τ is obtained when using only those data taken when the wind is from the northeast, where topographical effects on the sampled clouds are minimal.

Monitoring volcanic ash cloud top height through simultaneous retrieval of optical data from polar orbiting and geostationary satellites

NASA Astrophysics Data System (ADS)

Zakšek, K.; Hort, M.; Zaletelj, J.; Langmann, B.

2012-09-01

Volcanic ash cloud top height (ACTH) can be monitored on the global level using satellite remote sensing. Here we propose a photogrammetric method based on the parallax between data retrieved from geostationary and polar orbiting satellites to overcome some limitations of the existing methods of ACTH retrieval. SEVIRI HRV band and MODIS band 1 are a good choice because of their high resolution. The procedure works well if the data from both satellites are retrieved nearly simultaneously. MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. The proposed method was tested for the case of the Eyjafjallajökull eruption in April 2010. The parallax between MODIS and SEVIRI data can reach over 30 km which implies ACTH of more than 12 km in the beginning of the eruption. In the end of April eruption ACTH of 3-4 km is observed. The accuracy of ACTH was estimated to be 0.6 km.

Monitoring volcanic ash cloud top height through simultaneous retrieval of optical data from polar orbiting and geostationary satellites

NASA Astrophysics Data System (ADS)

Zakšek, K.; Hort, M.; Zaletelj, J.; Langmann, B.

2013-03-01

Volcanic ash cloud-top height (ACTH) can be monitored on the global level using satellite remote sensing. Here we propose a photogrammetric method based on the parallax between data retrieved from geostationary and polar orbiting satellites to overcome some limitations of the existing methods of ACTH retrieval. SEVIRI HRV band and MODIS band 1 are a good choice because of their high resolution. The procedure works well if the data from both satellites are retrieved nearly simultaneously. MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. The proposed method was tested for the case of the Eyjafjallajökull eruption in April 2010. The parallax between MODIS and SEVIRI data can reach 30 km, which implies an ACTH of approximately 12 km at the beginning of the eruption. At the end of April eruption an ACTH of 3-4 km is observed. The accuracy of ACTH was estimated to be 0.6 km.

A Comparison of High Spectral Resolution Infrared Cloud-Top Pressure Altitude Algorithms Using S-HIS Measurements

NASA Technical Reports Server (NTRS)

Holz, Robert E.; Ackerman, Steve; Antonelli, Paolo; Nagle, Fred; McGill, Matthew; Hlavka, Dennis L.; Hart, William D.

2005-01-01

This paper presents a comparison of cloud-top altitude retrieval methods applied to S-HIS (Scanning High Resolution Interferometer Sounder) measurements. Included in this comparison is an improvement to the traditional CO2 Slicing method. The new method, CO2 Sorting, determines optimal channel pairs to apply the CO2 Slicing. Measurements from collocated samples of the Cloud Physics Lidar (CPL) and Modis Airborne Simulator (MAS) instruments assist in the comparison. For optically thick clouds good correlation between the S-HIS and lidar cloud-top retrievals are found. For tenuous ice clouds there can be large differences between lidar (CPL) and S-HIS retrieved cloud-tops. It is found that CO2 Sorting significantly reduces the cloud height biases for the optically thin cloud (total optical depths less then 1.0). For geometrically thick but optically thin cirrus clouds large differences between the S-HIS infrared cloud top retrievals and the CPL detected cloud top where found. For these cases the cloud height retrieved by the S-HIS cloud retrievals correlated closely with the level the CPL integrated cloud optical depth was approximately 1.0.

Extending "Deep Blue" Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: Sensitivity Analysis and First Case Studies

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.

2016-01-01

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty approximately 25-50 percent (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty approximately10-20 percent, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

Comparison of Envisat ASAR GM, AMSR-E Passive Microwave, and MODIS Optical Remote Sensing for Flood Monitoring in Australia

NASA Astrophysics Data System (ADS)

Ticehurst, C. J.; Bartsch, A.; Doubkova, M.; van Dijk, A. I. J. M.

2009-11-01

Continuous flood monitoring can support emergency response, water management and environmental monitoring. Optical sensors such as MODIS allow inundation mapping with high spatial and temporal resolution (250-1000 m, twice daily) but are affected by cloud cover. Passive microwave sensors also acquire observations at high temporal resolution, but coarser spatial resolution (e.g. ca. 5-70 km for AMSR-E) and smaller footprints are also affected by cloud and/or rain. ScanSAR systems allow all-weather monitoring but require spatial resolution to be traded off against coverage and/or temporal resolution; e.g. the ENVISAT ASAR Global Mode observes at ca. 1 km over large regions about twice a week. The complementary role of the AMSR-E and ASAR GM data to that of MODIS is here introduced for three flood events and locations across Australia. Additional improvements can be made by integrating digital elevation models and stream flow gauging data.

Statistical Studies on Thin Cirrus from MODIS Data

NASA Technical Reports Server (NTRS)

Li, Rong-Rong; Kaufman, Yoram; Remer, Lorraine

2004-01-01

The 1.38 micron channel on the MODerate resolution Imaging Spectroradiomater (MODIS) is an ideal channel to identify and quantify thin cirrus on a global basis. This channel is used to produce the cirrus reflectance product in MOD06 and also used extensively by the MODIS aerosol algorithms to mask clouds for the MOD04 product. The aerosol product uses a lower threshold of the 1.38 micron channel reflectance of 0.01. A cirrus channel reflectance of 0.01 corresponds to approximately an aerosol optical thickness of 0.10. Therefore, the ambiguity due to the minor cirrus contamination may introduce artificial optical thickness in the aerosol products. The questions arise: How prevalent are the thinnest cirrus clouds over the globe? Do they persist over specific regions and seasons? Can we distinguish between the noise of the channel and the actual cloudiness by extrapolating the cloudiness signal to very dark scenes, statistically. We analyze the Terra data, over land and ocean to answer these questions.

Monte Carlo Bayesian Inference on a Statistical Model of Sub-gridcolumn Moisture Variability Using High-resolution Cloud Observations . Part II; Sensitivity Tests and Results

NASA Technical Reports Server (NTRS)

da Silva, Arlindo M.; Norris, Peter M.

2013-01-01

Part I presented a Monte Carlo Bayesian method for constraining a complex statistical model of GCM sub-gridcolumn moisture variability using high-resolution MODIS cloud data, thereby permitting large-scale model parameter estimation and cloud data assimilation. This part performs some basic testing of this new approach, verifying that it does indeed significantly reduce mean and standard deviation biases with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud top pressure, and that it also improves the simulated rotational-Ramman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the OMI instrument. Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows finite jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. This paper also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in the cloud observables on cloud vertical structure, beyond cloud top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard (1998) provides some help in this respect, by better honoring inversion structures in the background state.

Modeling Aerosol Microphysical and Radiative Effects on Clouds and Implications for the Effects of Black and Brown Carbon on Clouds

NASA Astrophysics Data System (ADS)

Ten Hoeve, J. E.; Jacobson, M. Z.

2010-12-01

Satellite observational studies have found an increase in cloud fraction (CF) and cloud optical depth (COD) with increasing aerosol optical depth (AOD) followed by a decreasing CF/COD with increasing AOD at higher AODs over the Amazon Basin. The shape of this curve is similar to that of a boomerang, and thus the effect has been dubbed the "boomerang effect.” The increase in CF/COD with increasing AOD at low AODs is ascribed to the first and second indirect effects and is referred to as a microphysical effect of aerosols on clouds. The decrease in CF/COD at higher AODs is ascribed to enhanced warming of clouds due to absorbing aerosols, either as inclusions in drops or interstitially between drops. This is referred to as a radiative effect. To date, the interaction of the microphysical and radiative effects has not been simulated with a regional or global computer model. Here, we simulate the boomerang effect with the nested global-through-urban climate, air pollution, weather forecast model, GATOR-GCMOM, for the Amazon biomass burning season of 2006. We also compare the model with an extensive set of data, including satellite data from MODIS, TRMM, and CALIPSO, in situ surface observations, upper-air data, and AERONET data. Biomass burning emissions are obtained from the Global Fire Emissions Database (GFEDv2), and are combined with MODIS land cover data along with biomass burning emission factors. A high-resolution domain, nested within three increasingly coarser domains, is employed over the heaviest biomass burning region within the arc of deforestation. Modeled trends in cloud properties with aerosol loading compare well with MODIS observed trends, allowing causation of these observed correlations, including of the boomerang effect, to be determined by model results. The impact of aerosols on various cloud parameters, such as cloud optical thickness, cloud fraction, cloud liquid water/ice content, and precipitation, are shown through differences between simulations that include and exclude biomass burning emissions. This study suggests by cause and effect through numerical modeling that aerosol radiative effects counteract microphysical effects at high AODs, a result previously shown by correlation alone. As such, computer models that exclude treatment of cloud radiative effects are likely to overpredict the indirect effects of aerosols on clouds and underestimate the warming due to aerosols containing black carbon.

The Research on the Spectral Characteristics of Sea Fog Based on Caliop and Modis Data

NASA Astrophysics Data System (ADS)

Wan, J.; Su, J.; Liu, S.; Sheng, H.

2018-04-01

In view of that difficulty of distinguish between sea fog and low cloud by optical remote sensing mean, the research on spectral characteristics of sea fog is focused and carried out. The satellite laser radar CALIOP data and the high spectral MODIS data were obtained from May to December 2017, and the scattering coefficient and the vertical height information were extracted from the atmospheric attenuation of the lower star to extract the sea fog sample points, and the spectral response curve based on MODIS was formed to analyse the spectral response characteristics of the sea fog, thus providing a theoretical basis for the monitoring of sea fog with optical remote sensing image.

How Often and Why MODIS Cloud Property Retrievals Fail for Liquid-Phase Clouds over Ocean? a Comprehensive Analysis Based on a-Train Observations

NASA Astrophysics Data System (ADS)

Zhang, Z.; Cho, H. M.; Platnick, S. E.; Meyer, K.; Lebsock, M. D.

2014-12-01

The cloud optical thickness (τ) and droplet effective radius (re) are two key cloud parameters retrieved by MODIS (Moderate Resolution Imaging Spectroradiometer). These MODIS cloud products are widely used in a broad range of earth system science applications. In this paper, we present a comprehensive analysis of the failed cloud τ and/or re retrievals for liquid-phase clouds over ocean in the Collection 6 MODIS cloud product. The main findings from this study are summarized as follows: MODIS retrieval failure rates for marine boundary layer (MBL) clouds have a strong dependence on the spectral combination used for retrieval (e.g., 0.86 + 2.1 µm vs. 0.8 + 3.7 µm) and the cloud morphology (i.e., "good" pixels vs. partly cloudy (PCL) pixels). Combining all clear-sky-restoral (CSR) categories (CSR=0,1 and 3), the 0.86 + 2.1 µm and 0.86 + 3.7 µm spectral combinations have an overall failure rate of about 20% and 12%, respectively (See figure below). The PCL pixels (CSR=1 & 3) have significantly higher failure rates and contribute more to the total failure population than the "good" (CSR=0) pixels. The majority of the failed retrievals are caused by the re too large failure, which explains about 85% and 70% of the failed 0.86 + 2.1 µm and 0.86 + 3.7 µm retrievals, respectively. The remaining failures are either due to the re too small failure or τ retrieval failure. The geographical distribution of failure rates has a significant dependence on cloud regime, lower over the coastal stratocumulus cloud regime and higher over the broken trade-wind cumulus cloud regime over open oceans. Enhanced retrieval failure rates are found when MBL clouds have high sub-pixel inhomogeneity , or are located at special Sun-satellite viewing geometries, such as sunglint, large viewing or solar zenith angle, or cloudbow and glory angles, or subject to cloud masking, cloud overlapping and/or cloud phase retrieval issues. About 80% of the failure retrievals can be attributed to at least one or more potential reasons mentioned above. Collocated radar reflectivity observations from CloudSat suggest that the remaining 20% are unlikely to be retrieval artifacts, but reflection of true cloud microphysics, i.e., the true is either truly very small or very large.

Intercomparison between CMIP5 model and MODIS satellite-retrieved data of aerosol optical depth, cloud fraction, and cloud-aerosol interactions

NASA Astrophysics Data System (ADS)

Sockol, Alyssa; Small Griswold, Jennifer D.

2017-08-01

Aerosols are a critical component of the Earth's atmosphere and can affect the climate of the Earth through their interactions with solar radiation and clouds. Cloud fraction (CF) and aerosol optical depth (AOD) at 550 nm from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used with analogous cloud and aerosol properties from Historical Phase 5 of the Coupled Model Intercomparison Project (CMIP5) model runs that explicitly include anthropogenic aerosols and parameterized cloud-aerosol interactions. The models underestimate AOD by approximately 15% and underestimate CF by approximately 10% overall on a global scale. A regional analysis is then used to evaluate model performance in two regions with known biomass burning activity and absorbing aerosol (South America (SAM) and South Africa (SAF)). In SAM, the models overestimate AOD by 4.8% and underestimate CF by 14%. In SAF, the models underestimate AOD by 35% and overestimate CF by 13.4%. Average annual cycles show that the monthly timing of AOD peaks closely match satellite data in both SAM and SAF for all except the Community Atmosphere Model 5 and Geophysical Fluid Dynamics Laboratory (GFDL) models. Monthly timing of CF peaks closely match for all models (except GFDL) for SAM and SAF. Sorting monthly averaged 2° × 2.5° model or MODIS CF as a function of AOD does not result in the previously observed "boomerang"-shaped CF versus AOD relationship characteristic of regions with absorbing aerosols from biomass burning. Cloud-aerosol interactions, as observed using daily (or higher) temporal resolution data, are not reproducible at the spatial or temporal resolution provided by the CMIP5 models.

Validation of MODIS Aerosol Optical Depth Retrieval Over Land

NASA Technical Reports Server (NTRS)

Chu, D. A.; Kaufman, Y. J.; Ichoku, C.; Remer, L. A.; Tanre, D.; Holben, B. N.; Einaudi, Franco (Technical Monitor)

2001-01-01

Aerosol optical depths are derived operationally for the first time over land in the visible wavelengths by MODIS (Moderate Resolution Imaging Spectroradiometer) onboard the EOSTerra spacecraft. More than 300 Sun photometer data points from more than 30 AERONET (Aerosol Robotic Network) sites globally were used in validating the aerosol optical depths obtained during July - September 2000. Excellent agreement is found with retrieval errors within (Delta)tau=+/- 0.05 +/- 0.20 tau, as predicted, over (partially) vegetated surfaces, consistent with pre-launch theoretical analysis and aircraft field experiments. In coastal and semi-arid regions larger errors are caused predominantly by the uncertainty in evaluating the surface reflectance. The excellent fit was achieved despite the ongoing improvements in instrument characterization and calibration. This results show that MODIS-derived aerosol optical depths can be used quantitatively in many applications with cautions for residual clouds, snow/ice, and water contamination.

The Impact of Subsampling on MODIS Level-3 Statistics of Cloud Optical Thickness and Effective Radius

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros

2004-01-01

The MODIS Level-3 optical thickness and effective radius cloud product is a gridded l deg. x 1 deg. dataset that is derived from aggregation and subsampling at 5 km of 1 km, resolution Level-2 orbital swath data (Level-2 granules). This study examines the impact of the 5 km subsampling on the mean, standard deviation and inhomogeneity parameter statistics of optical thickness and effective radius. The methodology is simple and consists of estimating mean errors for a large collection of Terra and Aqua Level-2 granules by taking the difference of the statistics at the original and subsampled resolutions. It is shown that the Level-3 sampling does not affect the various quantities investigated to the same degree, with second order moments suffering greater subsampling errors, as expected. Mean errors drop dramatically when averages over a sufficient number of regions (e.g., monthly and/or latitudinal averages) are taken, pointing to a dominance of errors that are of random nature. When histograms built from subsampled data with the same binning rules as in the Level-3 dataset are used to reconstruct the quantities of interest, the mean errors do not deteriorate significantly. The results in this paper provide guidance to users of MODIS Level-3 optical thickness and effective radius cloud products on the range of errors due to subsampling they should expect and perhaps account for, in scientific work with this dataset. In general, subsampling errors should not be a serious concern when moderate temporal and/or spatial averaging is performed.

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM2-MODIS_Edition2A)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Single Satellite Footprint, TOA and Surface Fluxes, Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Edition2A)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-09-16] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Edition1B)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Single Satellite Footprint, TOA and Surface Fluxes, Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Ed2A-NoSW)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2006-01-01] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM2-MODIS_Edition2B)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2006-01-01] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM1-MODIS_Edition2A)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

Remote sensing of cloud, aerosol and water vapor properties from the Moderate Resolution Imaging Spectrometer (MODIS)

NASA Technical Reports Server (NTRS)

King, M. D.

1992-01-01

The Moderate Resolution Imaging Spectrometer (MODIS) is an Earth-viewing sensor being developed as a facility instrument for the Earth Observing System (EOS) to be launched in the late 1990s. MODIS consists of two separate instruments that scan a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, Sun-synchronous, platform at an altitude of 705 km. Of primary interest for studies of atmospheric physics is the MODIS-N (nadir) instrument which will provide images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resoulutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean and atmosperhic processes. The intent of this lecture is to describe the current status of MODIS-N and its companion instrument MODIS-T (tilt), a tiltable cross-track scanning radiometer with 32 uniformly spaced channels between 0.410 and 0.875 micrometers, and to describe the physical principles behind the development of MODIS for the remote sensing of atmospheric properties. Primary emphasis will be placed on the main atmospheric applications of determining the optical, microphysical and physical properties of clouds and aerosol particles form spectral-reflection and thermal-emission measurements. In addition to cloud and aerosol properties, MODIS-N will be utilized for the determination of the total precipitable water vapor over land and atmospheric stability. The physical principles behind the determination of each of these atmospheric products will be described herein.

Consistency of two global MODIS aerosol products over ocean on Terra and Aqua CERES SSF datasets

NASA Astrophysics Data System (ADS)

Ignatov, Alexander; Minnis, Patrick; Wielicki, Bruce; Loeb, Norman G.; Remer, Lorraine A.; Kaufman, Yoram J.; Miller, Walter F.; Sun-Mack, Sunny; Laszlo, Istvan; Geier, Erika B.

2004-12-01

MODIS aerosol retrievals over ocean from Terra and Aqua platforms are available from the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint (SSF) datasets generated at NASA Langley Research Center (LaRC). Two aerosol products are reported side by side. The primary M product is generated by subsetting and remapping the multi-spectral (0.44 - 2.1 μm) MOD04 aerosols onto CERES footprints. MOD04 processing uses cloud screening and aerosol algorithms developed by the MODIS science team. The secondary (AVHRR-like) A product is generated in only two MODIS bands: 1 and 6 on Terra, and ` and 7 on Aqua. The A processing uses NASA/LaRC cloud-screening and NOAA/NESDIS single channel aerosol algorthm. The M and A products have been documented elsewhere and preliminarily compared using two weeks of global Terra CERES SSF (Edition 1A) data in December 2000 and June 2001. In this study, the M and A aerosol optical depths (AOD) in MODIS band 1 and (0.64 μm), τ1M and τ1A, are further checked for cross-platform consistency using 9 days of global Terra CERES SSF (Edition 2A) and Aqua CERES SSF (Edition 1A) data from 13 - 21 October 2002.

The Impact of Different Regimes in Estimating the Effects of Aerosols on Clouds. A Case Study over the Baltic Sea Countries.

NASA Astrophysics Data System (ADS)

Saponaro, G.

2015-12-01

The present study investigates the use of long-term satellite data to assess the influence of aerosols upon cloud parameters over the Baltic Sea region. This particular area offers the contrast of a very clean environment (Fennoscandia) against a more polluted one (Germany, Poland). The datasets used in this study consist of Collection 6 Level 3 daily observations from 2002 to 2014 retrieved from observations by the NASA's Moderate-Resolution Imaging Spectrometer (MODIS) instrument on-board the Aqua platform. The MODIS aerosol optical depth (AOD) and aerosol index (AI) products are used as a proxy for the number concentration of aerosol particles while the cloud effective radius (CER) and cloud optical thickness (COT) describe cloud microphysical and optical properties respectively. Through the analysis of a 12-years dataset, distribution maps provide information on a regional scale about the first aerosol indirect effect (AIE) by determining the aerosol-cloud interaction (ACI). The ACI is defined as the change in cloud optical depth or effective radius as a function of aerosol load, for which AI is used as a proxy, for a fixed liquid water path (LWP). Reanalysis data from ECMWF, namely ERA-Interim, are used to estimate meteorological settings on a regional scale. The relative humidity (RH) and specific humidity (SH) are chosen at the pressure level of 950 hPa and they are linearly interpolated to match MODIS resolution of 1 x 1 deg. The Lower Tropospheric Stability (LTS) is computed from the ERA- Interim reanalysis data as the difference between the potential temperature at 700hPa and the surface. In order to better identify and interpret the AIE, this study proposes a framework where the interactions between aerosols and clouds are estimated by dividing the dataset into different regimes. Regimes are defined by: Liquid Water Path (LWP). The discrimination by LWP allows assessing the Twomey effect. The AIE is more evident when the LWP is lower. Aerosol loading (both AOD and AI). Separated aerosol settings (AI/AOD <25th percentile versus AI/AOD > 75th percentile) provide information regarding the saturation effect. Meteorological environments. LTS determines an unstable thermodynamic environment (LTS <25th percentile) and a stable one ( LTS >75th percentile).

Examining the NZESM Cloud representation with Self Organizing Maps

NASA Astrophysics Data System (ADS)

Schuddeboom, Alex; McDonald, Adrian; Parsons, Simon; Morgenstern, Olaf; Harvey, Mike

2017-04-01

Several different cloud regimes are identified from MODIS satellite data and the representation of these regimes within the New Zealand Earth System Model (NZESM) is examined. For the development of our cloud classification we utilize a neural network algorithm known as self organizing maps (SOMs) on MODIS cloud top pressure - cloud optical thickness joint histograms. To evaluate the representation of the cloud within NZESM, the frequency and geographical distribution of the regimes is compared between the NZESM and satellite data. This approach has the advantage of not only identifying differences, but also potentially giving additional information about the discrepancy such as in which regions or phases of cloud the differences are most prominent. To allow for a more direct comparison between datasets, the COSP satellite simulation software is applied to NZESM output. COSP works by simulating the observational processes linked to a satellite, within the GCM, so that data can be generated in a way that shares the particular observational bias of specific satellites. By taking the COSP joint histograms and comparing them to our existing classifications we can easily search for discrepancies between the observational data and the simulations without having to be cautious of biases introduced by the satellite. Preliminary results, based on data for 2008, show a significant decrease in overall cloud fraction in the NZESM compared to the MODIS satellite data. To better understand the nature of this discrepancy, the cloud fraction related to different cloud heights and phases were also analysed.

A Physically Based Algorithm for Non-Blackbody Correction of Cloud-Top Temperature and Application to Convection Study

NASA Technical Reports Server (NTRS)

Wang, Chunpeng; Lou, Zhengzhao Johnny; Chen, Xiuhong; Zeng, Xiping; Tao, Wei-Kuo; Huang, Xianglei

2014-01-01

Cloud-top temperature (CTT) is an important parameter for convective clouds and is usually different from the 11-micrometers brightness temperature due to non-blackbody effects. This paper presents an algorithm for estimating convective CTT by using simultaneous passive [Moderate Resolution Imaging Spectroradiometer (MODIS)] and active [CloudSat 1 Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)] measurements of clouds to correct for the non-blackbody effect. To do this, a weighting function of the MODIS 11-micrometers band is explicitly calculated by feeding cloud hydrometer profiles from CloudSat and CALIPSO retrievals and temperature and humidity profiles based on ECMWF analyses into a radiation transfer model.Among 16 837 tropical deep convective clouds observed by CloudSat in 2008, the averaged effective emission level (EEL) of the 11-mm channel is located at optical depth; approximately 0.72, with a standard deviation of 0.3. The distance between the EEL and cloud-top height determined by CloudSat is shown to be related to a parameter called cloud-top fuzziness (CTF), defined as the vertical separation between 230 and 10 dBZ of CloudSat radar reflectivity. On the basis of these findings a relationship is then developed between the CTF and the difference between MODIS 11-micrometers brightness temperature and physical CTT, the latter being the non-blackbody correction of CTT. Correction of the non-blackbody effect of CTT is applied to analyze convective cloud-top buoyancy. With this correction, about 70% of the convective cores observed by CloudSat in the height range of 6-10 km have positive buoyancy near cloud top, meaning clouds are still growing vertically, although their final fate cannot be determined by snapshot observations.

The MODIS Aerosol Algorithm, Products and Validation

NASA Technical Reports Server (NTRS)

Remer, L. A.; Kaufman, Y. J.; Tanre, D.; Mattoo, S.; Chu, D. A.; Martins, J. V.; Li, R.-R.; Ichoku, C.; Levy, R. C.; Kleidman, R. G.

2003-01-01

The MODerate resolution Imaging Spectroradiometer (MODIS) aboard both NASA's Terra and Aqua satellites is making near global daily observations of the earth in a wide spectral range. These measurements are used to derive spectral aerosol optical thickness and aerosol size parameters over both land and ocean. The aerosol products available over land include aerosol optical thickness at three visible wavelengths, a measure of the fraction of aerosol optical thickness attributed to the fine mode and several derived parameters including reflected spectral solar flux at top of atmosphere. Over ocean, the aerosol optical thickness is provided in seven wavelengths from 0.47 microns to 2.13 microns. In addition, quantitative aerosol size information includes effective radius of the aerosol and quantitative fraction of optical thickness attributed to the fine mode. Spectral aerosol flux, mass concentration and number of cloud condensation nuclei round out the list of available aerosol products over the ocean. The spectral optical thickness and effective radius of the aerosol over the ocean are validated by comparison with two years of AERONET data gleaned from 133 AERONET stations. 8000 MODIS aerosol retrievals colocated with AERONET measurements confirm that one-standard deviation of MODIS optical thickness retrievals fall within the predicted uncertainty of delta tauapproximately equal to plus or minus 0.03 plus or minus 0.05 tau over ocean and delta tay equal to plus or minus 0.05 plus or minus 0.15 tau over land. 271 MODIS aerosol retrievals co-located with AERONET inversions at island and coastal sites suggest that one-standard deviation of MODIS effective radius retrievals falls within delta r_eff approximately equal to 0.11 microns. The accuracy of the MODIS retrievals suggests that the product can be used to help narrow the uncertainties associated with aerosol radiative forcing of global climate.

Comparison of CERES-MODIS stratus cloud properties with ground-based measurements at the DOE ARM Southern Great Plains site

NASA Astrophysics Data System (ADS)

Dong, Xiquan; Minnis, Patrick; Xi, Baike; Sun-Mack, Sunny; Chen, Yan

2008-02-01

Overcast stratus cloud properties derived for the Clouds and the Earth's Radiant Energy System (CERES) project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains site from March 2000 through December 2004. Retrievals from ARM surface-based data were averaged over a 1-h interval centered at the time of each satellite overpass, and the CERES-MODIS cloud properties were averaged within a 30 km × 30 km box centered on the ARM SGP site. Two data sets were analyzed: all of the data (ALL), which include multilayered, single-layered, and slightly broken stratus decks and a subset, single-layered unbroken decks (SL). The CERES-MODIS effective cloud heights were determined from effective cloud temperature using a lapse rate method with the surface temperature specified as the 24-h mean surface air temperature. For SL stratus, they are, on average, within the ARM radar-lidar estimated cloud boundaries and are 0.534 ± 0.542 km and 0.108 ± 0.480 km lower than the cloud physical tops and centers, respectively, and are comparable for day and night observations. The mean differences and standard deviations are slightly larger for ALL data, but not statistically different to those of SL data. The MODIS-derived effective cloud temperatures are 2.7 ± 2.4 K less than the surface-observed SL cloud center temperatures with very high correlations (0.86-0.97). Variations in the height differences are mainly caused by uncertainties in the surface air temperatures, lapse rates, and cloud top height variability. The biases are mainly the result of the differences between effective and physical cloud top, which are governed by cloud liquid water content and viewing zenith angle, and the selected lapse rate, -7.1 K km-1. On the basis of a total of 43 samples, the means and standard deviations of the differences between the daytime Terra and surface retrievals of effective radius re, optical depth, and liquid water path for SL stratus are 0.1 ± 1.9 μm (1.2 ± 23.5%), -1.3 ± 9.5 (-3.6 ± 26.2%), and 0.6 ± 49.9 gm-2 (0.3 ± 27%), respectively, while the corresponding correlation coefficients are 0.44, 0.87, and 0.89. For Aqua, they are 0.2 ± 1.9 μm (2.5 ± 23.4%), 2.5 ± 7.8 (7.8 ± 24.3%), and 28.1 ± 52.7 gm-2 (17.2 ± 32.2%), as well as 0.35, 0.96, and 0.93 from a total of 21 cases. The results for ALL cases are comparable. Although a bias in re was expected because the satellite retrieval of effective radius only represents the top of the cloud, the surface-based radar retrievals revealed that the vertical profile of re is highly variable with smaller droplets occurring at cloud top in some cases. The larger bias in optical depth and liquid water path for Aqua is due, at least partially, to differences in the Terra and Aqua MODIS visible channel calibrations. Methods for improving the cloud top height and microphysical property retrievals are suggested.

Comparison of CERES-MODIS Stratus Cloud Properties with Ground-Based Measurements at the DOE ARM Southern Great Plains Site

NASA Technical Reports Server (NTRS)

Dong, Xiquan; Minnis Patrick; Xi, Baike; Sun-Mack, Sunny; Chen, Yan

2008-01-01

Overcast stratus cloud properties derived for the Clouds and the Earth's Radiant Energy system (CERES) Project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site from March 2000 through December 2004. Retrievals from ARM surface-based data were averaged over a 1-hour interval centered at the time of each satellite overpass, and the CERES-MODIS cloud properties were averaged within a 30-km x 30 km box centered on the ARM SGP site. Two datasets were analyzed: all of the data (ALL) which include multilayered, single-layered, and slightly broken stratus decks and a subset, single-layered unbroken decks (SL). The CERES-MODIS effective cloud heights were determined from effective cloud temperature using a lapse rate method with the surface temperature specified as the 24-h mean surface air temperature. For SL stratus, they are, on average, within the ARM radar-lidar estimated cloud boundaries and are 0.534 +/- 0.542 km and 0.108 +/- 0.480 km lower than the cloud physical tops and centers, respectively, and are comparable for day and night observations. The mean differences and standard deviations are slightly larger for ALL data, but not statistically different to those of SL data. The MODIS-derived effective cloud temperatures are 2.7 +/- 2.4 K less than the surface-observed SL cloud center temperatures with very high correlations (0.86-0.97). Variations in the height differences are mainly caused by uncertainties in the surface air temperatures, lapse rates, and cloud-top height variability. The biases are mainly the result of the differences between effective and physical cloud top, which are governed by cloud liquid water content and viewing zenith angle, and the selected lapse rate, -7.1 K km(exp -1). Based on a total of 43 samples, the means and standard deviations of the differences between the daytime Terra and surface retrievals of effective radius r(sub e), optical depth, and liquid water path for SL stratu are 0.1 +/- 1.9 micrometers (1.2 +/- 23.5%), -1.3 +/- 9.5 (-3.6 +/-26.2%), and 0.6 +/- 49.9 gm (exp -2) (0.3 +/- 27%), respectively, while the corresponding correlation coefficients are 0.44, 0.87, and 0.89. For Aqua, they are 0.2 +/- 1.9 micrometers (2.5 +/- 23.4%), 2.5 +/- 7.8 (7.8 +/- 24.3%), and 28.1 +/- 52.7 gm (exp -2) (17.2 +/- 32.2%), as well as 0.35, 0.96, and 0.93 from a total of 21 cases. The results for ALL cases are comparable. Although a bias in R(sub e) was expected because the satellite retrieval of effective radius only represents the top of the cloud, the surface-based radar retrievals revealed that the vertical profile of r(sub e) is highly variable with smaller droplets occurring at cloud top in some cases. The larger bias in optical depth and liquid water path for Aqua is due, at least partially, to differences in the Terra and Aqua MODIS visible channel calibrations. methods for improving the cloud-top height and microphysical property retrievals are suggested.

Consistency of Global Modis Aerosol Optical Depths over Ocean on Terra and Aqua Ceres SSF Datasets

NASA Technical Reports Server (NTRS)

Ignatov, Alexander; Minnis, Patrick; Miller, Walter F.; Wielicki, Bruce A.; Remer, Lorraine

2006-01-01

Aerosol retrievals over ocean from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua platforms are available from the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint (SSF) datasets generated at NASA Langley Research Center (LaRC). Two aerosol products are reported side-by-side. The primary M product is generated by sub-setting and remapping the multi-spectral (0.47-2.1 micrometer) MODIS produced oceanic aerosol (MOD04/MYD04 for Terra/Aqua) onto CERES footprints. M*D04 processing uses cloud screening and aerosol algorithms developed by the MODIS science team. The secondary AVHRR-like A product is generated in only two MODIS bands 1 and 6 (on Aqua, bands 1 and 7). The A processing uses the CERES cloud screening algorithm, and NOAA/NESDIS glint identification, and single-channel aerosol retrieval algorithms. The M and A products have been documented elsewhere and preliminarily compared using 2 weeks of global Terra CERES SSF Edition 1A data in which the M product was based on MOD04 collection 3. In this study, the comparisons between the M and A aerosol optical depths (AOD) in MODIS band 1 (0.64 micrometers), tau(sub 1M) and tau(sub 1A) are re-examined using 9 days of global CERES SSF Terra Edition 2A and Aqua Edition 1B data from 13 - 21 October 2002, and extended to include cross-platform comparisons. The M and A products on the new CERES SSF release are generated using the same aerosol algorithms as before, but with different preprocessing and sampling procedures, lending themselves to a simple sensitivity check to non-aerosol factors. Both tau(sub 1M) and tau(sub 1A) generally compare well across platforms. However, the M product shows some differences, which increase with ambient cloud amount and towards the solar side of the orbit. Three types of comparisons conducted in this study - cross-platform, cross-product, and cross-release confirm the previously made observation that the major area for improvement in the current aerosol processing lies in a more formalized and standardized sampling (and most importantly, cloud screening) whereas optimization of the aerosol algorithm is deemed to be an important yet less critical element.

Detection of single and multilayer clouds in an artificial neural network approach

NASA Astrophysics Data System (ADS)

Sun-Mack, Sunny; Minnis, Patrick; Smith, William L.; Hong, Gang; Chen, Yan

2017-10-01

Determining whether a scene observed with a satellite imager is composed of a thin cirrus over a water cloud or thick cirrus contiguous with underlying layers of ice and water clouds is often difficult because of similarities in the observed radiance values. In this paper an artificial neural network (ANN) algorithm, employing several Aqua MODIS infrared channels and the retrieved total cloud visible optical depth, is trained to detect multilayer ice-over-water cloud systems as identified by matched April 2009 CloudSat and CALIPSO (CC) data. The CC lidar and radar profiles provide the vertical structure that serves as output truth for a multilayer ANN, or MLANN, algorithm. Applying the trained MLANN to independent July 2008 MODIS data resulted in a combined ML and single layer hit rate of 75% (72%) for nonpolar regions during the day (night). The results are comparable to or more accurate than currently available methods. Areas of improvement are identified and will be addressed in future versions of the MLANN.

An imager-based multispectral retrieval of above-cloud absorbing aerosol optical depth and the optical and microphysical properties of underlying marine stratocumulus clouds

NASA Astrophysics Data System (ADS)

Meyer, K.; Platnick, S. E.; Zhang, Z.

2014-12-01

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer (MBL) clouds over the southeastern Atlantic Ocean, which underlie a near-persistent smoke layer produced from extensive biomass burning throughout the southern African savanna during austral winter. The absorption of the above-cloud smoke layer, which increases with decreasing wavelength, can introduce biases into imager-based cloud optical and microphysical property retrievals of the underlying MBL clouds. This effect is more pronounced for cloud optical thickness retrievals, which are typically derived from the visible or near-IR wavelength channels (effective particle size retrievals are derived from short and mid-wave IR channels that are less affected by aerosol absorption). Here, a new method is introduced to simultaneously retrieve the above-cloud smoke aerosol optical depth (AOD) and the unbiased cloud optical thickness (COT) and effective radius (CER) using multiple spectral channels in the visible and near- and shortwave-IR. The technique has been applied to MODIS, and retrieval results and statistics, as well as comparisons with other A-Train sensors, are shown.

Retrieval of mass and sizes of particles in sandstorms using two MODIS IR bands: A case study of April 7, 2001 sandstorm in China

NASA Astrophysics Data System (ADS)

Gu, Yingxin; Rose, William I.; Bluth, Gregg J. S.

2003-08-01

A thermal infrared remote sensing retrieval method developed by Wen and Rose [1994], which retrieves particle sizes, optical depth, and total masses of silicate particles in the volcanic cloud, was applied to an April 07, 2001 sandstorm over northern China, using MODIS. Results indicate that the area of the dust cloud observed was 1.34 million km2, the mean particle radius of the dust was 1.44 μm, and the mean optical depth at 11 μm was 0.79. The mean burden of dust was approximately 4.8 tons/km2 and the main portion of the dust storm on April 07, 2001 contained 6.5 million tons of dust. The results are supported by both independent remote sensing data (TOMS) and in situ data for a similar event in 1998. This paper demonstrates that Wen and Rose's retrieval method could be successfully applied to past and future sandstorm events using IR channels of AVHRR, GOES or MODIS.

Synergistic use of MODIS cloud products and AIRS radiance measurements for retrieval of cloud parameters

NASA Astrophysics Data System (ADS)

Li, J.; Menzel, W.; Sun, F.; Schmit, T.

2003-12-01

The Moderate-Resolution Imaging Spectroradiometer (MODIS) and Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS) Aqua satellite will enable global monitoring of the distribution of clouds. MODIS is able to provide at high spatial resolution (1 ~ 5km) the cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), and cloud water path (CWP). AIRS is able to provide CTP, ECA, CPS, and CWP within the AIRS footprint with much better accuracy using its greatly enhanced hyperspectral remote sensing capability. The combined MODIS / AIRS system offers the opportunity for cloud products improved over those possible from either system alone. The algorithm developed was applied to process the AIRS longwave cloudy radiance measurements; results are compared with MODIS cloud products, as well as with the Geostationary Operational Environmental Satellite (GOES) sounder cloud products, to demonstrate the advantage of synergistic use of high spatial resolution MODIS cloud products and high spectral resolution AIRS sounder radiance measurements for optimal cloud retrieval. Data from ground-based instrumentation at the Atmospheric Radiation Measurement (ARM) Program Cloud and Radiation Test Bed (CART) in Oklahoma were used for the validation; results show that AIRS improves the MODIS cloud products in certain cases such as low-level clouds.

Estimates of the aerosol indirect effect over the Baltic Sea region derived from 12 years of MODIS observations

NASA Astrophysics Data System (ADS)

Saponaro, Giulia; Kolmonen, Pekka; Sogacheva, Larisa; Rodriguez, Edith; Virtanen, Timo; de Leeuw, Gerrit

2017-02-01

Retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the Aqua satellite, 12 years (2003-2014) of aerosol and cloud properties were used to statistically quantify aerosol-cloud interaction (ACI) over the Baltic Sea region, including the relatively clean Fennoscandia and the more polluted central-eastern Europe. These areas allowed us to study the effects of different aerosol types and concentrations on macro- and microphysical properties of clouds: cloud effective radius (CER), cloud fraction (CF), cloud optical thickness (COT), cloud liquid water path (LWP) and cloud-top height (CTH). Aerosol properties used are aerosol optical depth (AOD), Ångström exponent (AE) and aerosol index (AI). The study was limited to low-level water clouds in the summer. The vertical distributions of the relationships between cloud properties and aerosols show an effect of aerosols on low-level water clouds. CF, COT, LWP and CTH tend to increase with aerosol loading, indicating changes in the cloud structure, while the effective radius of cloud droplets decreases. The ACI is larger at relatively low cloud-top levels, between 900 and 700 hPa. Most of the studied cloud variables were unaffected by the lower-tropospheric stability (LTS), except for the cloud fraction. The spatial distribution of aerosol and cloud parameters and ACI, here defined as the change in CER as a function of aerosol concentration for a fixed LWP, shows positive and statistically significant ACI over the Baltic Sea and Fennoscandia, with the former having the largest values. Small negative ACI values are observed in central-eastern Europe, suggesting that large aerosol concentrations saturate the ACI.

The Apparent Bluing of Aerosols Near Clouds

NASA Technical Reports Server (NTRS)

Marshak, Alexander

2008-01-01

Numerous studies based on satellite observations have reported that aerosol optical depths increase with increasing cloud cover. Part of the increase comes from the humidification and consequent growth of aerosol particles in the moist cloud environment, but part comes from 3D cloud-radiative transfer effects on the retrieved aerosol properties. Often, discerning whether the observed increases in aerosol optical depths are artifacts or real proves difficult. I describe a simple model that quantifies the enhanced illumination of cloud-free columns in the vicinity of clouds that are used in the aerosol retrievals. This model is based on the assumption that the enhancement in the cloud-free column radiance comes from enhanced Rayleigh scattering that results from the presence of the nearby clouds. This assumption leads to a larger increase of AOT for shorter wavelengths, or to a "bluing" of aerosols near clouds. Examples from the MODIS observations that illustrate the apparent bluing of aerosols near clouds will be discussed.

Statistics Analysis of the Uncertainties in Cloud Optical Depth Retrievals Caused by Three-Dimensional Radiative Effects

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Marshak, Alexander

2000-01-01

This paper presents a simple approach to estimate the uncertainties that arise in satellite retrievals of cloud optical depth when the retrievals use one-dimensional radiative transfer theory for heterogeneous clouds that have variations in all three dimensions. For the first time, preliminary error bounds are set to estimate the uncertainty of cloud optical depth retrievals. These estimates can help us better understand the nature of uncertainties that three-dimensional effects can introduce into retrievals of this important product of the MODIS instrument. The probability distribution of resulting retrieval errors is examined through theoretical simulations of shortwave cloud reflection for a wide variety of cloud fields. The results are used to illustrate how retrieval uncertainties change with observable and known parameters, such as solar elevation or cloud brightness. Furthermore, the results indicate that a tendency observed in an earlier study, clouds appearing thicker for oblique sun, is indeed caused by three-dimensional radiative effects.

Spatially Varying Spectrally Thresholds for MODIS Cloud Detection

NASA Technical Reports Server (NTRS)

Haines, S. L.; Jedlovec, G. J.; Lafontaine, F.

2004-01-01

The EOS science team has developed an elaborate global MODIS cloud detection procedure, and the resulting MODIS product (MOD35) is used in the retrieval process of several geophysical parameters to mask out clouds. While the global application of the cloud detection approach appears quite robust, the product has some shortcomings on the regional scale, often over determining clouds in a variety of settings, particularly at night. This over-determination of clouds can cause a reduction in the spatial coverage of MODIS derived clear-sky products. To minimize this problem, a new regional cloud detection method for use with MODIS data has been developed at NASA's Global Hydrology and Climate Center (GHCC). The approach is similar to that used by the GHCC for GOES data over the continental United States. Several spatially varying thresholds are applied to MODIS spectral data to produce a set of tests for detecting clouds. The thresholds are valid for each MODIS orbital pass, and are derived from 20-day composites of GOES channels with similar wavelengths to MODIS. This paper and accompanying poster will introduce the GHCC MODIS cloud mask, provide some examples, and present some preliminary validation.

Near-Cloud Aerosol Properties from the 1 Km Resolution MODIS Ocean Product

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Marshak, Alexander

2014-01-01

This study examines aerosol properties in the vicinity of clouds by analyzing high-resolution atmospheric correction parameters provided in the MODIS (Moderate Resolution Imaging Spectroradiometer) ocean color product. The study analyzes data from a 2 week long period of September in 10 years, covering a large area in the northeast Atlantic Ocean. The results indicate that on the one hand, the Quality Assessment (QA) flags of the ocean color product successfully eliminate cloud-related uncertainties in ocean parameters such as chlorophyll content, but on the other hand, using the flags introduces a sampling bias in atmospheric products such as aerosol optical thickness (AOT) and Angstrom exponent. Therefore, researchers need to select QA flags by balancing the risks of increased retrieval uncertainties and sampling biases. Using an optimal set of QA flags, the results reveal substantial increases in optical thickness near clouds-on average the increase is 50% for the roughly half of pixels within 5 km from clouds and is accompanied by a roughly matching increase in particle size. Theoretical simulations show that the 50% increase in 550nm AOT changes instantaneous direct aerosol radiative forcing by up to 8W/m2 and that the radiative impact is significantly larger if observed near-cloud changes are attributed to aerosol particles as opposed to undetected cloud particles. These results underline that accounting for near-cloud areas and understanding the causes of near-cloud particle changes are critical for accurate calculations of direct aerosol radiative forcing.

Improved Thin Cirrus and Terminator Cloud Detection in CERES Cloud Mask

NASA Technical Reports Server (NTRS)

Trepte, Qing; Minnis, Patrick; Palikonda, Rabindra; Spangenberg, Doug; Haeffelin, Martial

2006-01-01

Thin cirrus clouds account for about 20-30% of the total cloud coverage and affect the global radiation budget by increasing the Earth's albedo and reducing infrared emissions. Thin cirrus, however, are often underestimated by traditional satellite cloud detection algorithms. This difficulty is caused by the lack of spectral contrast between optically thin cirrus and the surface in techniques that use visible (0.65 micron ) and infrared (11 micron ) channels. In the Clouds and the Earth s Radiant Energy System (CERES) Aqua Edition 1 (AEd1) and Terra Edition 3 (TEd3) Cloud Masks, thin cirrus detection is significantly improved over both land and ocean using a technique that combines MODIS high-resolution measurements from the 1.38 and 11 micron channels and brightness temperature differences (BTDs) of 11-12, 8.5-11, and 3.7-11 micron channels. To account for humidity and view angle dependencies, empirical relationships were derived with observations from the 1.38 micron reflectance and the 11-12 and 8.5-11 micron BTDs using 70 granules of MODIS data in 2002 and 2003. Another challenge in global cloud detection algorithms occurs near the day/night terminator where information from the visible 0.65 micron channel and the estimated solar component of 3.7 micron channel becomes less reliable. As a result, clouds are often underestimated or misidentified near the terminator over land and ocean. Comparisons between the CLAVR-x (Clouds from Advanced Very High Resolution Radiometer [AVHRR]) cloud coverage and Geoscience Laser Altimeter System (GLAS) measurements north of 60 N indicate significant amounts of missing clouds from CLAVR-x because this part of the world was near the day/night terminator viewed by AVHRR. Comparisons between MODIS cloud products (MOD06) and GLAS in the same region also show similar difficulties with MODIS cloud retrievals. The consistent detection of clouds through out the day is needed to provide reliable cloud and radiation products for CERES and other research efforts involving the modeling of clouds and their interaction with the radiation budget.

3D Cloud Radiative Effects on Aerosol Optical Thickness Retrievals in Cumulus Cloud Fields in the Biomass Burning Region in Brazil

NASA Technical Reports Server (NTRS)

Wen, Guo-Yong; Marshak, Alexander; Cahalan, Robert F.

2004-01-01

Aerosol amount in clear regions of a cloudy atmosphere is a critical parameter in studying the interaction between aerosols and clouds. Since the global cloud cover is about 50%, cloudy scenes are often encountered in any satellite images. Aerosols are more or less transparent, while clouds are extremely reflective in the visible spectrum of solar radiation. The radiative transfer in clear-cloudy condition is highly three- dimensional (3D). This paper focuses on estimating the 3D effects on aerosol optical thickness retrievals using Monte Carlo simulations. An ASTER image of cumulus cloud fields in the biomass burning region in Brazil is simulated in this study. The MODIS products (i-e., cloud optical thickness, particle effective radius, cloud top pressure, surface reflectance, etc.) are used to construct the cloud property and surface reflectance fields. To estimate the cloud 3-D effects, we assume a plane-parallel stratification of aerosol properties in the 60 km x 60 km ASTER image. The simulated solar radiation at the top of the atmosphere is compared with plane-parallel calculations. Furthermore, the 3D cloud radiative effects on aerosol optical thickness retrieval are estimated.

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF)- Test data in HDF (CER_SSF_TRMM-PFM-VIRS_Subset-Edition1)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=1998-08-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_TRMM-PFM-VIRS_Edition1)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

Assessment of 3D cloud radiative transfer effects applied to collocated A-Train data

NASA Astrophysics Data System (ADS)

Okata, M.; Nakajima, T.; Suzuki, K.; Toshiro, I.; Nakajima, T. Y.; Okamoto, H.

2017-12-01

This study investigates broadband radiative fluxes in the 3D cloud-laden atmospheres using a 3D radiative transfer (RT) model, MCstar, and the collocated A-Train cloud data. The 3D extinction coefficients are constructed by a newly devised Minimum cloud Information Deviation Profiling Method (MIDPM) that extrapolates CPR radar profiles at nadir into off-nadir regions within MODIS swath based on collocated information of MODIS-derived cloud properties and radar reflectivity profiles. The method is applied to low level maritime water clouds, for which the 3D-RT simulations are performed. The radiative fluxes thus simulated are compared to those obtained from CERES as a way to validate the MIDPM-constructed clouds and our 3D-RT simulations. The results show that the simulated SW flux agrees with CERES values within 8 - 50 Wm-2. One of the large biases occurred by cyclic boundary condition that was required to pose into our computational domain limited to 20km by 20km with 1km resolution. Another source of the bias also arises from the 1D assumption for cloud property retrievals particularly for thin clouds, which tend to be affected by spatial heterogeneity leading to overestimate of the cloud optical thickness. These 3D-RT simulations also serve to address another objective of this study, i.e. to characterize the "observed" specific 3D-RT effects by the cloud morphology. We extend the computational domain to 100km by 100km for this purpose. The 3D-RT effects are characterized by errors of existing 1D approximations to 3D radiation field. The errors are investigated in terms of their dependence on solar zenith angle (SZA) for the satellite-constructed real cloud cases, and we define two indices from the error tendencies. According to the indices, the 3D-RT effects are classified into three types which correspond to different simple three morphologies types, i.e. isolated cloud type, upper cloud-roughened type and lower cloud-roughened type. These 3D-RT effects linked to cloud morphologies are also visualized in the form of the RGB composite maps constructed from MODIS/Aqua three channels, which show cloud optical thickness and cloud height information. Such a classification offers a novel insight into 3D-RT effect in a manner that directly relates to cloud morphology.

Virtual Sensors: Using Data Mining to Efficiently Estimate Spectra

NASA Technical Reports Server (NTRS)

Srivastava, Ashok; Oza, Nikunj; Stroeve, Julienne

2004-01-01

Detecting clouds within a satellite image is essential for retrieving surface geophysical parameters, such as albedo and temperature, from optical and thermal imagery because the retrieval methods tend to be valid for clear skies only. Thus, routine satellite data processing requires reliable automated cloud detection algorithms that are applicable to many surface types. Unfortunately, cloud detection over snow and ice is difficult due to the lack of spectral contrast between clouds and snow. Snow and clouds are both highly reflective in the visible wavelen,ats and often show little contrast in the thermal Infrared. However, at 1.6 microns, the spectral signatures of snow and clouds differ enough to allow improved snow/ice/cloud discrimination. The recent Terra and Aqua Moderate Resolution Imaging Spectro-Radiometer (MODIS) sensors have a channel (channel 6) at 1.6 microns. Presently the most comprehensive, long-term information on surface albedo and temperature over snow- and ice-covered surfaces comes from the Advanced Very High Resolution Radiometer ( AVHRR) sensor that has been providing imagery since July 1981. The earlier AVHRR sensors (e.g. AVHRR/2) did not however have a channel designed for discriminating clouds from snow, such as the 1.6 micron channel available on the more recent AVHRR/3 or the MODIS sensors. In the absence of the 1.6 micron channel, the AVHRR Polar Pathfinder (APP) product performs cloud detection using a combination of time-series analysis and multispectral threshold tests based on the satellite's measuring channels to produce a cloud mask. The method has been found to work reasonably well over sea ice, but not so well over the ice sheets. Thus, improving the cloud mask in the APP dataset would be extremely helpful toward increasing the accuracy of the albedo and temperature retrievals, as well as extending the time-series of albedo and temperature retrievals from the more recent sensors to the historical ones. In this work, we use data mining methods to construct a model of MODIS channel 6 as a function of other channels that are common to both MODIS and AVHRR. The idea is to use the model to generate the equivalent of MODIS channel 6 for AVHRR as a function of the AVHRR equivalents to MODIS channels. We call this a Virtual Sensor because it predicts unmeasured spectra. The goal is to use this virtual channel 6. to yield a cloud mask superior to what is currently used in APP . Our results show that several data mining methods such as multilayer perceptrons (MLPs), ensemble methods (e.g., bagging), and kernel methods (e.g., support vector machines) generate channel 6 for unseen MODIS images with high accuracy. Because the true channel 6 is not available for AVHRR images, we qualitatively assess the virtual channel 6 for several AVHRR images.

A browser-based 3D Visualization Tool designed for comparing CERES/CALIOP/CloudSAT level-2 data sets.

NASA Astrophysics Data System (ADS)

Chu, C.; Sun-Mack, S.; Chen, Y.; Heckert, E.; Doelling, D. R.

2017-12-01

In Langley NASA, Clouds and the Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) are merged with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat Cloud Profiling Radar (CPR). The CERES merged product (C3M) matches up to three CALIPSO footprints with each MODIS pixel along its ground track. It then assigns the nearest CloudSat footprint to each of those MODIS pixels. The cloud properties from MODIS, retrieved using the CERES algorithms, are included in C3M with the matched CALIPSO and CloudSat products along with radiances from 18 MODIS channels. The dataset is used to validate the CERES retrieved MODIS cloud properties and the computed TOA and surface flux difference using MODIS or CALIOP/CloudSAT retrieved clouds. This information is then used to tune the computed fluxes to match the CERES observed TOA flux. A visualization tool will be invaluable to determine the cause of these large cloud and flux differences in order to improve the methodology. This effort is part of larger effort to allow users to order the CERES C3M product sub-setted by time and parameter as well as the previously mentioned visualization capabilities. This presentation will show a new graphical 3D-interface, 3D-CERESVis, that allows users to view both passive remote sensing satellites (MODIS and CERES) and active satellites (CALIPSO and CloudSat), such that the detailed vertical structures of cloud properties from CALIPSO and CloudSat are displayed side by side with horizontally retrieved cloud properties from MODIS and CERES. Similarly, the CERES computed profile fluxes whether using MODIS or CALIPSO and CloudSat clouds can also be compared. 3D-CERESVis is a browser-based visualization tool that makes uses of techniques such as multiple synchronized cursors, COLLADA format data and Cesium.

Toward Unified Satellite Climatology of Aerosol Properties. 3. MODIS Versus MISR Versus AERONET

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Liu, Li; Geogdzhayev, Igor V.; Travis, Larry D.; Cairns, Brian; Lacis, Andrew A.

2010-01-01

We use the full duration of collocated pixel-level MODIS-Terra and MISR aerosol optical thickness (AOT) retrievals and level 2 cloud-screened quality-assured AERONET measurements to evaluate the likely individual MODIS and MISR retrieval accuracies globally over oceans and land. We show that the use of quality-assured MODIS AOTs as opposed to the use of all MODIS AOTs has little effect on the resulting accuracy. The MODIS and MISR relative standard deviations (RSTDs) with respect to AERONET are remarkably stable over the entire measurement record and reveal nearly identical overall AOT performances of MODIS and MISR over the entire suite of AERONET sites. This result is used to evaluate the likely pixel-level MODIS and MISR performances on the global basis with respect to the (unknown) actual AOTs. For this purpose, we use only fully compatible MISR and MODIS aerosol pixels. We conclude that the likely RSTDs for this subset of MODIS and MISR AOTs are 73% over land and 30% over oceans. The average RSTDs for the combined [AOT(MODIS)+AOT(MISR)]/2 pixel-level product are close to 66% and 27%, respectively, which allows us to recommend this simple blend as a better alternative to the original MODIS and MISR data. These accuracy estimates still do not represent the totality of MISR and quality-assured MODIS pixel-level AOTs since an unaccounted for and potentially significant source of errors is imperfect cloud screening. Furthermore, many collocated pixels for which one of the datasets reports a retrieval, whereas the other one does not may also be problematic.

Uncertainty of Passive Imager Cloud Optical Property Retrievals to Instrument Radiometry and Model Assumptions: Examples from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; Wind, Galina; Meyer, Kerry; Amarasinghe, Nandana; Arnold, G. Thomas; Zhang, Zhibo; King, Michael D.

2013-01-01

The optical and microphysical structure of clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS on the NASA EOS Terra and Aqua platforms, simultaneous global-daily 1 km retrievals of cloud optical thickness (COT) and effective particle radius (CER) are provided, as well as the derived water path (WP). The cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate retrieval datasets for various two-channel retrievals, typically a VISNIR channel paired with a 1.6, 2.1, and 3.7 m spectral channel. The MOD06 forward model is derived from on a homogeneous plane-parallel cloud. In Collection 5 processing (completed in 2007 with a modified Collection 5.1 completed in 2010), pixel-level retrieval uncertainties were calculated for the following non-3-D error sources: radiometry, surface spectral albedo, and atmospheric corrections associated with model analysis uncertainties (water vapor only). The latter error source includes error correlation across the retrieval spectral channels. Estimates of uncertainty in 1 aggregated (Level-3) means were also provided assuming unity correlation between error sources for all pixels in a grid for a single day, and zero correlation of error sources from one day to the next. I n Collection 6 (expected to begin in late summer 2013) we expanded the uncertainty analysis to include: (a) scene-dependent calibration uncertainty that depends on new band and detector-specific Level 1B uncertainties, (b) new model error sources derived from the look-up tables which includes sensitivities associated with wind direction over the ocean and uncertainties in liquid water and ice effective variance, (c) thermal emission uncertainties in the 3.7 m band associated with cloud and surface temperatures that are needed to extract reflected solar radiation from the total radiance signal, (d) uncertainty in the solar spectral irradiance at 3.7 m, and (e) addition of stratospheric ozone uncertainty in visible atmospheric corrections. A summary of the approach and example Collection 6 results will be shown.

Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 2: Sensitivity tests and results

PubMed Central

Norris, Peter M.; da Silva, Arlindo M.

2018-01-01

Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational–Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state. PMID:29618848

Monte Carlo Bayesian Inference on a Statistical Model of Sub-Gridcolumn Moisture Variability Using High-Resolution Cloud Observations. Part 2: Sensitivity Tests and Results

NASA Technical Reports Server (NTRS)

Norris, Peter M.; da Silva, Arlindo M.

2016-01-01

Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational-Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state.

Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 2: Sensitivity tests and results.

PubMed

Norris, Peter M; da Silva, Arlindo M

2016-07-01

Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational-Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state.

Assessment and validation of the community radiative transfer model for ice cloud conditions

NASA Astrophysics Data System (ADS)

Yi, Bingqi; Yang, Ping; Weng, Fuzhong; Liu, Quanhua

2014-11-01

The performance of the Community Radiative Transfer Model (CRTM) under ice cloud conditions is evaluated and improved with the implementation of MODIS collection 6 ice cloud optical property model based on the use of severely roughened solid column aggregates and a modified Gamma particle size distribution. New ice cloud bulk scattering properties (namely, the extinction efficiency, single-scattering albedo, asymmetry factor, and scattering phase function) suitable for application to the CRTM are calculated by using the most up-to-date ice particle optical property library. CRTM-based simulations illustrate reasonable accuracy in comparison with the counterparts derived from a combination of the Discrete Ordinate Radiative Transfer (DISORT) model and the Line-by-line Radiative Transfer Model (LBLRTM). Furthermore, simulations of the top of the atmosphere brightness temperature with CRTM for the Crosstrack Infrared Sounder (CrIS) are carried out to further evaluate the updated CRTM ice cloud optical property look-up table.

Cloudy Sounding and Cloud-Top Height Retrieval From AIRS Alone Single Field-of-View Radiance Measurements

NASA Technical Reports Server (NTRS)

Weisz, Elisabeth; Li, Jun; Li, Jinlong; Zhou, Daniel K.; Huang, Hung-Lung; Goldberg, Mitchell D.; Yang, Ping

2007-01-01

High-spectral resolution measurements from the Atmospheric Infrared Sounder (AIRS) onboard the EOS (Earth Observing System) Aqua satellite provide unique information about atmospheric state, surface and cloud properties. This paper presents an AIRS alone single field-of-view (SFOV) retrieval algorithm to simultaneously retrieve temperature, humidity and ozone profiles under all weather conditions, as well as cloud top pressure (CTP) and cloud optical thickness (COT) under cloudy skies. For optically thick cloud conditions the above-cloud soundings are derived, whereas for clear skies and optically thin cloud conditions the profiles are retrieved from 0.005 hPa down to the earth's surface. Initial validation has been conducted by using the operational MODIS (Moderate Resolution Imaging Spectroradiometer) product, ECMWF (European Center of Medium range Weather Forecasts) analysis fields and radiosonde observations (RAOBs). These inter-comparisons clearly demonstrate the potential of this algorithm to process data from 38 high-spectral infrared (IR) sounder instruments.

Measurement Comparisons Towards Improving the Understanding of Aerosol-Cloud Processing

NASA Astrophysics Data System (ADS)

Noble, Stephen R.

Cloud processing of aerosol is an aerosol-cloud interaction that is not heavily researched but could have implications on climate. The three types of cloud processing are chemical processing, collision and coalescence processing, and Brownian capture of interstitial particles. All types improve cloud condensation nuclei (CCN) in size or hygroscopicity (kappa). These improved CCN affect subsequent clouds. This dissertation focuses on measurement comparisons to improve our observations and understanding of aerosol-cloud processing. Particle size distributions measured at the continental Southern Great Plains (SGP) site were compared with ground based measurements of cloud fraction (CF) and cloud base altitude (CBA). Particle size distributions were described by a new objective shape parameter to define bimodality rather than an old subjective one. Cloudy conditions at SGP were found to be correlated with lagged shape parameter. Horizontal wind speed and regional CF explained 42%+ of this lag time. Many of these surface particle size distributions were influenced by aerosol-cloud processing. Thus, cloud processing may be more widespread with more implications than previously thought. Particle size distributions measured during two aircraft field campaigns (MArine Stratus/stratocumulus Experiment; MASE; and Ice in Cloud Experiment-Tropical; ICE-T) were compared to CCN distributions. Tuning particle size to critical supersaturation revealed hygroscopicity expressed as ? when the distributions were overlain. Distributions near cumulus clouds (ICE-T) had a higher frequency of the same ?s (48% in ICE-T to 42% in MASE) between the accumulation (processed) and Aitken (unprocessed) modes. This suggested physical processing domination in ICE-T. More MASE (stratus cloud) kappa differences between modes pointed to chemical cloud processing. Chemistry measurements made in MASE showed increases in sulfates and nitrates with distributions that were more processed. This supported chemical cloud processing in MASE. This new method to determine kappa provides the needed information without interrupting ambient measurements. MODIS derived cloud optical thickness (COT), cloud liquid water path (LWP), and cloud effective radius (re) were compared to the same in situ derived variables from cloud probe measurements of two stratus/stratocumulus cloud campaigns (MASE and Physics Of Stratocumulus Tops; POST). In situ data were from complete vertical cloud penetrations, while MODIS data were from pixels along the aircraft penetration path. Comparisons were well correlated except that MODIS LWP (14-36%) and re (20-30%) were biased high. The LWP bias was from re bias and was not improved by using the vertically stratified assumption. MODIS re bias was almost removed when compared to cloud top maximum in situ re, but, that does not describe re for the full depth of the cloud. COT is validated by in situ COT. High correlations suggest that MODIS variables are useful in self-comparisons such as gradient changes in stratus cloud re during aerosol-cloud processing.

Quantifying the Climate-Scale Accuracy of Satellite Cloud Retrievals

NASA Astrophysics Data System (ADS)

Roberts, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Liang, L.; Di Girolamo, L.

2014-12-01

Instrument calibration and cloud retrieval algorithms have been developed to minimize retrieval errors on small scales. However, measurement uncertainties and assumptions within retrieval algorithms at the pixel level may alias into decadal-scale trends of cloud properties. We first, therefore, quantify how instrument calibration changes could alias into cloud property trends. For a perfect observing system the climate trend accuracy is limited only by the natural variability of the climate variable. Alternatively, for an actual observing system, the climate trend accuracy is additionally limited by the measurement uncertainty. Drifts in calibration over time may therefore be disguised as a true climate trend. We impose absolute calibration changes to MODIS spectral reflectance used as input to the CERES Cloud Property Retrieval System (CPRS) and run the modified MODIS reflectance through the CPRS to determine the sensitivity of cloud properties to calibration changes. We then use these changes to determine the impact of instrument calibration changes on trend uncertainty in reflected solar cloud properties. Secondly, we quantify how much cloud retrieval algorithm assumptions alias into cloud optical retrieval trends by starting with the largest of these biases: the plane-parallel assumption in cloud optical thickness (τC) retrievals. First, we collect liquid water cloud fields obtained from Multi-angle Imaging Spectroradiometer (MISR) measurements to construct realistic probability distribution functions (PDFs) of 3D cloud anisotropy (a measure of the degree to which clouds depart from plane-parallel) for different ISCCP cloud types. Next, we will conduct a theoretical study with dynamically simulated cloud fields and a 3D radiative transfer model to determine the relationship between 3D cloud anisotropy and 3D τC bias for each cloud type. Combining these results provides distributions of 3D τC bias by cloud type. Finally, we will estimate the change in frequency of occurrence of cloud types between two decades and will have the information needed to calculate the total change in 3D optical thickness bias between two decades. If we uncover aliases in this study, the results will motivate the development and rigorous testing of climate specific cloud retrieval algorithms.

What is the Uncertainty in MODIS Aerosol Optical Depth in the Vicinity of Clouds?

NASA Technical Reports Server (NTRS)

Patadia, Falguni; Levy, Rob; Mattoo, Shana

2017-01-01

MODIS dark-target (DT) algorithm retrieves aerosol optical depth (AOD) using a Look Up Table (LUT) approach. Global comparison of AOD (Collection 6 ) with ground-based sun photometer gives an Estimated Error (EE) of +/-(0.04 + 10%) over ocean. However, EE does not represent per-retrieval uncertainty. For retrievals that are biased high compared to AERONET, here we aim to closely examine the contribution of biases due to presence of clouds and per-pixel retrieval uncertainty. We have characterized AOD uncertainty at 550 nm, due to standard deviation of reflectance in 10 km retrieval region, uncertainty related to gas (H2O, O3) absorption, surface albedo, and aerosol models. The uncertainty in retrieved AOD seems to lie within the estimated over ocean error envelope of +/-(0.03+10%). Regions between broken clouds tend to have higher uncertainty. Compared to C6 AOD, a retrieval omitting observations in the vicinity of clouds (< or = 1 km) is biased by about +/- 0.05. For homogeneous aerosol distribution, clear sky retrievals show near zero bias. Close look at per-pixel reflectance histograms suggests retrieval possibility using median reflectance values.

Comparison of CERES-MODIS cloud microphysical properties with surface observations over Loess Plateau

NASA Astrophysics Data System (ADS)

Yan, Hongru; Huang, Jianping; Minnis, Patrick; Yi, Yuhong; Sun-Mack, Sunny; Wang, Tianhe; Nakajima, Takashi Y.

2015-03-01

To enhance the utility of satellite-derived cloud properties for studying the role of clouds in climate change and the hydrological cycle in semi-arid areas, it is necessary to know their uncertainties. This paper estimates the uncertainties of several cloud properties by comparing those derived over the China Loess Plateau from the MODerate-resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua by the Clouds and Earth's Radiant Energy System (CERES) with surface observations at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL). The comparisons use data from January 2008 to June 2010 limited to single layer and overcast stratus conditions during daytime. Cloud optical depths (τ) and liquid water paths (LWP) from both Terra and Aqua generally track the variation of the surface counterparts with modest correlation, while cloud effective radius (re) is only weakly correlated with the surface retrievals. The mean differences between Terra and the SACOL retrievals are -4.7±12.9, 2.1±3.2 μm and 30.2±85.3 g m-2 for τ, re and LWP, respectively. The corresponding differences for Aqua are 2.1±8.4, 1.2±2.9 μm and 47.4±79.6 g m-2, respectively. Possible causes for biases of satellite retrievals are discussed through statistical analysis and case studies. Generally, the CERES-MODIS cloud properties have a bit larger biases over the Loess Plateau than those in previous studies over other locations.

Improving snow fraction spatio-temporal continuity using a combination of MODIS and Fengyun-2 satellites over China

NASA Astrophysics Data System (ADS)

Jiang, L.; Wang, G.

2017-12-01

Snow cover is one of key elements in the investigations of weather, climatic change, water resource, and snow hazard. Satellites observations from on-board optical sensors provides the ability to snow cover mapping through the discrimination of snow from other surface features and cloud. MODIS provides maximum of snow cover data using 8-day composition data in order to reduce the cloud obscuration impacts. However, snow cover mapping is often required to obtain at the temporal scale of less than one day, especially in the case of disasters. Geostationary satellites provide much higher temporal resolution measurements (typically at 15 min or half or one hour), which has a great potential to reduce cloud cover problem and observe ground surface for identifying snow. The proposed method in this work is that how to take the advantages of polar-orbiting and geostationary optical sensors to accurately map snow cover without data gaps due to cloud. FY-2 geostationary satellites have high temporal resolution observations, however, they are lacking enough spectral bands essential for snow cover monitoring, such as the 1.6 μm band. Based on our recent work (Wang et al., 2017), we improved FY-2/VISSR fractional snow cover estimation with a linear spectral unmixing analysis method. The linear approach is applied then using the reflectance observed at the certain hourly image of FY-2 to calculate pixel-wise snow cover fraction. The composition of daily factional snow cover employs the sun zenith angle, where the snow fraction under lowest sun zenith angle is considered as the most confident result. FY-2/VISSR fractional snow cover map has less cloud due to the composition of multi-temporal snow maps in a single day. In order to get an accurate and cloud-reduced fractional snow cover map, both of MODIS and FY-2/VISSR daily snow fraction maps are blended together. With the combination of FY-2E/VISSR and MODIS, there are still some cloud existing in the daily snow fraction map. Then the combination snow fraction map is temporally reconstructed using MATLAB Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) function to derive a completely daily cloud-free snow cover map under all the sky conditions.

Validation of Cloud Properties From Multiple Satellites Using CALIOP Data

NASA Technical Reports Server (NTRS)

Yost, Christopher R.; Minnis, Patrick; Bedka, Kristopher M.; Heck, Patrick W.; Palikonda, Rabindra; Sun-Mack, Sunny; Trepte, Qing

2016-01-01

The NASA Langley Satellite ClOud and Radiative Property retrieval System (SatCORPS) is routinely applied to multispectral imagery from several geostationary and polar-orbiting imagers to retrieve cloud properties for weather and climate applications. Validation of the retrievals with independent datasets is continuously ongoing in order to understand differences caused by calibration, spatial resolution, viewing geometry, and other factors. The CALIOP instrument provides a decade of detailed cloud observations which can be used to evaluate passive imager retrievals of cloud boundaries, thermodynamic phase, cloud optical depth, and water path on a global scale. This paper focuses on comparisons of CALIOP retrievals to retrievals from MODIS, VIIRS, AVHRR, GOES, SEVIRI, and MTSAT. CALIOP is particularly skilled at detecting weakly-scattering cirrus clouds with optical depths less than approx. 0.5. These clouds are often undetected by passive imagers and the effect this has on the property retrievals is discussed.

The effect of different spectral shape parameterizations of cloud droplet size distribution on first and second aerosol indirect effects in NACR CAM5 and evaluation with satellite data

NASA Astrophysics Data System (ADS)

Wang, M.; Peng, Y.; Xie, X.; Liu, Y.

2017-12-01

Aerosol cloud interaction continues to constitute one of the most significant uncertainties for anthropogenic climate perturbations. The parameterization of cloud droplet size distribution and autoconversion process from large scale cloud to rain can influence the estimation of first and second aerosol indirect effects in global climate models. We design a series of experiments focusing on the microphysical cloud scheme of NCAR CAM5 (Community Atmospheric Model Version 5) in transient historical run with realistic sea surface temperature and sea ice. We investigate the effect of three empirical, two semi-empirical and one analytical expressions for droplet size distribution on cloud properties and explore the statistical relationships between aerosol optical thickness (AOT) and simulated cloud variables, including cloud top droplet effective radius (CDER), cloud optical depth (COD), cloud water path (CWP). We also introduce the droplet spectral shape parameter into the autoconversion process to incorporate the effect of droplet size distribution on second aerosol indirect effect. Three satellite datasets (MODIS Terra/ MODIS Aqua/ AVHRR) are used to evaluate the simulated aerosol indirect effect from the model. Evident CDER decreasing with significant AOT increasing is found in the east coast of China to the North Pacific Ocean and the east coast of USA to the North Atlantic Ocean. Analytical and semi-empirical expressions for spectral shape parameterization show stronger first aerosol indirect effect but weaker second aerosol indirect effect than empirical expressions because of the narrower droplet size distribution.

A physically based algorithm for non-blackbody correction of the cloud top temperature for the convective clouds

NASA Astrophysics Data System (ADS)

Wang, C.; Luo, Z. J.; Chen, X.; Zeng, X.; Tao, W.; Huang, X.

2012-12-01

Cloud top temperature is a key parameter to retrieval in the remote sensing of convective clouds. Passive remote sensing cannot directly measure the temperature at the cloud tops. Here we explore a synergistic way of estimating cloud top temperature by making use of the simultaneous passive and active remote sensing of clouds (in this case, CloudSat and MODIS). Weighting function of the MODIS 11μm band is explicitly calculated by feeding cloud hydrometer profiles from CloudSat retrievals and temperature and humidity profiles based on ECMWF ERA-interim reanalysis into a radiation transfer model. Among 19,699 tropical deep convective clouds observed by the CloudSat in 2008, the averaged effective emission level (EEL, where the weighting function attains its maximum) is at optical depth 0.91 with a standard deviation of 0.33. Furthermore, the vertical gradient of CloudSat radar reflectivity, an indicator of the fuzziness of convective cloud top, is linearly proportional to, d_{CTH-EEL}, the distance between the EEL of 11μm channel and cloud top height (CTH) determined by the CloudSat when d_{CTH-EEL}<0.6km. Beyond 0.6km, the distance has little sensitivity to the vertical gradient of CloudSat radar reflectivity. Based on these findings, we derive a formula between the fuzziness in the cloud top region, which is measurable by CloudSat, and the MODIS 11μm brightness temperature assuming that the difference between effective emission temperature and the 11μm brightness temperature is proportional to the cloud top fuzziness. This formula is verified using the simulated deep convective cloud profiles by the Goddard Cumulus Ensemble model. We further discuss the application of this formula in estimating cloud top buoyancy as well as the error characteristics of the radiative calculation within such deep-convective clouds.

Clear-Sky Narrowband Albedo Datasets Derived from Modis Data

NASA Astrophysics Data System (ADS)

Chen, Y.; Minnis, P.; Sun-Mack, S.; Arduini, R. F.; Hong, G.

2013-12-01

Satellite remote sensing of clouds requires an accurate estimate of the clear-sky radiances for a given scene to detect clouds and aerosols and to retrieve their microphysical properties. Knowing the spatial and angular variability of clear-sky albedo is essential for predicting the clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the near-infrared (NIR; 1.24, 1.6 or 2.13 μm) and visible (VIS; 0.63 μm) channels available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS) to help identify clouds and retrieve their properties. Generally, clear-sky albedo for a given surface type is determined for conditions when the vegetation is either thriving or dormant and free of snow. The clear-sky albedos are derived using a radiative transfer parameterization of the impact of the atmosphere, including aerosols, on the observed reflectances. This paper presents the method of generating monthly clear-sky overhead albedo maps for both snow-free and snow-covered surfaces of these channels using one year of MODIS (Moderate Resolution Imaging Spectroradiometer) CERES products. Maps of 1.24 and 1.6 μm are being used as the background to help retrieve cloud properties (e.g., effective particle size, optical depth) in CERES cloud retrievals in both snow-free and snow-covered conditions.

The Effect of Asian Dust Aerosols on Cloud Properties and Radiative Forcing from MODIS and CERES

NASA Technical Reports Server (NTRS)

Huang, Jianping; Minnis, Patrick; Lin, Bing; Wang, Tianhe; Yi, Yuhong; Hu, Yongxiang; Sun-Mack, Sunny; Ayers, Kirk

2005-01-01

The effects of dust storms on cloud properties and radiative forcing are analyzed over northwestern China from April 2001 to June 2004 using data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth's Radiant Energy System (CERES) instruments on the Aqua and Terra satellites. On average, ice cloud effective particle diameter, optical depth and ice water path of the cirrus clouds under dust polluted conditions are 11%, 32.8%, and 42% less, respectively, than those derived from ice clouds in dust-free atmospheric environments. The humidity differences are larger in the dusty region than in the dust-free region, and may be caused by removal of moisture by wet dust precipitation. Due to changes in cloud microphysics, the instantaneous net radiative forcing is reduced from -71.2 W/m2 for dust contaminated clouds to -182.7 W/m2 for dust-free clouds. The reduced cooling effects of dusts may lead to a net warming of 1 W/m2, which, if confirmed, would be the strongest aerosol forcing during later winter and early spring dust storm seasons over the studied region.

Comparing airborne and satellite retrievals of cloud optical thickness and particle effective radius using a spectral radiance ratio technique: two case studies for cirrus and deep convective clouds

NASA Astrophysics Data System (ADS)

Krisna, Trismono C.; Wendisch, Manfred; Ehrlich, André; Jäkel, Evelyn; Werner, Frank; Weigel, Ralf; Borrmann, Stephan; Mahnke, Christoph; Pöschl, Ulrich; Andreae, Meinrat O.; Voigt, Christiane; Machado, Luiz A. T.

2018-04-01

Solar radiation reflected by cirrus and deep convective clouds (DCCs) was measured by the Spectral Modular Airborne Radiation Measurement System (SMART) installed on the German High Altitude and Long Range Research Aircraft (HALO) during the Mid-Latitude Cirrus (ML-CIRRUS) and the Aerosol, Cloud, Precipitation, and Radiation Interaction and Dynamic of Convective Clouds System - Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modelling and to the Global Precipitation Measurement (ACRIDICON-CHUVA) campaigns. On particular flights, HALO performed measurements closely collocated with overpasses of the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite. A cirrus cloud located above liquid water clouds and a DCC topped by an anvil cirrus are analyzed in this paper. Based on the nadir spectral upward radiance measured above the two clouds, the optical thickness τ and particle effective radius reff of the cirrus and DCC are retrieved using a radiance ratio technique, which considers the cloud thermodynamic phase, the vertical profile of cloud microphysical properties, the presence of multilayer clouds, and the heterogeneity of the surface albedo. For the cirrus case, the comparison of τ and reff retrieved on the basis of SMART and MODIS measurements yields a normalized mean absolute deviation of up to 1.2 % for τ and 2.1 % for reff. For the DCC case, deviations of up to 3.6 % for τ and 6.2 % for reff are obtained. The larger deviations in the DCC case are mainly attributed to the fast cloud evolution and three-dimensional (3-D) radiative effects. Measurements of spectral upward radiance at near-infrared wavelengths are employed to investigate the vertical profile of reff in the cirrus. The retrieved values of reff are compared with corresponding in situ measurements using a vertical weighting method. Compared to the MODIS observations, measurements of SMART provide more information on the vertical distribution of particle sizes, which allow reconstructing the profile of reff close to the cloud top. The comparison between retrieved and in situ reff yields a normalized mean absolute deviation, which ranges between 1.5 and 10.3 %, and a robust correlation coefficient of 0.82.

Retrieval of Cloud Properties for Partially Cloud-Filled Pixels During CRYSTAL-FACE

NASA Astrophysics Data System (ADS)

Nguyen, L.; Minnis, P.; Smith, W. L.; Khaiyer, M. M.; Heck, P. W.; Sun-Mack, S.; Uttal, T.; Comstock, J.

2003-12-01

Partially cloud-filled pixels can be a significant problem for remote sensing of cloud properties. Generally, the optical depth and effective particle sizes are often too small or too large, respectively, when derived from radiances that are assumed to be overcast but contain radiation from both clear and cloud areas within the satellite imager field of view. This study presents a method for reducing the impact of such partially cloud field pixels by estimating the cloud fraction within each pixel using higher resolution visible (VIS, 0.65mm) imager data. Although the nominal resolution for most channels on the Geostationary Operational Environmental Satellite (GOES) imager and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra are 4 and 1 km, respectively, both instruments also take VIS channel data at 1 km and 0.25 km, respectively. Thus, it may be possible to obtain an improved estimate of cloud fraction within the lower resolution pixels by using the information contained in the higher resolution VIS data. GOES and MODIS multi-spectral data, taken during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE), are analyzed with the algorithm used for the Atmospheric Radiation Measurement Program (ARM) and the Clouds and Earth's Radiant Energy System (CERES) to derive cloud amount, temperature, height, phase, effective particle size, optical depth, and water path. Normally, the algorithm assumes that each pixel is either entirely clear or cloudy. In this study, a threshold method is applied to the higher resolution VIS data to estimate the partial cloud fraction within each low-resolution pixel. The cloud properties are then derived from the observed low-resolution radiances using the cloud cover estimate to properly extract the radiances due only to the cloudy part of the scene. This approach is applied to both GOES and MODIS data to estimate the improvement in the retrievals for each resolution. Results are compared with the radar reflectivity techniques employed by the NOAA ETL MMCR and the PARSL 94 GHz radars located at the CRYSTAL-FACE Eastern & Western Ground Sites, respectively. This technique is most likely to yield improvements for low and midlevel layer clouds that have little thermal variability in cloud height.

The Influence of Thermodynamic Phase on the Retrieval of Mixed-Phase Cloud Microphysical and Optical Properties in the Visible and Near Infrared Region

NASA Technical Reports Server (NTRS)

Lee, Joonsuk; Yang, Ping; Dessler, Andrew E.; Baum, Bryan A.; Platnick, Steven

2005-01-01

Cloud microphysical and optical properties are inferred from the bidirectional reflectances simulated for a single-layered cloud consisting of an external mixture of ice particles and liquid droplets. The reflectances are calculated with a rigorous discrete ordinates radiative transfer model and are functions of the cloud effective particle size, the cloud optical thickness, and the values of the ice fraction in the cloud (i.e., the ratio of ice water content to total water content). In the present light scattering and radiative transfer simulations, the ice fraction is assumed to be vertically homogeneous; the habit (shape) percentage as a function of ice particle size is consistent with that used for the Moderate Resolution Imaging Spectroradiometer (MODIS) operational (Collection 4 and earlier) cloud products; and the surface is assumed to be Lambertian with an albedo of 0.03. Furthermore, error analyses pertaining to the inference of the effective particle sizes and optical thicknesses of mixed-phase clouds are performed. Errors are calculated with respect to the assumption of a cloud containing solely liquid or ice phase particles. The analyses suggest that the effective particle size inferred for a mixed-phase cloud can be underestimated (or overestimated) if pure liquid phase (or pure ice phase) is assumed for the cloud, whereas the corresponding cloud optical thickness can be overestimated (or underestimated).

Effects of Cloud Horizontal Inhomogeneity and Drizzle on Remote Sensing of Cloud Droplet Effective Radius: Case Studies Based on Large-eddy Simulations

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Ackerman, Andrew S.; Feingold, Graham; Platnick, Steven; Pincus, Robert; Xue, Huiwen

2012-01-01

This study investigates effects of drizzle and cloud horizontal inhomogeneity on cloud effective radius (re) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS). In order to identify the relative importance of various factors, we developed a MODIS cloud property retrieval simulator based on the combination of large-eddy simulations (LES) and radiative transfer computations. The case studies based on synthetic LES cloud fields indicate that at high spatial resolution (100 m) 3-D radiative transfer effects, such as illumination and shadowing, can induce significant differences between retrievals ofre based on reflectance at 2.1 m (re,2.1) and 3.7 m (re,3.7). It is also found that 3-D effects tend to have stronger impact onre,2.1 than re,3.7, leading to positive difference between the two (re,3.72.1) from illumination and negative re,3.72.1from shadowing. The cancellation of opposing 3-D effects leads to overall reasonable agreement betweenre,2.1 and re,3.7 at high spatial resolution as far as domain averages are concerned. At resolutions similar to MODIS, however, re,2.1 is systematically larger than re,3.7when averaged over the LES domain, with the difference exhibiting a threshold-like dependence on bothre,2.1and an index of the sub-pixel variability in reflectance (H), consistent with MODIS observations. In the LES cases studied, drizzle does not strongly impact reretrievals at either wavelength. It is also found that opposing 3-D radiative transfer effects partly cancel each other when cloud reflectance is aggregated from high spatial resolution to MODIS resolution, resulting in a weaker net impact of 3-D radiative effects onre retrievals. The large difference at MODIS resolution between re,3.7 and re,2.1 for highly inhomogeneous pixels with H 0.4 can be largely attributed to what we refer to as the plane-parallelrebias, which is attributable to the impact of sub-pixel level horizontal variability of cloud optical thickness onre retrievals and is greater for re,2.1 than re,3.7. These results suggest that there are substantial uncertainties attributable to 3-D radiative effects and plane-parallelre bias in the MODIS re,2.1retrievals for pixels with strong sub-pixel scale variability, and theH index can be used to identify these uncertainties.

DSCOVR EPIC L2 Atmospheric Correction (MAIAC) Data Release Announcement

Atmospheric Science Data Center

2018-06-22

... several atmospheric quantities including cloud mask and aerosol optical depth (AOD) required for atmospheric correction. The parameters ... is a useful complementary dataset to MODIS and VIIRS global aerosol products.   Information about the DSCOVR EPIC Atmospheric ...

Aerosol climatology using a tunable spectral variability cloud screening of AERONET data

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Gobbi, Gian Paolo; Koren, Ilan

2005-01-01

Can cloud screening of an aerosol data set, affect the aerosol optical thickness (AOT) climatology? Aerosols, humidity and clouds are correlated. Therefore, rigorous cloud screening can systematically bias towards less cloudy conditions, underestimating the average AOT. Here, using AERONET data we show that systematic rejection of variable atmospheric optical conditions can generate such bias in the average AOT. Therefore we recommend (1) to introduce more powerful spectral variability cloud screening and (2) to change the philosophy behind present aerosol climatologies: Instead of systematically rejecting all cloud contaminations, we suggest to intentionally allow the presence of cloud contamination, estimate the statistical impact of the contamination and correct for it. The analysis, applied to 10 AERONET stations with approx. 4 years of data, shows almost no change for Rome (Italy), but up to a change in AOT of 0.12 in Beijing (PRC). Similar technique may be explored for satellite analysis, e.g. MODIS.

Initial Validation and Results of Geoscience Laser Altimeter System Optical Properties Retrievals

NASA Technical Reports Server (NTRS)

Hlavka, Dennis L.; Hart, W. D.; Pal, S. P.; McGill, M.; Spinhirne, J. D.

2004-01-01

Verification of Geoscience Laser Altimeter System (GLAS) optical retrievals is . problematic in that passage over ground sites is both instantaneous and sparse plus space-borne passive sensors such as MODIS are too frequently out of sync with the GLAS position. In October 2003, the GLAS Validation Experiment was executed from NASA Dryden Research Center, California to greatly increase validation possibilities. The high-altitude NASA ER-2 aircraft and onboard instrumentation of Cloud Physics Lidar (CPL), MODIS Airborne Simulator (MAS), and/or MODIS/ASTER Airborne Simulator (MASTER) under-flew seven orbit tracks of GLAS for cirrus, smoke, and urban pollution optical properties inter-comparisons. These highly calibrated suite of instruments are the best data set yet to validate GLAS atmospheric parameters. In this presentation, we will focus on the inter-comparison with GLAS and CPL and draw preliminary conclusions about the accuracies of the GLAS 532nm retrievals of optical depth, extinction, backscatter cross section, and calculated extinction-to-backscatter ratio. Comparisons to an AERONET/MPL ground-based site at Monterey, California will be attempted. Examples of GLAS operational optical data products will be shown.

A Big Data Approach for Situation-Aware estimation, correction and prediction of aerosol effects, based on MODIS Joint Atmosphere product (collection 6) time series data

NASA Astrophysics Data System (ADS)

Singh, A. K.; Toshniwal, D.

2017-12-01

The MODIS Joint Atmosphere product, MODATML2 and MYDATML2 L2/3 provided by LAADS DAAC (Level-1 and Atmosphere Archive & Distribution System Distributed Active Archive Center) re-sampled from medium resolution MODIS Terra /Aqua Satellites data at 5km scale, contains Cloud Reflectance, Cloud Top Temperature, Water Vapor, Aerosol Optical Depth/Thickness, Humidity data. These re-sampled data, when used for deriving climatic effects of aerosols (particularly in case of cooling effect) still exposes limitations in presence of uncertainty measures in atmospheric artifacts such as aerosol, cloud, cirrus cloud etc. The effect of uncertainty measures in these artifacts imposes an important challenge for estimation of aerosol effects, adequately affecting precise regional weather modeling and predictions: Forecasting and recommendation applications developed largely depend on these short-term local conditions (e.g. City/Locality based recommendations to citizens/farmers based on local weather models). Our approach inculcates artificial intelligence technique for representing heterogeneous data(satellite data along with air quality data from local weather stations (i.e. in situ data)) to learn, correct and predict aerosol effects in the presence of cloud and other atmospheric artifacts, defusing Spatio-temporal correlations and regressions. The Big Data process pipeline consisting correlation and regression techniques developed on Apache Spark platform can easily scale for large data sets including many tiles (scenes) and over widened time-scale. Keywords: Climatic Effects of Aerosols, Situation-Aware, Big Data, Apache Spark, MODIS Terra /Aqua, Time Series

An Assessment of Differences Between Cloud Effective Particle Radius Retrievals for Marine Water Clouds from Three MODIS Spectral Bands

NASA Technical Reports Server (NTRS)

Platnick, Steven; Zhang, Zhibo

2011-01-01

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

The impact of cloud vertical profile on liquid water path retrieval based on the bispectral method: A theoretical study based on large-eddy simulations of shallow marine boundary layer clouds.

PubMed

Miller, Daniel J; Zhang, Zhibo; Ackerman, Andrew S; Platnick, Steven; Baum, Bryan A

2016-04-27

Passive optical retrievals of cloud liquid water path (LWP), like those implemented for Moderate Resolution Imaging Spectroradiometer (MODIS), rely on cloud vertical profile assumptions to relate optical thickness ( τ ) and effective radius ( r e ) retrievals to LWP. These techniques typically assume that shallow clouds are vertically homogeneous; however, an adiabatic cloud model is plausibly more realistic for shallow marine boundary layer cloud regimes. In this study a satellite retrieval simulator is used to perform MODIS-like satellite retrievals, which in turn are compared directly to the large-eddy simulation (LES) output. This satellite simulator creates a framework for rigorous quantification of the impact that vertical profile features have on LWP retrievals, and it accomplishes this while also avoiding sources of bias present in previous observational studies. The cloud vertical profiles from the LES are often more complex than either of the two standard assumptions, and the favored assumption was found to be sensitive to cloud regime (cumuliform/stratiform). Confirming previous studies, drizzle and cloud top entrainment of dry air are identified as physical features that bias LWP retrievals away from adiabatic and toward homogeneous assumptions. The mean bias induced by drizzle-influenced profiles was shown to be on the order of 5-10 g/m 2 . In contrast, the influence of cloud top entrainment was found to be smaller by about a factor of 2. A theoretical framework is developed to explain variability in LWP retrievals by introducing modifications to the adiabatic r e profile. In addition to analyzing bispectral retrievals, we also compare results with the vertical profile sensitivity of passive polarimetric retrieval techniques.

The impact of cloud vertical profile on liquid water path retrieval based on the bispectral method: A theoretical study based on large-eddy simulations of shallow marine boundary layer clouds

PubMed Central

Miller, Daniel J.; Zhang, Zhibo; Ackerman, Andrew S.; Platnick, Steven; Baum, Bryan A.

2018-01-01

Passive optical retrievals of cloud liquid water path (LWP), like those implemented for Moderate Resolution Imaging Spectroradiometer (MODIS), rely on cloud vertical profile assumptions to relate optical thickness (τ) and effective radius (re) retrievals to LWP. These techniques typically assume that shallow clouds are vertically homogeneous; however, an adiabatic cloud model is plausibly more realistic for shallow marine boundary layer cloud regimes. In this study a satellite retrieval simulator is used to perform MODIS-like satellite retrievals, which in turn are compared directly to the large-eddy simulation (LES) output. This satellite simulator creates a framework for rigorous quantification of the impact that vertical profile features have on LWP retrievals, and it accomplishes this while also avoiding sources of bias present in previous observational studies. The cloud vertical profiles from the LES are often more complex than either of the two standard assumptions, and the favored assumption was found to be sensitive to cloud regime (cumuliform/stratiform). Confirming previous studies, drizzle and cloud top entrainment of dry air are identified as physical features that bias LWP retrievals away from adiabatic and toward homogeneous assumptions. The mean bias induced by drizzle-influenced profiles was shown to be on the order of 5–10 g/m2. In contrast, the influence of cloud top entrainment was found to be smaller by about a factor of 2. A theoretical framework is developed to explain variability in LWP retrievals by introducing modifications to the adiabatic re profile. In addition to analyzing bispectral retrievals, we also compare results with the vertical profile sensitivity of passive polarimetric retrieval techniques. PMID:29637042

Cloud Retrieval Information Content Studies with the Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Ocean Color Imager (OCI)

NASA Astrophysics Data System (ADS)

Coddington, Odele; Platnick, Steven; Pilewskie, Peter; Schmidt, Sebastian

2016-04-01

The NASA Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Science Definition Team (SDT) report released in 2012 defined imager stability requirements for the Ocean Color Instrument (OCI) at the sub-percent level. While the instrument suite and measurement requirements are currently being determined, the PACE SDT report provided details on imager options and spectral specifications. The options for a threshold instrument included a hyperspectral imager from 350-800 nm, two near-infrared (NIR) channels, and three short wave infrared (SWIR) channels at 1240, 1640, and 2130 nm. Other instrument options include a variation of the threshold instrument with 3 additional spectral channels at 940, 1378, and 2250 nm and the inclusion of a spectral polarimeter. In this work, we present cloud retrieval information content studies of optical thickness, droplet effective radius, and thermodynamic phase to quantify the potential for continuing the low cloud climate data record established by the MOderate Resolution and Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) missions with the PACE OCI instrument (i.e., non-polarized cloud reflectances and in the absence of midwave and longwave infrared channels). The information content analysis is performed using the GEneralized Nonlinear Retrieval Analysis (GENRA) methodology and the Collection 6 simulated cloud reflectance data for the common MODIS/VIIRS algorithm (MODAWG) for Cloud Mask, Cloud-Top, and Optical Properties. We show that using both channels near 2 microns improves the probability of cloud phase discrimination with shortwave-only cloud reflectance retrievals. Ongoing work will extend the information content analysis, currently performed for dark ocean surfaces, to different land surface types.

Progress in Understanding the Impacts of 3-D Cloud Structure on MODIS Cloud Property Retrievals for Marine Boundary Layer Clouds

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Werner, Frank; Miller, Daniel; Platnick, Steven; Ackerman, Andrew; DiGirolamo, Larry; Meyer, Kerry; Marshak, Alexander; Wind, Galina; Zhao, Guangyu

2016-01-01

Theory: A novel framework based on 2-D Tayler expansion for quantifying the uncertainty in MODIS retrievals caused by sub-pixel reflectance inhomogeneity. (Zhang et al. 2016). How cloud vertical structure influences MODIS LWP retrievals. (Miller et al. 2016). Observation: Analysis of failed MODIS cloud property retrievals. (Cho et al. 2015). Cloud property retrievals from 15m resolution ASTER observations. (Werner et al. 2016). Modeling: LES-Satellite observation simulator (Zhang et al. 2012, Miller et al. 2016).

MODIS volcanic ash retrievals vs FALL3D transport model: a quantitative comparison

NASA Astrophysics Data System (ADS)

Corradini, S.; Merucci, L.; Folch, A.

2010-12-01

Satellite retrievals and transport models represents the key tools to monitor the volcanic clouds evolution. Because of the harming effects of fine ash particles on aircrafts, the real-time tracking and forecasting of volcanic clouds is key for aviation safety. Together with the security reasons also the economical consequences of a disruption of airports must be taken into account. The airport closures due to the recent Icelandic Eyjafjöll eruption caused millions of passengers to be stranded not only in Europe, but across the world. IATA (the International Air Transport Association) estimates that the worldwide airline industry has lost a total of about 2.5 billion of Euro during the disruption. Both security and economical issues require reliable and robust ash cloud retrievals and trajectory forecasting. The intercomparison between remote sensing and modeling is required to assure precise and reliable volcanic ash products. In this work we perform a quantitative comparison between Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of volcanic ash cloud mass and Aerosol Optical Depth (AOD) with the FALL3D ash dispersal model. MODIS, aboard the NASA-Terra and NASA-Aqua polar satellites, is a multispectral instrument with 36 spectral bands operating in the VIS-TIR spectral range and spatial resolution varying between 250 and 1000 m at nadir. The MODIS channels centered around 11 and 12 micron have been used for the ash retrievals through the Brightness Temperature Difference algorithm and MODTRAN simulations. FALL3D is a 3-D time-dependent Eulerian model for the transport and deposition of volcanic particles that outputs, among other variables, cloud column mass and AOD. Three MODIS images collected the October 28, 29 and 30 on Mt. Etna volcano during the 2002 eruption have been considered as test cases. The results show a general good agreement between the retrieved and the modeled volcanic clouds in the first 300 km from the vents. Even if the modeled volcanic cloud area is systematically wider than the retrieved area, the ash total mass is comparable and varies between 35 and 60 kt and between 20 and 42 kt for FALL3D and MODIS respectively. The mean AOD values are in good agreement and approximately equal to 0.8. When the whole volcanic clouds are considered the ash areas and the total ash masses, computed by FALL3D model are significantly greater than the same parameters retrieved from the MODIS data, while the mean AOD values remain in a very good agreement and equal to about 0.6. The volcanic cloud direction in its distal part is not coincident for the 29 and 30 October 2002 images due to the difference between the real and the modeled local wind fields. Finally the MODIS maps show regions of high mass and AOD due to volcanic puffs not modeled by FALL3D.

Comparison of CERES Cloud Properties Derived from Aqua and Terra MODIS Data and TRMM VIRS Radiances

NASA Astrophysics Data System (ADS)

Minnis, P.; Young, D. F.; Sun-Mack, S.; Trepte, Q. Z.; Chen, Y.; Heck, P. W.; Wielicki, B. A.

2003-12-01

The Clouds and Earth's Radiant Energy System (CERES) Project is obtaining Earth radiation budget measurements of unprecedented accuracy as a result of improved instruments and an analysis system that combines simultaneous, high-resolution cloud property retrievals with the broadband radiance data. The cloud properties are derived from three different satellite imagers: the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) and the Moderate Resolution Imaging Spectroradiometers (MODIS) on the Aqua and Terra satellites. A single set of consistent algorithms using the 0.65, 1.6 or 2.1, 3.7, 10.8, and 12.0-æm channels are applied to all three imagers. The cloud properties include, cloud coverage, height, thickness, temperature, optical depth, phase, effective particle size, and liquid or ice water path. Because each satellite is in a different orbit, the results provide information on the diurnal cycle of cloud properties. Initial intercalibrations show excellent consistency between the three images except for some differences of ~ 1K between the 3.7-æm channel on Terra and those on VIRS and Aqua. The derived cloud properties are consistent with the known diurnal characteristics of clouds in different areas. These datasets should be valuable for exploring the role of clouds in the radiation budget and hydrological cycle.

Effects of Aerosol Pollution on Clouds over Megacities

NASA Astrophysics Data System (ADS)

Sechrist, B.; Jacobson, M. Z.

2013-12-01

The correlation between aerosol optical depth (AOD) and cloud properties - principally cloud fraction and cloud optical depth (COD) - is examined using satellite retrievals from the MODIS satellites over Los Angeles and Beijing. Ten Hoeve et al. (2011, Atmos. Chem. Phys, 11(7), 3021-3036) used satellite data to examine the impact of aerosols on warm clouds around Rondonia, Brazil, during the biomass burning season. They found that the COD-AOD relationship exhibits a 'boomerang' shape in which COD initially increases with increasing AOD but then decreases as AOD continues to increase beyond some critical level. This result is thought to reflect the balance between the microphysical and radiative components of a cloud's response to aerosols. The microphysical process dominates at low AOD, while the radiative process dominates at high AOD. This study is analogous to Ten Hoeve et al., but for aerosols derived primarily from fossil fuel combustion rather than biomass burning. Preliminary results will be presented.

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters. Part 1; Equivalent Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, Galina; DaSilva, Arlindo M.; Norris, Peter M.; Platnick, Steven E.

2013-01-01

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters . Pt. 1; Synthetic Sensor Radiance Formulation; [Synthetic Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, G.; DaSilva, A. M.; Norris, P. M.; Platnick, S.

2013-01-01

In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

Comparasion of Cloud Cover restituted by POLDER and MODIS

NASA Astrophysics Data System (ADS)

Zeng, S.; Parol, F.; Riedi, J.; Cornet, C.; Thieuxleux, F.

2009-04-01

PARASOL and AQUA are two sun-synchronous orbit satellites in the queue of A-Train satellites that observe our earth within a few minutes apart from each other. Aboard these two platforms, POLDER and MODIS provide coincident observations of the cloud cover with very different characteristics. These give us a good opportunity to study the clouds system and evaluate strengths and weaknesses of each dataset in order to provide an accurate representation of global cloud cover properties. This description is indeed of outermost importance to quantify and understand the effect of clouds on global radiation budget of the earth-atmosphere system and their influence on the climate changes. We have developed a joint dataset containing both POLDER and MODIS level 2 cloud products collocated and reprojected on a common sinusoidal grid in order to make the data comparison feasible and veracious. Our foremost work focuses on the comparison of both spatial distribution and temporal variation of the global cloud cover. This simple yet critical cloud parameter need to be clearly understood to allow further comparison of the other cloud parameters. From our study, we demonstrate that on average these two sensors both detect the clouds fairly well. They provide similar spatial distributions and temporal variations:both sensors see high values of cloud amount associated with deep convection in ITCZ, over Indonesia, and in west-central Pacific Ocean warm pool region; they also provide similar high cloud cover associated to mid-latitude storm tracks, to Indian monsoon or to the stratocumulus along the west coast of continents; on the other hand small cloud amounts that typically present over subtropical oceans and deserts in subsidence aeras are well identified by both POLDER and MODIS. Each sensor has its advantages and inconveniences for the detection of a particular cloud types. With higher spatial resolution, MODIS can better detect the fractional clouds thus explaining as one part of a positive bias in any latitude and in any viewing angle with an order of 10% between the POLDER cloud amount and the so-called MODIS "combined" cloud amount. Nevertheless it is worthy to note that a negative bias of about 10% is obtained between the POLDER cloud amount and the MODIS "day-mean" cloud amount. Main differences between the two MODIS cloud amount values are known to be due to the filtering of remaining aerosols or cloud edges. due to both this high spatial resolution of MODIS and the fact that "combined" cloud amount filters cloud edges, we can also explain why appear the high positive bias regions over subtropical ocean in south hemisphere and over east Africa in summer. Thanks to several channels in the thermal infrared spectral domain, MODIS detects probably much better the thin cirrus especially over land, thus causing a general negative bias for ice clouds. The multi-spectral capability of MODIS also allows for a better detection of low clouds over snow or ice, Hence the (POLDER-MODIS) cloud amount difference is often negative over Greenland, Antarctica, and over the continents at middle-high latitudes in spring and autumn associated to the snow coverage. The multi-spectral capability of MODIS also makes the discrimination possible between the biomass burning aerosols and the fractional clouds over the continents. Thus a positive bias appears in central Africa in summer and autumn associated to important biomass burning events. Over transition region between desert and non-desert, the presence of large negative bias (POLDER-MODIS) of cloud amount maybe partly due to MODIS pixel falsely labeled the desert as cloudy, where MODIS algorithm uses static desert mask. This is clearly highlighted in south of Sahara in spring and summer where we find a bias negative with an order of -0.1. What is more, thanks to its multi-angular capability, POLDER can discriminate the sun-glint region thus minimizing the dependence of cloud amount on view angle. It makes the detection of high clouds easier over a black surface thanks to its polarization character.

The Community Cloud retrieval for CLimate (CC4CL) - Part 2: The optimal estimation approach

NASA Astrophysics Data System (ADS)

McGarragh, Gregory R.; Poulsen, Caroline A.; Thomas, Gareth E.; Povey, Adam C.; Sus, Oliver; Stapelberg, Stefan; Schlundt, Cornelia; Proud, Simon; Christensen, Matthew W.; Stengel, Martin; Hollmann, Rainer; Grainger, Roy G.

2018-06-01

The Community Cloud retrieval for Climate (CC4CL) is a cloud property retrieval system for satellite-based multispectral imagers and is an important component of the Cloud Climate Change Initiative (Cloud_cci) project. In this paper we discuss the optimal estimation retrieval of cloud optical thickness, effective radius and cloud top pressure based on the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm. Key to this method is the forward model, which includes the clear-sky model, the liquid water and ice cloud models, the surface model including a bidirectional reflectance distribution function (BRDF), and the "fast" radiative transfer solution (which includes a multiple scattering treatment). All of these components and their assumptions and limitations will be discussed in detail. The forward model provides the accuracy appropriate for our retrieval method. The errors are comparable to the instrument noise for cloud optical thicknesses greater than 10. At optical thicknesses less than 10 modeling errors become more significant. The retrieval method is then presented describing optimal estimation in general, the nonlinear inversion method employed, measurement and a priori inputs, the propagation of input uncertainties and the calculation of subsidiary quantities that are derived from the retrieval results. An evaluation of the retrieval was performed using measurements simulated with noise levels appropriate for the MODIS instrument. Results show errors less than 10 % for cloud optical thicknesses greater than 10. Results for clouds of optical thicknesses less than 10 have errors up to 20 %.

Validation of Cloud Parameters Derived from Geostationary Satellites, AVHRR, MODIS, and VIIRS Using SatCORPS Algorithms

NASA Technical Reports Server (NTRS)

Minnis, P.; Sun-Mack, S.; Bedka, K. M.; Yost, C. R.; Trepte, Q. Z.; Smith, W. L., Jr.; Painemal, D.; Chen, Y.; Palikonda, R.; Dong, X.;

How do A-train Sensors Inter-Compare in the Retrieval of Above-Cloud Aerosol Optical Depth? A Case Study based Assessment

NASA Astrophysics Data System (ADS)

Jethva, H. T.; Torres, O.; Waquet, F.; Chand, D.

2013-12-01

Atmospheric aerosols are known to produce a net cooling effect in the cloud-free conditions. However, when present over the reflective cloud decks, absorbing aerosols such as biomass burning generated smoke and wind-blown dust can potentially exert a large positive forcing through enhanced atmospheric heating resulting from cloud-aerosol radiative interactions. The interest on this aspect of aerosol science has grown significantly in the recent years. Particularly, development of the satellite-based retrieval techniques and unprecedented knowledge on the above-cloud aerosol optical depth (ACAOD) is of great relevance. A direct validation of satellite ACAOD is a difficult task primarily due to lack of ample in situ and/or remote sensing measurements of aerosols above cloud. In these circumstances, a comparative analysis on the inter-satellite ACAOD retrievals can be performed for the sack of consistency check. Here, we inter-compare the ACAOD of biomass burning plumes observed from different A-train sensors, i.e., MODIS [Jethva et al., 2013], CALIOP [Chand et al., 2008], POLDER [Waquet et al., 2009], and OMI [Torres et al., 2012]. These sensors have been shown to acquire sensitivity and independent capabilities to detect and retrieve aerosol loading above marine stratocumulus clouds--a kind of situation often found over the southeastern Atlantic Ocean during dry burning season. A systematic one-to-one comparison reveals that, in general, all passive sensors and CALIOP-based research methods retrieve comparable ACAOD over homogeneous cloud fields. The high-resolution sensors (MODIS and CALIOP) are able to retrieve aerosols over thin clouds but with larger discrepancies. Given the different types of sensor measurements processed with different algorithms, a reasonable agreement between them is encouraging. A direct validation of satellite-based ACAOD remains an open challenge for which dedicated field measurements over the region of frequent aerosol/cloud overlap are a prime requirement. Jethva, H., O. Torres, L. A. Remer, P. K. Bhartia (2013), A Color Ratio Method for Simultaneous Retrieval of Aerosol and Cloud Optical Thickness of Above-Cloud Absorbing Aerosols From Passive Sensors: Application to MODIS Measurements, Geoscience and Remote Sensing, IEEE Transactions on, 51(7), pp. 3862-3870, doi: 10.1109/TGRS.2012.2230008. Chand, D., T. L. Anderson, R. Wood, R. J. Charlson, Y. Hu, Z. Liu, and M. Vaughan (2008), Quantifying above-cloud aerosol using spaceborne lidar for improved understanding of cloudy-sky direct climate forcing, J. Geophys. Res., 113, D13206, doi:10.1029/2007JD009433. Waquet, F., J. Riedi, L. C. Labonnote, P. Goloub, B. Cairns, J.-L. Deuzeand, and D. Tanre (2009), Aerosol remote sensing over clouds using a-train observations, J. Atmos. Sci., 66(8), 2468-2480, doi: http://dx.doi.org/10.1175/2009JAS3026.1 Torres, O., H. Jethva, and P. K. Bhartia (2012), Retrieval of aerosol optical depth above clouds from OMI observations: Sensitivity analysis and case studies, J. Atmos. Sci., 69(3), 1037-1053, doi: http://dx.doi.org/10.1175/JAS-D-11-0130.

Retrieval of Ice Cloud Properties Using Variable Phase Functions

NASA Astrophysics Data System (ADS)

Heck, Patrick W.; Minnis, Patrick; Yang, Ping; Chang, Fu-Lung; Palikonda, Rabindra; Arduini, Robert F.; Sun-Mack, Sunny

2009-03-01

An enhancement to NASA Langley's Visible Infrared Solar-infrared Split-window Technique (VISST) is developed to identify and account for situations when errors are induced by using smooth ice crystals. The retrieval scheme incorporates new ice cloud phase functions that utilize hexagonal crystals with roughened surfaces. In some situations, cloud optical depths are reduced, hence, cloud height is increased. Cloud effective particle size also changes with the roughened ice crystal models which results in varied effects on the calculation of ice water path. Once validated and expanded, the new approach will be integrated in the CERES MODIS algorithm and real-time retrievals at Langley.

Evaluating NASA S-NPP continuity cloud products for climate research using CALIPSO, CATS and Level-3 analysis

NASA Astrophysics Data System (ADS)

Holz, R.; Platnick, S. E.; Meyer, K.; Frey, R.; Wind, G.; Ackerman, S. A.; Heidinger, A. K.; Botambekov, D.; Yorks, J. E.; McGill, M. J.

2016-12-01

The launch of VIIRS and CrIS on Suomi NPP in the fall of 2011 introduced the next generation of U.S. operational polar orbiting environmental observations. Similar to MODIS, VIIRS provides visible and IR observations at moderate spatial resolution and has a 1:30 pm equatorial crossing time consistent with the MODIS on Aqua platform. However unlike MODIS, VIIRS lacks water vapor and CO2 absorbing channels that are used by the MODIS cloud algorithms for both cloud detection and to retrieve cloud top height and cloud emissivity for ice clouds. Given the different spectral and spatial characteristics of VIIRS, we seek to understand the extent to which the 15-year MODIS climate record can be continued with VIIRS/CrIS observations while maintaining consistent sensitivities across the observational systems. This presentation will focus on the evaluation of the latest version of the NASA funded cloud retrieval algorithms being developed for climate research. We will present collocated inter-comparisons between the imagers (VIIRS and MODIS Aqua) with CALIPSO and Cloud Aerosol Transport System (CATS) lidar observations as well as long term statistics based on a new Level-3 (L3) product being developed as part the project. The CALIPSO inter-comparisons will focus on cloud detection (cloud mask) with a focus on the impact of recent modifications to the cloud mask and how these changes impact the global statistics. For the first time we will provide inter-comparisons between two different cloud lidar systems (CALIOP and CATS) and investigate how the different sensitivities of the lidars impact the cloud mask and cloud comparisons. Using CALIPSO and CATS as the reference, and applying the same algorithms to VIIRS and MODIS, we will discuss the consistency between products from both imagers. The L3 analysis will focus on the regional and seasonal consistency between the suite of MODIS and VIIRS continuity cloud products. Do systematic biases remains when using consistent algorithms but applied to different observations (MODIS or VIIRS)?

Validation of satellite-retrieved MBL cloud properties using DOE ARM AMF measurements at the Azores

NASA Astrophysics Data System (ADS)

Xi, B.; Dong, X.; Minnis, P.; Sun-Mack, S.

2013-05-01

Marine Boundary Layer (MBL) cloud properties derived for the Clouds and the Earth's Radiant Energy System (CERES) Project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Atmospheric Radiation Measurement (ARM) AMF AZORES site from June 2009 through December 2010. Retrievals from ARM surface-based data were averaged over a 1-hour interval centered at the time of each satellite overpass, and the CERES-MODIS Ed4 cloud properties were averaged within a 30-km x 30-km box centered on the ARM AZORES site. Two datasets were analyzed: all of the single-layered unbroken decks (SL) and those cases without temperature inversions. The CERES-MODIS cloud top/base heights were determined from cloud top/base temperature by using a lapse rate method normalized to the 24-h mean surface air temperature. The preliminary results show: for all SL MBL at daytime, they are, on average, 0.148 km (cloud top) and 0.087 km (cloud base) higher than the ARM radar-lidar observed cloud top and base, respectively. At nighttime, they are 0.446 km (cloud top) and 0.334 km (cloud base). For those cases without temperature inversions, the comparisons are close to their SL counterparts. For cloud temperatures, the MODIS-derived cloud-top and -base temperatures are 1.6 K lower and 0.4 K higher than the surface values with correlations of 0.92 during daytime. At nighttime, the differences are slightly larger and correlations are lower than daytime comparisons. Variations in the height difference are mainly caused by uncertainties in the surface air temperatures and lapse rates. Based on a total of 61 daytime and 87 nighttime samples (ALL SL cases), the temperature inversion layers occur about 72% during daytime and 83% during nighttime. The difference of surface-observed lapse rate and the satellite derived lapse rate can be 1.6 K/km for daytime and 3.3K/km for nighttime. From these lapse rates, we can further analyze the surface air temperature difference that used to calculate these lapse rate, which are ~3K difference between surface-observed and the satellite derived during the daytime and 5.1 K during nighttime. Further studies of the cause of the temperature inversions that may help the cloud heights retrievals by satellite. The preliminary comparisons in MBL microphysical properties have shown that the averaged CERES-MODIS derived MBL cloud-droplet effective radius is only 1.5 μm larger than ARM retrieval (13.2 μm), and LWP values are also very close to each other (112 vs. 124 gm-2) with a relative large difference in optical depth (10.6 vs. 14.4).

Understanding Differences Between Co-Incident CloudSat, Aqua/MODIS and NOAA18 MHS Ice water Path Retrievals Over the Tropical Oceans

NASA Technical Reports Server (NTRS)

Pittman, Jasna; Robertson, Franklin; Blankenship, Clay

2008-01-01

Accurate measurement of the physical and radiative properties of clouds and their representation in climate models continues to be a challe nge. Model parameterizations are still subject to a large number of t unable parameters; furthermore, accurate and representative in situ o bservations are very sparse, and satellite observations historically have significant quantitative uncertainties, particularly with respect to particle size distribution (PSD) and cloud phase. Ice Water Path (IWP), or amount of ice present in a cloud column, is an important cl oud property to accurately quantify, because it is an integral measur e of the microphysical properties of clouds and the cloud feedback pr ocesses in the climate system. This paper investigates near co-incident retrievals of IWP over tropical oceans using three diverse measurem ent systems: radar from CloudSat, Vis/IR from Aqua/MODIS, and microwa ve from NOAA-18IMHS. CloudSat 94 GHz radar measurements provide high resolution vertical and along-orbit structure of cloud reflectivity a nd enable IWP (and IWC) retrievals. Overlapping MODIS measurements of cloud optical thickness and phase allow estimates of IWP when cloud tops are identified as being ice. Periodically, NOAA18 becomes co-inci dent in space I time to enable comparison of A-Train measurements to IWP inferred from the 157 and 89 GHz channel radiances. This latter m easurement is effective only for thick convective anvil systems. We s tratify these co-incident data (less than 4 minutes separation) into cirrus only, cirrus overlying liquid water clouds, and precipitating d eep convective clouds. Substantial biases in IWP and ice effective ra dius are found. Systematic differences in these retrievals are consid ered in light of the uncertainties in a priori assumptions ofPSDs, sp ectral sensitivity and algorithm strategies, which have a direct impact on the IWP product.

Promise and Capability of NASA's Earth Observing System to Monitor Human-Induced Climate Variations

NASA Technical Reports Server (NTRS)

King, M. D.

2003-01-01

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. The Moderate Resolution Imaging Spectroradiometer (MODIS), developed as part of the Earth Observing System (EOS) and launched on Terra in December 1999 and Aqua in May 2002, is designed to meet the scientific needs for satellite remote sensing of clouds, aerosols, water vapor, and land and ocean surface properties. This sensor and multi-platform observing system is especially well suited to observing detailed interdisciplinary components of the Earth s surface and atmosphere in and around urban environments, including aerosol optical properties, cloud optical and microphysical properties of both liquid water and ice clouds, land surface reflectance, fire occurrence, and many other properties that influence the urban environment and are influenced by them. In this presentation I will summarize the current capabilities of MODIS and other EOS sensors currently in orbit to study human-induced climate variations.

Developing Remote Sensing Capabilities for Meter-Scale Sea Ice Properties

DTIC Science & Technology

2013-09-30

such as MODIS . APPROACH 1. Task and acquire high resolution panchromatic and multispectral optical (e.g. Quickbird, Worldview, National Assets...does not display a currently valid OMB control number. 1. REPORT DATE 30 SEP 2013 2. REPORT TYPE 3. DATES COVERED 00-00-2013 to 00-00-2013 4...cloud cover , an excessive percentage of the imagery acquired over drifting sites was cloud covered , and the vendor did not delay acquisitions or

If the MODIS Aerosol Product is so Infested with Cloud Contamination, Why Does Everybody Use the Product?

NASA Technical Reports Server (NTRS)

Remeer, Lorraine A.

2011-01-01

The MODIS aerosol cloud mask is based on a spatial variability test, using the assumption that aerosols are more homogeneous than clouds. On top of this first line of defense are a series of additional tests based on threshold values and ratios of various MODIS channels. The goal is to eliminate clouds and keep the aerosol. How well have we succeeded? There have been several studies showing cloud contamination in the MODIS aerosol product and several alternative cloud masks proposed. There are even "competing" MODIS aerosol products that offer an alternative "cloud free" world. Are these alternative products an improvement to the old standard product? We find there is a trade-off between retrieval availability and cloud contamination, and for many applications it is better to have a little bit of cloud in the product than to not have enough product. I will review the decisions that led us to the present MODIS cloud mask, and show how it is simultaneously too liberal and too conservative, some ideas on how to make it better and why in the end it doesn't matter. I hope to inspire a spirited discussion and will be very willing to take your complaints and suggestions.

Ground truth spectrometry and imagery of eruption clouds to maximize utility of satellite imagery

NASA Technical Reports Server (NTRS)

Rose, William I.

1993-01-01

Field experiments with thermal imaging infrared radiometers were performed and a laboratory system was designed for controlled study of simulated ash clouds. Using AVHRR (Advanced Very High Resolution Radiometer) thermal infrared bands 4 and 5, a radiative transfer method was developed to retrieve particle sizes, optical depth and particle mass involcanic clouds. A model was developed for measuring the same parameters using TIMS (Thermal Infrared Multispectral Scanner), MODIS (Moderate Resolution Imaging Spectrometer), and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer). Related publications are attached.

Remote Sensing of Water Vapor and Thin Cirrus Clouds using MODIS Near-IR Channels

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Kaufman, Yoram J.

2001-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS), a major facility instrument on board the Terra Spacecraft, was successfully launched into space in December of 1999. MODIS has several near-IR channels within and around the 0.94 micrometer water vapor bands for remote sensing of integrated atmospheric water vapor over land and above clouds. MODIS also has a special near-IR channel centered at 1.375-micron with a width of 30 nm for remote sensing of cirrus clouds. In this paper, we describe briefly the physical principles on remote sensing of water vapor and cirrus clouds using these channels. We also present sample water vapor images and cirrus cloud images obtained from MODIS data.

The Radiative Consistency of Atmospheric Infrared Sounder and Moderate Resolution Imaging Spectroradiometer Cloud Retrievals

NASA Technical Reports Server (NTRS)

Kahn, Brian H.; Fishbein, Evan; Nasiri, Shaima L.; Eldering, Annmarie; Fetzer, Eric J.; Garay, Michael J.; Lee, Sung-Yung

2007-01-01

The consistency of cloud top temperature (Tc) and effective cloud fraction (f) retrieved by the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) observation suite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on the EOS-Aqua platform are investigated. Collocated AIRS and MODIS TC and f are compared via an 'effective scene brightness temperature' (Tb,e). Tb,e is calculated with partial field of view (FOV) contributions from TC and surface temperature (TS), weighted by f and 1-f, respectively. AIRS reports up to two cloud layers while MODIS reports up to one. However, MODIS reports TC, TS, and f at a higher spatial resolution than AIRS. As a result, pixel-scale comparisons of TC and f are difficult to interpret, demonstrating the need for alternatives such as Tb,e. AIRS-MODIS Tb,e differences ((Delta)Tb,e) for identical observing scenes are useful as a diagnostic for cloud quantity comparisons. The smallest values of DTb,e are for high and opaque clouds, with increasing scatter in (Delta)Tb,e for clouds of smaller opacity and lower altitude. A persistent positive bias in DTb,e is observed in warmer and low-latitude scenes, characterized by a mixture of MODIS CO2 slicing and 11-mm window retrievals. These scenes contain heterogeneous cloud cover, including mixtures of multilayered cloudiness and misplaced MODIS cloud top pressure. The spatial patterns of (Delta)Tb,e are systematic and do not correlate well with collocated AIRS-MODIS radiance differences, which are more random in nature and smaller in magnitude than (Delta)Tb,e. This suggests that the observed inconsistencies in AIRS and MODIS cloud fields are dominated by retrieval algorithm differences, instead of differences in the observed radiances. The results presented here have implications for the validation of cloudy satellite retrieval algorithms, and use of cloud products in quantitative analyses.

Progress towards MODIS and VIIRS Cloud Fraction Data Record Continuity

NASA Astrophysics Data System (ADS)

Ackerman, S. A.; Frey, R.; Holz, R.; Platnick, S. E.; Heidinger, A. K.

2016-12-01

Satellite-derived clear-sky vs. cloudy-sky discrimination at the pixel scale is an important input parameter used in many real-time applications. Cloud fractions, resulting from integrating over time and space, are also critical to the study of recent decadal climate changes. The NASA NPOESS Preparatory Project (NPP) has funded a science team to develop and study the ability to make continuous climate records from MODIS (2000-2020) and VIIRS (2012-2030). The MODAWG project, led by Dr. Steve Platnick of NASA/GSFC, combines elements of the MODIS processing system and the NOAA Algorithm Working Group (AWG) to achieve this goal. This presentation will focus on the cloud masking aspects of MODAWG, derived primarily from the MODIS cloud mask (MOD35). Challenges to continuity of cloud detection due to differences in instrument characteristics will be discussed. Cloud mask results from use of the same (continuity) algorithm will be shown for both MODIS and VIIRS, including comparisons to collocated CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) cloud data.

Improved Cloud and Snow Screening in MAIAC Aerosol Retrievals Using Spectral and Spatial Analysis

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Laszlo, I.; Kokrkin, S.

2012-01-01

An improved cloud/snow screening technique in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is described. It is implemented as part of MAIAC aerosol retrievals based on analysis of spectral residuals and spatial variability. Comparisons with AERONET aerosol observations and a large-scale MODIS data analysis show strong suppression of aerosol optical thickness outliers due to unresolved clouds and snow. At the same time, the developed filter does not reduce the aerosol retrieval capability at high 1 km resolution in strongly inhomogeneous environments, such as near centers of the active fires. Despite significant improvement, the optical depth outliers in high spatial resolution data are and will remain the problem to be addressed by the application-dependent specialized filtering techniques.

Analysis of aerosol-cloud-precipitation interactions based on MODIS data

NASA Astrophysics Data System (ADS)

Cheng, Feng; Zhang, Jiahua; He, Junliang; Zha, Yong; Li, Qiannan; Li, Yunmei

2017-01-01

Aerosols exert an indirect impact on climate change via its impact on clouds by altering its radiative and optical properties which, in turn, changes the process of precipitation. Over recent years how to study the indirect climate effect of aerosols has become an important research topic. In this study we attempted to understand the complex mutual interactions among aerosols, clouds and precipitation through analysis of the spatial correlation between aerosol optical depth (AOD), cloud effective radius (CER) and precipitation during 2000-2012 in central-eastern China that has one of the highest concentrations of aerosols globally. With the assistance of moderate resolution imaging spectroradiometer (MODIS)-derived aerosol and cloud product data, this analysis focuses on regional differentiation and seasonal variation of the correlation in which in situ observed precipitation was incorporated. On the basis of the achieved results, we proposed four patterns depicting the mutual interactions between aerosols, clouds and precipitation. They characterize the indirect effects of aerosols on the regional scale. These effects can be summarized as complex seasonal variations and north-south regional differentiation over the study area. The relationship between AOD and CER is predominated mostly by the first indirect effect (the negative correlation between AOD and CER) in the north of the study area in the winter and spring seasons, and over the entire study area in the summer season. The relationship between CER and precipitation is dominated chiefly by the second indirect effect (the positive correlation between CER and precipitation) in the northern area in summer and over the entire study area in autumn. It must be noted that aerosols are not the factor affecting clouds and rainfall singularly. It is the joint effect of aerosols with other factors such as atmospheric dynamics that governs the variation in clouds and rainfall.

Uncertainty of passive imager cloud retrievals to instrument radiometry and model assumptions: Examples from MODIS Collection 6

NASA Astrophysics Data System (ADS)

Platnick, S.; Wind, G.; Amarasinghe, N.; Arnold, G. T.; Zhang, Z.; Meyer, K.; King, M. D.

2013-12-01

The optical and microphysical structure of clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness (COT) and effective particle radius (CER) are provided, as well as the derived water path (WP). The cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate retrieval datasets for various two-channel retrievals, typically a VIS/NIR channel paired with a 1.6, 2.1, and 3.7 μm spectral channel. The MOD06 forward model is derived from a homogeneous plane-parallel cloud. In Collection 5 processing (completed in 2007 with a modified Collection 5.1 completed in 2010), pixel-level retrieval uncertainties were calculated for the following non-3-D error sources: radiometry, surface spectral albedo, and atmospheric corrections associated with model analysis uncertainties (water vapor only). The latter error source includes error correlation across the retrieval spectral channels. Estimates of uncertainty in 1° aggregated (Level-3) means were also provided assuming unity correlation between error sources for all pixels in a grid for a single day, and zero correlation of error sources from one day to the next. In Collection 6 (expected to begin in late summer 2013) we expanded the uncertainty analysis to include: (a) scene-dependent calibration uncertainty that depends on new band and detector-specific Level 1B uncertainties, (b) new model error sources derived from the look-up tables which includes sensitivities associated with wind direction over the ocean and uncertainties in liquid water and ice effective variance, (c) thermal emission uncertainties in the 3.7 μm band associated with cloud and surface temperatures that are needed to extract reflected solar radiation from the total radiance signal, (d) uncertainty in the solar spectral irradiance at 3.7 μm, and (e) addition of stratospheric ozone uncertainty in visible atmospheric corrections. A summary of the approach and example Collection 6 results will be shown.

Constructing An Event Based Aerosol Product Under High Aerosol Loading Conditions

NASA Astrophysics Data System (ADS)

Levy, R. C.; Shi, Y.; Mattoo, S.; Remer, L. A.; Zhang, J.

2016-12-01

High aerosol loading events, such as the Indonesia's forest fire in Fall 2015 or the persistent wintertime haze near Beijing, gain tremendous interests due to their large impact on regional visibility and air quality. Understanding the optical properties of these events and further being able to simulate and predict these events are beneficial. However, it is a great challenge to consistently identify and then retrieve aerosol optical depth (AOD) from passive sensors during heavy aerosol events. Some reasons include:1). large differences between optical properties of high-loading aerosols and those under normal conditions, 2) spectral signals of optically thick aerosols can be mistaken with surface depending on aerosol types, and 3) Extremely optically thick aerosol plumes can also be misidentified as clouds due to its high optical thickness. Thus, even under clear-sky conditions, the global distribution of extreme aerosol events is not well captured in datasets such as the MODIS Dark-Target (DT) aerosol product. In this study, with the synthetic use of OMI Aerosol Index, MODIS cloud product, and operational DT product, the heavy smoke events over the seven sea region are identified and retrieved over the dry season. An event based aerosol product that would compensate the standard "global" aerosol retrieval will be created and evaluated. The impact of missing high AOD retrievals on the regional aerosol climatology will be studied using this newly developed research product.

Susceptibility of Aerosol Retrievals to Cirrus Contamination during the BASE-ASIA Campaign and at Global View

NASA Astrophysics Data System (ADS)

Huang, J.; Hsu, C.; Tsay, S.; Jeong, M.; Holben, B.; Berkoff, T.; Welton, E. J.

2010-12-01

Cirrus clouds, particularly subvisual high thin cirrus with low optical thickness, are difficult to be screened out in the operational aerosol retrieval algorithms. In this study, we jointly used ground measurements (AERONET, aerosol robotic network; MPLNET, micro-pulse lidar network) and satellite data (MODIS, moderate resolution imaging spectroradiometer; CALIPSO, cloud-aerosol lidar and infrared pathfinder satellite observations) to closely examine the susceptibility of satellite retrieved and ground measured aerosol optical thickness (AOT) to cirrus contamination. Special cases were selected at Phimai (102.56°E, 15.18°N, also known as Pimai), Thailand, during the Biomass-burning Aerosols in South East-Asia: Smoke Impact Assessment (BASE-ASIA) campaign (February-May 2006). By taking advantage of space-borne and ground lidars in detecting cirrus clouds, we conducted the statistical analysis by matching up concurrent cirrus and aerosol observations at four levels: MPLNET vs AERONET, MPLNET vs MODIS, CALIPSO vs AERONET, and CALIPSO vs MODIS. Results suggest that the susceptibility of current operational AERONET and MODIS AOT products to cirrus features strong regional and seasonal variability, particularly in cirrus prevailing regions. The values of AOT and aerosol particle size appear to be larger for cirrus-susceptible cases than those for confidently non-cirrus cases, a possible signature of cirrus contamination. To further assess cirrus-screening algorithms, we tested 8 MODIS-derived cirrus screening parameters against lidar observations for their performance and robustness on cirrus screening: apparent reflectance at 1.38μm (R1.38), cirrus reflectance at 0.66μm (CR0.66), CR0.66 cirrus flag, reflectance ratio between 1.38μm and 0.66μm (RR1.38/0.66), reflectance ratio between 1.38μm and 1.24μm (RR1.38/1.24), brightness temperature difference between 8.6μm and 11μm (BTD8.6-11), brightness temperature difference between 11μm and 12μm (BTD11-12), and cloud phase infrared approach (CPIR). The quantitative findings from the study suggest that particular caution and careful evaluations on cirrus contamination in the satellite and ground AOT measurements should be exercised before they are used for aerosol related climatic forcing studies.

Mapping Snow Grain Size over Greenland from MODIS

NASA Technical Reports Server (NTRS)

Lyapustin, Alexei; Tedesco, Marco; Wang, Yujie; Kokhanovsky, Alexander

2008-01-01

This paper presents a new automatic algorithm to derive optical snow grain size (SGS) at 1 km resolution using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. Differently from previous approaches, snow grains are not assumed to be spherical but a fractal approach is used to account for their irregular shape. The retrieval is conceptually based on an analytical asymptotic radiative transfer model which predicts spectral bidirectional snow reflectance as a function of the grain size and ice absorption. The analytical form of solution leads to an explicit and fast retrieval algorithm. The time series analysis of derived SGS shows a good sensitivity to snow metamorphism, including melting and snow precipitation events. Preprocessing is performed by a Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, which includes gridding MODIS data to 1 km resolution, water vapor retrieval, cloud masking and an atmospheric correction. MAIAC cloud mask (CM) is a new algorithm based on a time series of gridded MODIS measurements and an image-based rather than pixel-based processing. Extensive processing of MODIS TERRA data over Greenland shows a robust performance of CM algorithm in discrimination of clouds over bright snow and ice. As part of the validation analysis, SGS derived from MODIS over selected sites in 2004 was compared to the microwave brightness temperature measurements of SSM\\I radiometer, which is sensitive to the amount of liquid water in the snowpack. The comparison showed a good qualitative agreement, with both datasets detecting two main periods of snowmelt. Additionally, MODIS SGS was compared with predictions of the snow model CROCUS driven by measurements of the automatic whether stations of the Greenland Climate Network. We found that CROCUS grain size is on average a factor of two larger than MODIS-derived SGS. Overall, the agreement between CROCUS and MODIS results was satisfactory, in particular before and during the first melting period in mid-June. Following detailed time series analysis of SGS for four permanent sites, the paper presents SGS maps over the Greenland ice sheet for the March-September period of 2004.

Quantifying the radiative and microphysical impacts of fire aerosols on cloud dynamics in the tropics using temporally offset satellite observations

NASA Astrophysics Data System (ADS)

Tosca, M. G.; Diner, D. J.; Garay, M. J.; Kalashnikova, O.

2013-12-01

Anthropogenic fires in Southeast Asia and Central America emit smoke that affects cloud dynamics, meteorology, and climate. We measured the cloud response to direct and indirect forcing from biomass burning aerosols using aerosol retrievals from the Multi-angle Imaging SpectroRadiometer (MISR) and non-synchronous cloud retrievals from the MODerate resolution Imaging Spectroradiometer (MODIS) from collocated morning and afternoon overpasses. Level 2 data from thirty-one individual scenes acquired between 2006 and 2010 were used to quantify changes in cloud fraction, cloud droplet size, cloud optical depth and cloud top temperature from morning (10:30am local time) to afternoon (1:30pm local time) in the presence of varying aerosol burdens. We accounted for large-scale meteorological differences between scenes by normalizing observed changes to the mean difference per individual scene. Elevated AODs reduced cloud fraction and cloud droplet size and increased cloud optical depths in both Southeast Asia and Central America. In mostly cloudy regions, aerosols significantly reduced cloud fraction and cloud droplet sizes, but in clear skies, cloud fraction, cloud optical thickness and cloud droplet sizes increased. In clouds with vertical development, aerosols reduced cloud fraction via semi-direct effects but spurred cloud growth via indirect effects. These results imply a positive feedback loop between anthropogenic burning and cloudiness in both Central America and Southeast Asia, and are consistent with previous studies linking smoke aerosols to both cloud reduction and convective invigoration.

Enhanced clear sky reflectance near clouds: What can be learned from it about aerosol properties?

NASA Astrophysics Data System (ADS)

Marshak, A.; Varnai, T.; Wen, G.; Chiu, J.

2009-12-01

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 radiative interactions between clouds and cloud-free areas, also known as a cloud adjacency effect. The cloud adjacency effect is well observed in MODIS clear-sky data in the vicinity of clouds. Comparing with CALIPSO clear-sky backscatterer measurements, we show that this effect may be responsible for a large portion of the enhanced clear-sky reflectance observed by MODIS. Finally, 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.

Influence of Aerosols And Surface Reflectance On NO2 Retrieval Over China From 2005 to 2015

NASA Astrophysics Data System (ADS)

Liu, M.; Lin, J.

2016-12-01

Satellite observation is a powerful way to analysis annual and seasonal variations of nitrogen dioxide (NO2). However, much retrieval of vertical column densities (VCDs) of normally do not explicitly account for aerosol optical effects and surface reflectance anisotropy that vary with space and time. In traditional retrieval, aerosols' effects are often considered as cloud. However, China has complicated aerosols type and aerosol loading. Their optical properties may be very different from the cloud. Furthermore, China has undergone big changes in land use type in recent 10 years. Traditional climatology surface reflectance data may not have representation. In order to study spatial-temporal variation of and influences of these two factors on variations and trends, we use an improved retrieval method of VCDs over China, called the POMINO, based on measurements from the Ozone Monitoring Instrument (OMI), and we compare the results of without aerosol, without surface reflectance treatments and without both to the original POMINO product from 2005 to 2015. Furthermore, we will study correspondent spatial-temporal variations of aerosols, represented by MODIS aerosol optical depth (AOD) data and CALIOP extinction data; surface reflectance, represented by MODIS bidirectional reflectance distribution function (BRDF) data.

Cloud Properties of CERES-MODIS Edition 4 and CERES-VIIRS Edition 1

NASA Technical Reports Server (NTRS)

Sun-Mack, Sunny; Minnis, Patrick; Chang, Fu-Lung; Hong, Gang; Arduini, Robert; Chen, Yan; Trepte, Qing; Yost, Chris; Smith, Rita; Brown, Ricky;

Snow cover detection algorithm using dynamic time warping method and reflectances of MODIS solar spectrum channels

NASA Astrophysics Data System (ADS)

Lee, Kyeong-sang; Choi, Sungwon; Seo, Minji; Lee, Chang suk; Seong, Noh-hun; Han, Kyung-Soo

2016-10-01

Snow cover is biggest single component of cryosphere. The Snow is covering the ground in the Northern Hemisphere approximately 50% in winter season and is one of climate factors that affects Earth's energy budget because it has higher reflectance than other land types. Also, snow cover has an important role about hydrological modeling and water resource management. For this reason, accurate detection of snow cover acts as an essential element for regional water resource management. Snow cover detection using satellite-based data have some advantages such as obtaining wide spatial range data and time-series observations periodically. In the case of snow cover detection using satellite data, the discrimination of snow and cloud is very important. Typically, Misclassified cloud and snow pixel can lead directly to error factor for retrieval of satellite-based surface products. However, classification of snow and cloud is difficult because cloud and snow have similar optical characteristics and are composed of water or ice. But cloud and snow has different reflectance in 1.5 1.7 μm wavelength because cloud has lower grain size and moisture content than snow. So, cloud and snow shows difference reflectance patterns change according to wavelength. Therefore, in this study, we perform algorithm for classifying snow cover and cloud with satellite-based data using Dynamic Time Warping (DTW) method which is one of commonly used pattern analysis such as speech and fingerprint recognitions and reflectance spectral library of snow and cloud. Reflectance spectral library is constructed in advance using MOD21km (MODIS Level1 swath 1km) data that their reflectance is six channels including 3 (0.466μm), 4 (0.554μm), 1 (0.647μm), 2 (0.857μm), 26 (1.382μm) and 6 (1.629μm). We validate our result using MODIS RGB image and MOD10 L2 swath (MODIS swath snow cover product). And we use PA (Producer's Accuracy), UA (User's Accuracy) and CI (Comparison Index) as validation criteria. The result of our study detect as snow cover in the several regions which are did not detected as snow in MOD10 L2 and detected as snow cover in MODIS RGB image. The result of our study can improve accuracy of other surface product such as land surface reflectance and land surface emissivity. Also it can use input data of hydrological modeling.

Long Term Cloud Property Datasets From MODIS and AVHRR Using the CERES Cloud Algorithm

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Bedka, Kristopher M.; Doelling, David R.; Sun-Mack, Sunny; Yost, Christopher R.; Trepte, Qing Z.; Bedka, Sarah T.; Palikonda, Rabindra; Scarino, Benjamin R.; Chen, Yan;

Scientific impact of MODIS C5 calibration degradation and C6+ improvements

NASA Astrophysics Data System (ADS)

Lyapustin, A.; Wang, Y.; Xiong, X.; Meister, G.; Platnick, S.; Levy, R.; Franz, B.; Korkin, S.; Hilker, T.; Tucker, J.; Hall, F.; Sellers, P.; Wu, A.; Angal, A.

2014-12-01

The Collection 6 (C6) MODIS (Moderate Resolution Imaging Spectroradiometer) land and atmosphere data sets are scheduled for release in 2014. C6 contains significant revisions of the calibration approach to account for sensor aging. This analysis documents the presence of systematic temporal trends in the visible and near-infrared (500 m) bands of the Collection 5 (C5) MODIS Terra and, to lesser extent, in MODIS Aqua geophysical data sets. Sensor degradation is largest in the blue band (B3) of the MODIS sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple MODIS C5 products including the dark target algorithm's aerosol optical depth over land and Ångström exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface reflectance and vegetation indices, including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). As the C5 production will be maintained for another year in parallel with C6, one objective of this paper is to raise awareness of the calibration-related trends for the broad MODIS user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6+ calibration of the MODIS data set which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of MODIS Terra since about 2007, as well as detrending and Terra-Aqua cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the MODIS ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface reflectance (SR) records along with spectral distortions of SR. Using the multiangle implementation of atmospheric correction (MAIAC) algorithm over deserts, we have also developed a detrending and cross-calibration method which removes residual decadal trends on the order of several tenths of 1% of the top-of-atmosphere (TOA) reflectance in the visible and near-infrared MODIS bands B1-B4, and provides a good consistency between the two MODIS sensors. MAIAC analysis over the southern USA shows that the C6+ approach removed an additional negative decadal trend of Terra ΔNDVI ~ 0.01 as compared to Aqua data. This change is particularly important for analysis of vegetation dynamics and trends in the tropics, e.g., Amazon rainforest, where the morning orbit of Terra provides considerably more cloud-free observations compared to the afternoon Aqua measurements.

Scientific Impact of MODIS C5 Calibration Degradation and C6+ Improvements

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Xiong, X.; Meister, G.; Platnick, S.; Levy, R.; Franz, B.; Korkin, S.; Hilker, T.; Tucker, J.;

MODIS Views Variations in Cloud Types

NASA Technical Reports Server (NTRS)

2002-01-01

This MODIS image, centered over the Great Lakes region in North America, shows a variety of cloud types. The clouds at the top of the image, colored pink, are cold, high-level snow and ice clouds, while the neon green clouds are lower-level water clouds. Because different cloud types reflect and emit radiant energy differently, scientists can use MODIS' unique data set to measure the sizes of cloud particles and distinguish between water, snow, and ice clouds. This scene was acquired on Feb. 24, 2000, and is a red, green, blue composite of bands 1, 6, and 31 (0.66, 1.6, and 11.0 microns, respectively). Image by Liam Gumley, Space Science and Engineering Center, University of Wisconsin-Madison

Using High-Resolution Airborne Remote Sensing to Study Aerosol Near Clouds

NASA Technical Reports Server (NTRS)

Levy, Robert; Munchak, Leigh; Mattoo, Shana; Marshak, Alexander; Wilcox, Eric; Gao, Lan; Yorks, John; Platnick, Steven

2016-01-01

The horizontal space in between clear and cloudy air is very complex. This so-called twilight zone includes activated aerosols that are not quite clouds, thin cloud fragments that are not easily observable, and dying clouds that have not quite disappeared. This is a huge challenge for satellite remote sensing, specifically for retrieval of aerosol properties. Identifying what is cloud versus what is not cloud is critically important for attributing radiative effects and forcings to aerosols. At the same time, the radiative interactions between clouds and the surrounding media (molecules, surface and aerosols themselves) will contaminate retrieval of aerosol properties, even in clear skies. Most studies on aerosol cloud interactions are relevant to moderate resolution imagery (e.g. 500 m) from sensors such as MODIS. Since standard aerosol retrieval algorithms tend to keep a distance (e.g. 1 km) from the nearest detected cloud, it is impossible to evaluate what happens closer to the cloud. During Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS), the NASA ER-2 flew with the enhanced MODIS Airborne Simulator (eMAS), providing MODIS-like spectral observations at high (50 m) spatial resolution. We have applied MODIS-like aerosol retrieval for the eMAS data, providing new detail to characterization of aerosol near clouds. Interpretation and evaluation of these eMAS aerosol retrievals is aided by independent MODIS-like cloud retrievals, as well as profiles from the co-flying Cloud Physics Lidar (CPL). Understanding aerosolcloud retrieval at high resolution will lead to better characterization and interpretation of long-term, global products from lower resolution (e.g.MODIS) satellite retrievals.

Examination of Regional Trends in Cloud Properties over Surface Sites Derived from MODIS and AVHRR using the CERES Cloud Algorithm

NASA Astrophysics Data System (ADS)

Smith, W. L., Jr.; Minnis, P.; Bedka, K. M.; Sun-Mack, S.; Chen, Y.; Doelling, D. R.; Kato, S.; Rutan, D. A.

2017-12-01

Recent studies analyzing long-term measurements of surface insolation at ground sites suggest that decadal-scale trends of increasing (brightening) and decreasing (dimming) downward solar flux have occurred at various times over the last century. Regional variations have been reported that range from near 0 Wm-2/decade to as large as 9 Wm-2/decade depending on the location and time period analyzed. The more significant trends have been attributed to changes in overhead clouds and aerosols, although quantifying their relative impacts using independent observations has been difficult, owing in part to a lack of consistent long-term measurements of cloud properties. This paper examines new satellite based records of cloud properties derived from MODIS (2000-present) and AVHRR (1981- present) data to infer cloud property trends over a number of surface radiation sites across the globe. The MODIS cloud algorithm was developed for the NASA Clouds and the Earth's Radiant Energy System (CERES) project to provide a consistent record of cloud properties to help improve broadband radiation measurements and to better understand cloud radiative effects. The CERES-MODIS cloud algorithm has been modified to analyze other satellites including the AVHRR on the NOAA satellites. Compared to MODIS, obtaining consistent cloud properties over a long period from AVHRR is a much more significant challenge owing to the number of different satellites, instrument calibration uncertainties, orbital drift and other factors. Nevertheless, both the MODIS and AVHRR cloud properties will be analyzed to determine trends, and their level of consistency and correspondence with surface radiation trends derived from the ground-based radiometer data. It is anticipated that this initial study will contribute to an improved understanding of surface solar radiation trends and their relationship to clouds.

Validation of CERES-MODIS Arctic cloud properties using CloudSat/CALIPSO and ARM NSA observations

NASA Astrophysics Data System (ADS)

Giannecchini, K.; Dong, X.; Xi, B.; Minnis, P.; Kato, S.

2011-12-01

The traditional passive satellite studies of cloud properties in the Arctic are often affected by the complex surface features present across the region. Nominal visual and thermal contrast exists between Arctic clouds and the snow- and ice-covered surfaces beneath them, which can lead to difficulties in satellite retrievals of cloud properties. However, the addition of active sensors to the A-Train constellation of satellites has increased the availability of validation sources for cloud properties derived from passive sensors in the data-sparse high-latitude regions. In this study, Arctic cloud fraction and cloud heights derived from the NASA CERES team (CERES-MODIS) have been compared with CloudSat/CALIPSO and DOE ARM NSA radar-lidar observations over Barrow, AK, for the two-year period from 2007 to 2008. An Arctic-wide comparison of cloud fraction and height between CERES-MODIS and CloudSat/CALIPSO was then conducted for the same time period. The CERES-MODIS cloud properties, which include cloud fraction and cloud effective heights, were retrieved using the 4-channel VISST (Visible Infrared Solar-Infrared Split-window Technique) [Minnis et al.,1995]. CloudSat/CALIPSO cloud fraction and cloud-base and -top heights were from version RelB1 data products determined by both the 94 GHz radar onboard CloudSat and the lidar on CALIPSO with a vertical resolution of 30 m below 8.2 km and 60 m above. To match the surface and satellite observations/retrievals, the ARM surface observations were averaged into 3-hour intervals centered at the time of the satellite overpass, while satellite observations were averaged within a 3°x3° grid box centered on the Barrow site. The preliminary results have shown that all observed CFs have peaks during April-May and September-October, and dips during winter months (January-February) and summer months (June-July) during the study period of 2007-2008. ARM radar-lidar and CloudSat/CALIPSO show generally good agreement in CF (0.79 vs. 0.74), while CERES-MODIS derived values are much lower (0.60). CERES-MODIS derived cloud effective height (2.7 km) falls between the CloudSat/CALIPSO derived cloud base (0.6 km) and top (6.4 km) and the ARM ceilometers and MMCR derived cloud base (0.9 km) and radar derived cloud top (5.8 km). When extended to the entire Arctic, although the CERES-MODIS and Cloudsat/CALIPSO derived annual mean CFs agree within a few percents, there are significant differences over several regions, and the maximum cloud heights derived from CloudSat/CALIPSO (13.4 km) and CERES-MODIS (10.7 km) show the largest disagreement during early spring.

MODIS Collection 6 Clear Sky Restoral (CSR): Filtering Cloud Mast 'Not Clear' Pixels

NASA Technical Reports Server (NTRS)

Meyer, Kerry G.; Platnick, Steven Edward; Wind, Galina; Riedi, Jerome

2014-01-01

Correctly identifying cloudy pixels appropriate for the MOD06 cloud optical and microphysical property retrievals is accomplished in large part using results from the MOD35 1km cloud mask tests (note there are also two 250m subpixel cloud mask tests that can convert the 1km cloudy designations to clear sky). However, because MOD35 is by design clear sky conservative (i.e., it identifies "not clear" pixels), certain situations exist in which pixels identified by MOD35 as "cloudy" are nevertheless likely to be poor retrieval candidates. For instance, near the edge of clouds or within broken cloud fields, a given 1km MODIS field of view (FOV) may in fact only be partially cloudy. This can be problematic for the MOD06 retrievals because in these cases the assumptions of a completely overcast homogenous cloudy FOV and 1-dimensional plane-parallel radiative transfer no longer hold, and subsequent retrievals will be of low confidence. Furthermore, some pixels may be identified by MOD35 as "cloudy" for reasons other than the presence of clouds, such as scenes with thick smoke or lofted dust, and should therefore not be retrieved as clouds. With such situations in mind, a Clear Sky Restoral (CSR) algorithm was introduced in C5 that attempts to identify pixels expected to be poor retrieval candidates. Table 1 provides SDS locations for CSR and partly cloudy (PCL) pixels.

Aerosol Optical Depth Changes in Version 4 CALIPSO Level 2 Product

NASA Astrophysics Data System (ADS)

Kim, M. H.; Omar, A. H.; Tackett, J. L.; Vaughan, M.; Winker, D. M.; Trepte, C. R.; Hu, Y.; Liu, Z.

2017-12-01

The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) version 4 (V4) products were released in November 2016 with substantial enhancements. There have been improvements in the V4 CALIOP level 2 aerosol optical depth (AOD) compared to V3 (version 3) due to various factors. To analyze the AOD changes we selected every bin whose the vertical feature mask (VFM) is determined as aerosol for either V3 or V4 (or both) from the CALIOP level 2 profile product from 2007 to 2009. We isolated the AOD differences due to changes in six factors: layer detection, cloud-aerosol discrimination (CAD), surface detection, stratospheric aerosol, aerosol subtype, and lidar ratio. Total mean (± standard deviation) column AOD increases from V3 in V4 by 0.051±0.296 and 0.075±0.383 for daytime and nighttime, respectively. Dominant reasons for AOD change are differences in aerosol layer detection, CAD, aerosol subtype, and lidar ratio between V3 and V4 with AOD changes of 0.011 (0.027), 0.018 (0.015), -0.002 (0.009), 0.016 (0.017) for daytime (nighttime), respectively. CALIOP AOD was compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) and Aerosol Robotic Network (AERONET) for both V3 and V4. The comparison shows that mean AOD biases with AERONET and MODIS (collection 6, over ocean) decrease in V4 compared to V3. Mean AOD difference with MODIS for cloud-screened data changes from -0.012±0.079 in V3 to -0.008±0.067 in V4. Mean AOD difference with AERONET is -0.071±0.207 and -0.023±0.233 for V3 and V4, respectively. There is reduction in the CALIOP AOD negative bias with respect to both MODIS and AERONET.

Evaluation and Assimilation of Cloud Cleared Radiances for AIRS in GEOS-5

NASA Technical Reports Server (NTRS)

Liu, Hui-chun

2008-01-01

The use of clear (cloud-free) channels for AIRS in GEOS-5 had shown positive impact on forecast skills in both hemispheres. However, improvements in forecast skills due to the assimilation of AIRS data are less impressive since the number of assimilated channels from AIRS is much larger than that from other Infrared sounders such as HIRS-3 onboard NOAA 15-17 satellites. This limitation of AIRS radiance data to improve the forecast skill is mainly due to the fact that channels capable of peaking below clouds are not used in the assimilation and yet those have highest vertical resolving capability of AIRS instrument are concentrated in the lower troposphere. On average, the percentage of AIRS footprints completely clear for all channels is less than 10%. The percentage of assimilated AIRS channel radiances however ranges from 100% for channels peaking in the upper stratosphere, above the cloud, to no more that 5% in the lower atmosphere due to cloud contamination. Our current ability to model and predict clouds accurately in global model, and to fully characterize and parameterize optical properties of cloud particles in radiative transfer model are the two major obstacles prohibiting us to use cloudy radiance directly in the assimilation. To further improve forecast skill using AIRS data, we ought to use the channels peaking below the clouds in the troposphere, which can be accomplished by assimilating cloud-cleared radiance. The cloud-cleared radiance data for AIRS used in this study were obtained from optimal cloud clearing procedures developed by researchers at CIMSS of University of Wisconsin at Madison to retrieve clear column radiances for all AIRS channels by collocating multi-band MODIS IR clear radiance observations with the AIRS cloudy radiances on a single footprint basis. Two adjacent AIRS cloudy footprints are used to retrieve one AIRS cloud-cleared radiance spectrum and no background information (first guess) is needed. To assimilate the cloud-cleared radiance data, the errors of the cloud-cleared radiances need to be addressed. The details of convolving AIRS radiances with MODIS spectral response function and comparison with MODIS-measured cloud-free radiance will be presented. The range of errors of cloud-cleared radiances for AIRS using collocated MODIS clear and near-by AIRS clear data will be shown. The NASA. global data assimilation model, GEOS-5, is used to evaluate and assimilate the cloud-cleared radiance for AIRS. The residues between the cloud-cleared brightness temperature and the simulated brightness temperature from background (i.e., OMFs) will be investigated. The quality control procedures will be documented based on error estimation and the OMFs. Finally, the impacts between assimilation of clear channel radiances and cloud-cleared radiances will be addressed.

Integrated Cloud-Aerosol-Radiation Product using CERES, MODIS, CALIPSO and CloudSat Data

NASA Technical Reports Server (NTRS)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Gibson, Sharon; Yi, Yuhong; Trepte, Qing; Wielicki, Bruce; Kato, Seiji; Winker, Dave

2007-01-01

This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and radiation using the combined NASA A-Train data from the Aqua Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat radar are merged with the integrated column cloud properties from the CERES-MODIS analyses. The active and passive datasets are compared to determine commonalities and differences in order to facilitate the development of a 3- dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint. Preliminary results from the comparisons for April 2007 reveal that the CERES-MODIS global cloud amounts are, on average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

Integrated cloud-aerosol-radiation product using CERES, MODIS, CALIPSO, and CloudSat data

NASA Astrophysics Data System (ADS)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Gibson, Sharon; Yi, Yuhong; Trepte, Qing; Wielicki, Bruce; Kato, Seiji; Winker, Dave; Stephens, Graeme; Partain, Philip

2007-10-01

This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and radiation using the combined NASA A-Train data from the Aqua Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat radar are merged with the integrated column cloud properties from the CERES-MODIS analyses. The active and passive datasets are compared to determine commonalities and differences in order to facilitate the development of a 3-dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint. Preliminary results from the comparisons for April 2007 reveal that the CERES-MODIS global cloud amounts are, on average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

Laser Pulse Bidirectional Reflectance from CALIPSO Mission

NASA Technical Reports Server (NTRS)

Lu, Xiaomei; Hu, Yongxiang; Yang, Yuekui; Liu, Zhaoyan; Vaughan, Mark; Lucker, Patricia; Trepte, Charles

2017-01-01

In this Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) study, we present a simple way of determining laser pulse bidirectional reflectance over snow/ice surface using the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) 532 nanometer polarization channels' measurements. The saturated laser pulse returns from snow and ice surfaces are recovered based on surface tail information. The method overview and initial assessment of the method performance will be presented. The retrieved snow surface bidirectional reflectance is compared with reflectance from both CALIOP cloud cover regions and Moderate Resolution Imaging Spectroradiometer (Earth Observing System (EOS)) (MODIS) Bi-directional Reflectance Distribution Function (BRDF) / Albedo model parameters. The comparisons show that the snow surface bidirectional reflectance over Antarctica for saturation region are generally reliable with a mean value of about 0.90 plus or minus 0.10, while the mean surface reflectance from cloud cover region is about 0.84 plus or minus 0.13 and the calculated MODIS reflectance at 555 nanometers from the BRDF / Albedo model with near nadir illumination and viewing angles is about 0.96 plus or minus 0.04. The comparisons here demonstrate that the snow surface reflectance underneath the cloud with cloud optical depth of about 1 is significantly lower than that for a clear sky condition.

Mesoscale modeling of smoke transport over Central Africa: influences of trade winds, subtropical high, ITCZ and vertical statistics

NASA Astrophysics Data System (ADS)

Yang, Z.; Wang, J.; Hyer, E. J.; Ichoku, C. M.

2012-12-01

A fully-coupled meteorology-chemistry-aerosol model, Weather Research and Forecasting model with Chemistry (WRF-Chem), is used to simulate the transport of smoke aerosol over the Central Africa during February 2008. Smoke emission used in this study is specified from the Fire Locating and Modeling of Burning Emissions (FLAMBE) database derived from Moderate Resolution Imaging Spectroradiometer (MODIS) fire products. Model performance is evaluated using MODIS true color images, measured Aerosol Optical Depth (AOD) from space-borne MODIS (550 nm) and ground-based AERONET (500 nm), and Cloud-Aerosol Lidar data with Orthogonal Polarization (CALIOP) level 1 and 2 products. The simulated smoke transport is in good agreement with the validation data. Analyzing from three smoke events, smoke is constrained in a narrow belt between the Equator and 10°N near the surface, with the interplay of trade winds, subtropical high, and ITCZ. At the 700 hpa level, smoke expands farther meridionally. Topography blocks the smoke transport to the southeast of study area, because of high mountains located near the Great Rift Valley region. The simulation with injection height of 650 m is consistent with CALIOP measurements. The particular phenomenon, aerosol above cloud, is studied statistically from CALIOP observations. The total percentage of aerosol above cloud is about 5%.

Evaluation of multi-layer cloud detection based on MODIS CO2-slicing algorithm with CALIPSO-CloudSat measurements.

NASA Astrophysics Data System (ADS)

Viudez-Mora, A.; Kato, S.; Smith, W. L., Jr.; Chang, F. L.

2016-12-01

Knowledge of the vertical cloud distribution is important for a variety of climate and weather applications. The cloud overlapping variations greatly influence the atmospheric heating/cooling rates, with implications for the surface-troposphere radiative balance, global circulation and precipitation. Additionally, an accurate knowledge of the multi-layer cloud distribution in real-time can be used in applications such safety condition for aviation through storms and adverse weather conditions. In this study, we evaluate a multi-layered cloud algorithm (Chang et al. 2005) based on MODIS measurements aboard Aqua satellite (MCF). This algorithm uses the CO2-slicing technique combined with cloud properties determined from VIS, IR and NIR channels to locate high thin clouds over low-level clouds, and retrieve the τ of each layer. We use CALIPSO (Winker et. al, 2010) and CloudSat (Stephens et. al, 2002) (CLCS) derived cloud vertical profiles included in the C3M data product (Kato et al. 2010) to evaluate MCF derived multi-layer cloud properties. We focus on 2 layer overlapping and 1-layer clouds identified by the active sensors and investigate how well these systems are identified by the MODIS multi-layer technique. The results show that for these multi-layered clouds identified by CLCS, the MCF correctly identifies about 83% of the cases as multi-layer. However, it is found that the upper CTH is underestimated by about 2.6±0.4 km, because the CO2-slicing technique is not as sensitive to the cloud physical top as the CLCS. The lower CTH agree better with differences found to be about 1.2±0.5 km. Another outstanding issue for the MCF approach is the large number of multi-layer false alarms that occur in single-layer conditions. References: Chang, F.-L., and Z. Li, 2005: A new method for detection of cirrus overlapping water clouds and determination of their optical properties. J. Atmos. Sci., 62. Kato, S., et al. (2010), Relationships among cloud occurrence frequency, overlap, and effective thickness derived from CALIPSO and CloudSat merged cloud vertical profiles, J. Geophys. Res., 115. Stephens, G. L., et al. (2002), The CloudSat mission and A-Train, Bull. Am. Meteorol. Soc., 83. Winker, D. M., et al., 2010: The CALIPSO Mission: A global 3D view of aerosols and clouds. Bull. Amer. Meteor. Soc., 91.

Retrieval of Absorbing Aerosols Above Clouds retrieval over the South East Atlantic Ocean from MSG/SEVIRI

NASA Astrophysics Data System (ADS)

Peers, F.; Haywood, J. M.; Francis, P. N.; Meyer, K.; Platnick, S. E.

2017-12-01

Over the South East Atlantic Ocean, biomass burning aerosols from Southern Africa are frequently observed above clouds during fire season. However, the quantification of their interactions with both radiations and clouds remains uncertain because of a lack of information on aerosol properties and on their interaction process. In the last decade, methods have been developed to retrieve aerosol optical properties above clouds from satellite measurements, especially over the South East Atlantic Ocean. Most of these methods have been applied to polar orbiting instruments which prevent the analysis of aerosols and clouds at a sub-daily scale. With its wide spatial coverage and its high temporal resolution, the geostationary instrument SEVIRI, on board the MSG platform, offers a unique opportunity to monitor aerosols in this region and to evaluate their impact on clouds and their radiative effects. In this study, we will investigate the possibility of retrieving simultaneously aerosol and cloud properties (i.e. aerosol and cloud optical thicknesses and cloud droplet effective radius) when aerosols are located above clouds. The retrieved properties will then be compared with the ones obtained from MODIS [Meyer et al., 2015] as well as observations from the CLARIFY-2017 field campaign.

Estimate of the Aerosol Anthropogenic Component and Focusing from Satellite Data

NASA Technical Reports Server (NTRS)

Kaufman, Yoram; Remer, Lorraine A.; Chin, Mian

2004-01-01

Satellite measurements of aerosol do not contain information on the chemical composition needed to resolve anthropogenic vs. natural aerosol components. Besides, the same chemical species can have natural and anthropogenic origins. However the ability of the new satellite instruments (MODIS, MISR, POLDER) to distinguish fine from coarse aerosols over the oceans, can be used as a signature of the presence of anthropogenic component and used to measure the fraction of the aerosol originating from anthropogenic activity with an uncertainty of 10 percent for aerosol optical thickness larger than 0.1. We develop the methods and investigated it using model calculations (GOCART) and satellite data (MODIS). Preliminary application to 2 years of global MODIS data shows that 0.200.08 of the aerosol optical thickness and radiative effect has anthropogenic origin. The resultant aerosol forcing over cloud free oceans is 1.30.6 W/sq m, larger than model simulations. Further research until the presentation will probably modify these values.

Effect of Cloud Fraction on Near-Cloud Aerosol Behavior Based on MODIS and CALIPSO Observations

NASA Technical Reports Server (NTRS)

Marshak, A.; Varnai, T.; Yang, W.

2015-01-01

Organizers of the MODIS-VIIRS Science Team Meeting, held May 18-22, 2015 in Silver Spring, MD plan to post the presentations and posters to the NASA MODIS website: http:modis.gsfc.nasa.govsci_teammeetings201505index.php. The MODIS Science Team Meeting is held twice a year, so that the members of the science team may assemble and discuss data they have collected, ideas they have formed, and future issues that apply to the MODIS Mission.

The impact of aerosol vertical distribution on aerosol optical depth retrieval using CALIPSO and MODIS data: Case study over dust and smoke regions

NASA Astrophysics Data System (ADS)

Wu, Yerong; de Graaf, Martin; Menenti, Massimo

2017-08-01

Global quantitative aerosol information has been derived from MODerate Resolution Imaging SpectroRadiometer (MODIS) observations for decades since early 2000 and widely used for air quality and climate change research. However, the operational MODIS Aerosol Optical Depth (AOD) products Collection 6 (C6) can still be biased, because of uncertainty in assumed aerosol optical properties and aerosol vertical distribution. This study investigates the impact of aerosol vertical distribution on the AOD retrieval. We developed a new algorithm by considering dynamic vertical profiles, which is an adaptation of MODIS C6 Dark Target (C6_DT) algorithm over land. The new algorithm makes use of the aerosol vertical profile extracted from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements to generate an accurate top of the atmosphere (TOA) reflectance for the AOD retrieval, where the profile is assumed to be a single layer and represented as a Gaussian function with the mean height as single variable. To test the impact, a comparison was made between MODIS DT and Aerosol Robotic Network (AERONET) AOD, over dust and smoke regions. The results show that the aerosol vertical distribution has a strong impact on the AOD retrieval. The assumed aerosol layers close to the ground can negatively bias the retrievals in C6_DT. Regarding the evaluated smoke and dust layers, the new algorithm can improve the retrieval by reducing the negative biases by 3-5%.

Improvement in the cloud mask for Terra MODIS mitigated by electronic crosstalk correction in the 6.7 μm and 8.5 μm channels

NASA Astrophysics Data System (ADS)

Sun, Junqiang; Madhavan, S.; Wang, M.

2016-09-01

MODerate resolution Imaging Spectroradiometer (MODIS), a remarkable heritage sensor in the fleet of Earth Observing System for the National Aeronautics and Space Administration (NASA) is in space orbit on two spacecrafts. They are the Terra (T) and Aqua (A) platforms which tracks the Earth in the morning and afternoon orbits. T-MODIS has continued to operate over 15 years easily surpassing the 6 year design life time on orbit. Of the several science products derived from MODIS, one of the primary derivatives is the MODIS Cloud Mask (MOD035). The cloud mask algorithm incorporates several of the MODIS channels in both reflective and thermal infrared wavelengths to identify cloud pixels from clear sky. Two of the thermal infrared channels used in detecting clouds are the 6.7 μm and 8.5 μm. Based on a difference threshold with the 11 μm channel, the 6.7 μm channel helps in identifying thick high clouds while the 8.5 μm channel being useful for identifying thin clouds. Starting 2010, it had been observed in the cloud mask products that several pixels have been misclassified due to the change in the thermal band radiometry. The long-term radiometric changes in these thermal channels have been attributed to the electronic crosstalk contamination. In this paper, the improvement in cloud detection using the 6.7 μm and 8.5 μm channels are demonstrated using the electronic crosstalk correction. The electronic crosstalk phenomena analysis and characterization were developed using the regular moon observation of MODIS and reported in several works. The results presented in this paper should significantly help in improving the MOD035 product, maintaining the long term dataset from T-MODIS which is important for global change monitoring.

Modeling the Impact of Drizzle and 3D Cloud Structure on Remote Sensing of Effective Radius

NASA Technical Reports Server (NTRS)

Platnick, Steven; Zinner, Tobias; Ackerman, S.

2008-01-01

Remote sensing of cloud particle size with passive sensors like MODIS is an important tool for cloud microphysical studies. As a measure of the radiatively relevant droplet size, effective radius can be retrieved with different combinations of visible through shortwave infrared channels. MODIS observations sometimes show significantly larger effective radii in marine boundary layer cloud fields derived from the 1.6 and 2.1 pm channel observations than for 3.7 pm retrievals. Possible explanations range from 3D radiative transport effects and sub-pixel cloud inhomogeneity to the impact of drizzle formation on the droplet distribution. To investigate the potential influence of these factors, we use LES boundary layer cloud simulations in combination with 3D Monte Carlo simulations of MODIS observations. LES simulations of warm cloud spectral microphysics for cases of marine stratus and broken stratocumulus, each for two different values of cloud condensation nuclei density, produce cloud structures comprising droplet size distributions with and without drizzle size drops. In this study, synthetic MODIS observations generated from 3D radiative transport simulations that consider the full droplet size distribution will be generated for each scene. The operational MODIS effective radius retrievals will then be applied to the simulated reflectances and the results compared with the LES microphysics.

Analysis of Co-Located MODIS and CALIPSO Observations Near Clouds

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Marshak, Alexander

2011-01-01

The purpose of this paper is to help researchers combine data from different satellites and thus gain new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects, For this, the paper explores whether cloud information from the Aqua satellite's MODIS instrument can help characterize systematic aerosol changes near clouds by refining earlier perceptions of these changes that were based on the CALIPSO satellite's CALIOP instrument. Similar to a radar but using visible and ncar-infrared light, CALIOP sends out laser pulses and provides aerosol and cloud information along a single line that tracks the satellite orbit by measuring the reflection of its pulses. In contrast, MODIS takes images of reflected sunlight and emitted infrared radiation at several wavelengths, and covers wide areas around the satellite track. This paper analyzes a year-long global dataset covering all ice-free oceans, and finds that MODIS can greatly help the interpretation of CALIOP observations, especially by detecting clouds that lie outside the line observed by CALlPSO. The paper also finds that complications such as differences in view direction or clouds drifting in the 72 seconds that elapse between MODIS and CALIOP observations have only a minor impact. The study also finds that MODIS data helps refine but does not qualitatively alter perceptions of the systematic aerosol changes that were detected in earlier studies using only CALIOP data. It then proposes a statistical approach to account for clouds lying outside the CALIOP track even when MODIS cannot as reliably detect low clouds, for example at night or over ice. Finally, the paper finds that, because of variations in cloud amount and type, the typical distance to clouds in maritime clear areas varies with season and location. The overall median distance to clouds in maritime clear areas around 4-5 km. The fact that half of all clear areas is closer than 5 km to clouds implies that pronounced near-cloud changes in aerosol properties have significant implications for overall clear-sky characteristics, including the radiative impact of aerosols.

Validation of MODIS Aerosol Retrievals during PRIDE

NASA Technical Reports Server (NTRS)

Levy, R.; Remier, L.; Kaufman, Y.; Kleidman, R.; Holben, B.; Russell, P.; Livingston, J.; Einaudi, Franco (Technical Monitor)

2000-01-01

The Puerto Rico Dust Experiment (PRIDE) was held in Roosevelt Roads, Puerto Rico from June 26 to July 24, 2000. It was intended to study the radiative and microphysical properties of Saharan dust transported into Puerto Rico. PRIDE had the unique distinction of being the first major field experiment to allow direct comparison of aerosol retrievals from MODIS (MODerate Imaging Spectro-radiometer - aboard the Terra satellite) with data from a variety of ground, shipboard and air-based instruments. Over the ocean the MODIS algorithm retrieves optical depth as well as information about the aerosol's size. During PRIDE, MODIS passed over Roosevelt Roads approximately once per day during daylight hours. Due to sunglint and clouds over Puerto Rico, aerosol retrievals can be made from only about half the MODIS scenes. In this study we try to "validate" our aerosol retrievals by comparing to measurements taken by sun-photometers from multiple platforms, including: Cimel (AERONET) from the ground, Microtops (handheld) from ground and ship, and the NASA-Ames sunphotometer from the air.

Assessing cloud radiative effects on tropospheric photolysis rates and key oxidants during aircraft campaigns using satellite cloud observations and a global chemical transport model

NASA Astrophysics Data System (ADS)

Zhang, B.; Liu, H.; Crawford, J. H.; Chen, G.; Voulgarakis, A.; Fairlie, T. D.; Duncan, B. N.; Ham, S. H.; Kato, S.; Payer Sulprizio, M.; Yantosca, R.

2017-12-01

Clouds affect tropospheric photochemistry through modifying solar radiation that determines photolysis rates. Observational and modeling studies have indicated that photolysis rates are enhanced above and in the upper portion of cloud layers and are reduced below optically thick clouds due to their dominant backscattering effect. However, large uncertainties exist in the representation of cloud spatiotemporal (especially vertical) distributions in global models, which makes understanding of cloud radiative effects on tropospheric chemistry challenging. Our previous study using a global 3-D chemical transport model (GEOS-Chem) driven by various meteorological data sets showed that the radiative effects of clouds on photochemistry are more sensitive to the differences in the vertical distribution of clouds than to those in the magnitude of column cloud optical depths. In this work, we evaluate monthly mean cloud optical properties and distributions in the MERRA-2 reanalysis with those in C3M, a 3-D cloud data product developed at NASA Langley Research Center and merged from multiple A-Train satellite (CERES, CloudSat, CALIPSO, and MODIS) observations. We conduct tropospheric chemistry simulations for the periods of several aircraft campaigns, including ARCTAS (April, June-July, 2008), DC3 (May-June, 2012), and SEAC4RS (August-September, 2013) with GEOS-Chem driven by MERRA-2. We compare model simulations with and without constraints of cloud optical properties and distributions from C3M, and evaluate model photolysis rates (J[O1D] and J[NO2]) and key oxidants (e.g., OH and ozone) with aircraft profile measurements. We will assess whether the constraints provided by C3M improve model simulations of photolysis rates and oxidants as well as their variabilities.

Evaluation of RRTMG and Fu-Liou RTM Performance against LBLRTM-DISORT Simulations and CERES Data in terms of Ice Clouds Radiative Effects

NASA Astrophysics Data System (ADS)

Gu, B.; Yang, P.; Kuo, C. P.; Mlawer, E. J.

2017-12-01

Evaluation of RRTMG and Fu-Liou RTM Performance against LBLRTM-DISORT Simulations and CERES Data in terms of Ice Clouds Radiative Effects Boyan Gu1, Ping Yang1, Chia-Pang Kuo1, Eli J. Mlawer2 Department of Atmospheric Sciences, Texas A&M University, College Station, TX 77843, USA Atmospheric and Environmental Research (AER), Lexington, MA 02421, USA Ice clouds play an important role in climate system, especially in the Earth's radiation balance and hydrological cycle. However, the representation of ice cloud radiative effects (CRE) remains significant uncertainty, because scattering properties of ice clouds are not well considered in general circulation models (GCM). We analyze the strengths and weakness of the Rapid Radiative Transfer Model for GCM Applications (RRTMG) and Fu-Liou Radiative Transfer Model (RTM) against rigorous LBLRTM-DISORT (a combination of Line-By-Line Radiative Transfer Model and Discrete Ordinate Radiative Transfer Model) calculations and CERES (Clouds and the Earth's Radiant Energy System) flux observations. In total, 6 US standard atmospheric profiles and 42 atmospheric profiles from Atmospheric and Environmental Research (AER) Company are used to evaluate the RRTMG and Fu-Liou RTM by LBLRTM-DISORT calculations from 0 to 3250 cm-1. Ice cloud radiative effect simulations with RRTMG and Fu-Liou RTM are initialized using the ice cloud properties from MODIS collection-6 products. Simulations of single layer ice cloud CRE by RRTMG and LBLRTM-DISORT show that RRTMG, neglecting scattering, overestimates the TOA flux by about 0-15 W/m2 depending on the cloud particle size and optical depth, and the most significant overestimation occurs when the particle effective radius is small (around 10 μm) and the cloud optical depth is intermediate (about 1-10). The overestimation reduces significantly when the similarity rule is applied to RRTMG. We combine ice cloud properties from MODIS Collection-6 and atmospheric profiles from the Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) reanalysis to simulate ice cloud CRE, which is compared with CERES observations.

Remote Sensing of Energy Distribution Characteristics over the Tibet

NASA Astrophysics Data System (ADS)

Shi, J.; Husi, L.; Wang, T.

2017-12-01

The overall objective of our study is to quantify the spatiotemporal characteristics and changes of typical factors dominating water and energy cycles in the Tibet region. Especially, we focus on variables of clouds optical & microphysical parameters, surface shortwave and longwave radiation. Clouds play a key role in the Tibetan region's water and energy cycles. They seriously impact the precipitation, temperature and surface energy distribution. Considering that proper cloud products with relatively higher spatial and temporal sampling and with satisfactory accuracy are serious lacking in the Tibet region, except cloud optical thickness, cloud effective radius and liquid/ice water content, the cloud coverage dynamics at hourly scales also analyzed jointly based on measurements of Himawari-8, and MODIS. Surface radiation, as an important energy source in perturbating the Tibet's evapotranspiration, snow and glacier melting, is a controlling factor in energy balance in the Tibet region. All currently available radiation products in this area are not suitable for regional scale study of water and energy exchange and snow/glacier melting due to their coarse resolution and low accuracies because of cloud and topography. A strategy for deriving land surface upward and downward radiation by fusing optical and microwave remote sensing data is proposed. At the same time, the big topographic effect on the surface radiation are also modelled and analyzed over the Tibet region.

Importance of molecular Rayleigh scattering in the enhancement of clear sky reflectance in the vicinity of boundary layer cumulus clouds

NASA Astrophysics Data System (ADS)

Wen, Guoyong; Marshak, Alexander; Cahalan, Robert F.

2008-12-01

Clouds increase the complexity of atmospheric radiative transfer processes, particularly for aerosol retrievals in clear regions in the vicinity of clouds. This study focuses on identifying mechanisms responsible for the enhancement of nadir reflectance in clear regions in the vicinity of cumulus clouds and quantifies the relative importance of each mechanism. Using cloud optical properties and surface albedo derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectroradiometer (MODIS), we performed extensive Monte Carlo simulations of radiative transfer in two cumulus scenes in a biomass burning region in Brazil. The results show that the scattering of radiation by clouds, followed by upward Rayleigh scattering by molecules above cloud top over clear gaps, is the dominant mechanism for the enhancement of visible reflectance in clear regions in boundary layer cumulus field over dark surfaces with aerosols trapped in the boundary layer. The Rayleigh scattering contributes ˜80% and ˜50% to the total enhancement for wavelengths 0.47 μm (with aerosol optical thickness 0.2) and 0.66 μm (with aerosol optical thickness 0.1), respectively. Out of the total contribution of molecular scattering, ˜90% arises from the clear atmosphere above cloud top height. The mechanism is valid for a large range of aerosol optical thicknesses (up to 1 in this study) for 0.47 μm, and for aerosol optical thickness up to 0.2 for 0.66 μm. Our results provide a basis to develop simplifications for future aerosol remote sensing from satellite.

The New MODIS-Terra, and the Proposed COBRA Mission: First Global Aerosol Distribution and Properties Over Land and Ocean, and Plans to Measure Global Black Carbon Absorption Over the Ocean Glint

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Tanre, Didier; Remer, Lorraine; Martins, Vanderlei; Schoeberl, Mark; Lau, William K. M. (Technical Monitor)

2001-01-01

The MODIS instrument was launched on the NASA Terra satellite in Dec. 1999. Since last Oct, the sensor and the aerosol algorithm reached maturity and provide global daily retrievals of aerosol optical thickness and properties. MODIS has 36 spectral channels in the visible to IR with resolution down to 250 m. This allows accurate cloud screening and multi-spectral aerosol retrievals. We derive the aerosol optical thickness over the ocean and most of the land areas, distinguishing between fine (mainly man-made aerosol) and coarse (mainly natural) aerosol particles. New methods to derive the aerosol absorption of sunlight are also being developed. These measurements are use to track different aerosol sources, transport and the radiative forcing at the top and bottom of the atmosphere. However MODIS or any present satellite sensor cannot measure absorption by Black Carbon over the oceans, a critical component in studying climate change and human health. For this purpose we propose the COBRA mission that observes the ocean at glint and off glint simultaneously measuring the spectral polarized light and deriving precisely the aerosol absorption.

Fast Simulators for Satellite Cloud Optical Centroid Pressure Retrievals, 1. Evaluation of OMI Cloud Retrievals

NASA Technical Reports Server (NTRS)

Joiner, J.; Vasilkov, A. P.; Gupta, Pawan; Bhartia, P. K.; Veefkind, Pepijn; Sneep, Maarten; deHaan, Johan; Polonsky, Igor; Spurr, Robert

2011-01-01

We have developed a relatively simple scheme for simulating retrieved cloud optical centroid pressures (OCP) from satellite solar backscatter observations. We have compared simulator results with those from more detailed retrieval simulators that more fully account for the complex radiative transfer in a cloudy atmosphere. We used this fast simulator to conduct a comprehensive evaluation of cloud OCPs from the two OMI algorithms using collocated data from CloudSat and Aqua MODIS, a unique situation afforded by the A-train formation of satellites. We find that both OMI algorithms perform reasonably well and that the two algorithms agree better with each other than either does with the collocated CloudSat data. This indicates that patchy snow/ice, cloud 3D, and aerosol effects not simulated with the CloudSat data are affecting both algorithms similarly. We note that the collocation with CloudSat occurs mainly on the East side of OMI's swath. Therefore, we are not able to address cross-track biases in OMI cloud OCP retrievals. Our fast simulator may also be used to simulate cloud OCP from output generated by general circulation models (GCM) with appropriate account of cloud overlap. We have implemented such a scheme and plan to compare OMI data with GCM output in the near future.

Multi-sensor cloud and aerosol retrieval simulator and remote sensing from model parameters - Part 2: Aerosols

NASA Astrophysics Data System (ADS)

Wind, Galina; da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

2016-07-01

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a "simulated radiance" product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land-ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers.This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled.In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model subgrid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms.Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (M{O/Y}D04). The M{O/Y}D04 product is of course normally produced from M{O/Y}D021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a M{O/Y}D021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source.We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters . Part 2; Aerosols

NASA Technical Reports Server (NTRS)

Wind, Galina; Da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

2016-01-01

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

How Do A-train Sensors Intercompare in the Retrieval of Above-cloud Aerosol Optical Depth? A Case Study-based Assessment

NASA Technical Reports Server (NTRS)

Jethva, Hiren; Torres, Omar; Waquet, Fabien; Chand, Duli; Hu, Yongxiang

2014-01-01

We intercompare the above-cloud aerosol optical depth (ACAOD) of biomass burning plumes retrieved from A-train sensors, i.e., Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Polarization and Directionality of Earth Reflectances (POLDER), and Ozone Monitoring Instrument (OMI). These sensors have shown independent capabilities to retrieve aerosol loading above marine boundary layer clouds-a kind of situation often found over the southeast Atlantic Ocean during dry burning season. A systematic comparison reveals that all passive sensors and CALIOP-based research methods derive comparable ACAOD with differences mostly within 0.2 over homogeneous cloud fields. The 532 nm ACAOD retrieved by CALIOP operational algorithm is underestimated. The retrieved 1064 nm AOD however shows closer agreement with passive sensors. Given the different types of measurements processed with different algorithms, the reported close agreement between them is encouraging. Due to unavailability of direct measurements above cloud, the validation of satellite-based ACAOD remains an open challenge. The intersatellite comparison however can be useful for the relative evaluation and consistency check

An Integrated Cloud-Aerosol-Radiation Product Using CERES, MODIS, CALIPSO and CloudSat Data

NASA Astrophysics Data System (ADS)

Sun-Mack, S.; Gibson, S.; Chen, Y.; Wielicki, B.; Minnis, P.

2006-12-01

The goal of this paper is to provide the first integrated data set of global vertical profiles of aerosols, clouds, and radiation using the combined NASA A-Train data from Aqua CERES and MODIS, CALIPSO, and CloudSat. All of these instruments are flying in formation as part of the Aqua Train, or A-Train. This paper will present the preliminary results of merging aerosol and cloud data from the CALIPSO active lidar, cloud data from CloudSat, integrated column aerosol and cloud data from the MODIS CERES analyses, and surface and top-of-atmosphere broadband radiation fluxes from CERES. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

Characterization of 3D Cirrus Cloud and Radiation Fields Using ARS/AIRS/MODIS data and its Application to Climate Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liou, Kuo-Nan; Ou, S. C.; Gu, Y.

During the report period, we have made the following research accomplishments. First, we performed analysis for a number of MODIS scenes comprising of heavy dust events and ice clouds, covering regions of frequent dust outbreaks in East Asia, Middle East, and West Africa, as well as areas associated with long-range dust transports over the Equatorial Tropical Atlantic Ocean. These scenes contain both dust/aerosols and clouds. We collected suitable aerosol/ice-cloud data, correlated ice cloud and aerosol parameters by means of statistical analysis, and interpreted resulting correlation trends based on the physical principles governing cloud microphysics. Aerosol and cloud optical depths andmore » cloud effective particle size inferred from MODIS for selected domains were analyzed from which the parameters including dust aerosol number concentration, ice cloud water path, and ice particle number concentration were subsequently derived. We illustrated that the Twomey (solar albedo) effect can be statistically quantified based on the slope of best-fit straight lines in the correlation study. Analysis of aerosol and cloud retrieval products revealed that for all cases, the region with a larger dust aerosol optical depth is always characterized by a smaller cloud particle size, consistent with the Twomey hypothesis for aerosol-cloud interactions. Second, we developed mean correlation curves with uncertainties associated with small ice-crystal concentration observations for the mean effective ice crystal size (De) and ice water content (IWC) by dividing the atmosphere into three characteristic regions: Tropics cirrus, Midlatitude cirrus, including a temperature classification to improve correlation, and Arctic ice clouds. We illustrated that De has a high correlation with IWC based on theoretical consideration and analysis of thousands of observed ice crystal data obtained from a number of ARM-DOE field campaigns and other experiments. The correlation has the form: ln(De) = a + b ln(IWC) + c ((ln(IWC))2, where a, b, and c are fitting coefficients and are functions of three regions. We demonstrated that this correlation can be effectively incorporated in GCMs and climate models that predict IWC - a significant advance in ice microphysics parameterization for interactive cloud-radiation analysis and feedback. Substantial July mean differences are shown in the OLR (W/m2) and precipitation (mm/day) patterns between UCLA GCM simulations based on Des determined from the De-IWC correlations and the control run using a fixed ice crystal size. Third, in order to improve the computation of spectral radiative transfer processes in the WRF model, we developed a consistent and efficient radiation scheme that can better resolve the spectral bands, determine the cloud optical properties, and provide more reliable and accurate radiative heating fields. In the newly developed radiation module, we have implemented in WRF a modified and improved version referred to as the Fu-Liou-Gu scheme, which includes a combination of delta-four-stream and delta-two-stream approximations for solar and IR flux calculations, respectively. This combination has been proven to be computationally efficient and at the same time to produce a high degree of accuracy. The incorporation of nongray gaseous absorption in multiple scattering atmospheres was based on the correlated k-distribution method. The solar and IR spectra are divided into 6 and 12 bands, respectively, according to the location of absorption bands of H2O, CO2, O3, CH4, N2O, and CFCs. We further included absorption by the water vapor continuum and a number of minor absorbers in the solar spectrum leading to an additional absorption of solar flux in a clear atmosphere on the order of 1-3 W/m2. Additionally, we incorporated the ice microphysics parameterization that includes an interactive mean effective ice crystal size in association with radiation parameterizations. The Fu-Liou-Gu scheme is an ideal tool for the simulation of radiative transfer and ice microphysics within the domain of WRF. It is particularly useful for studying direct and indirect aerosol radiative effects associated with ice cloud formation. The newly implemented radiation module has been demonstrated to work well in WRF and can be effectively used for studies related to cirrus cloud formation and evolution as well as aerosol-cloud-radiation interactions. With the newly implemented radiation scheme, the simulations of cloud cover and ice water path have been improved for cirrus clouds, with a more consistent comparison with the corresponding MODIS observations, especially for optically thin cirrus with an improvement of about 20% in the simulated mean ice water path.« less

Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms: validation against collocated MODIS and CALIOP data

NASA Astrophysics Data System (ADS)

Taylor, Thomas E.; O'Dell, Christopher W.; Frankenberg, Christian; Partain, Philip T.; Cronk, Heather Q.; Savtchenko, Andrey; Nelson, Robert R.; Rosenthal, Emily J.; Chang, Albert Y.; Fisher, Brenden; Osterman, Gregory B.; Pollock, Randy H.; Crisp, David; Eldering, Annmarie; Gunson, Michael R.

2016-03-01

The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO2) dry air mole fraction (XCO2) from satellite measurements of reflected sunlight in the near-infrared. These estimates can be biased by clouds and aerosols, i.e., contamination, within the instrument's field of view. Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) XCO2 retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 µm O2 A band, neglecting scattering by clouds and aerosols, which introduce photon path-length differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO2 and H2O column abundances using observations taken at 1.61 µm (weak CO2 band) and 2.06 µm (strong CO2 band), while neglecting atmospheric scattering. The CO2 and H2O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which are sensitive to different features in the spectra, provides the basis for cloud screening of the OCO-2 data set.To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (MODIS), aboard the Aqua platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning of algorithmic threshold parameters that allows for processing of ≃ 20-25 % of all OCO-2 soundings, agreement between the OCO-2 and MODIS cloud screening methods is found to be ≃ 85 % over four 16-day orbit repeat cycles in both the winter (December) and spring (April-May) for OCO-2 nadir-land, glint-land and glint-water observations.No major, systematic, spatial or temporal dependencies were found, although slight differences in the seasonal data sets do exist and validation is more problematic with increasing solar zenith angle and when surfaces are covered in snow and ice and have complex topography. To further analyze the performance of the cloud screening algorithms, an initial comparison of OCO-2 observations was made to collocated measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). These comparisons highlight the strength of the OCO-2 cloud screening algorithms in identifying high, thin clouds but suggest some difficulty in identifying some clouds near the surface, even when the optical thicknesses are greater than 1.

Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms; validation against collocated MODIS and CALIOP data

NASA Astrophysics Data System (ADS)

Taylor, T. E.; O'Dell, C. W.; Frankenberg, C.; Partain, P.; Cronk, H. Q.; Savtchenko, A.; Nelson, R. R.; Rosenthal, E. J.; Chang, A. Y.; Fisher, B.; Osterman, G.; Pollock, R. H.; Crisp, D.; Eldering, A.; Gunson, M. R.

2015-12-01

The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO2) dry air mole fraction (XCO2) from satellite measurements of reflected sunlight in the near-infrared. These estimates can be biased by clouds and aerosols within the instrument's field of view (FOV). Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) XCO2 retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 μm O2 A-band, neglecting scattering by clouds and aerosols, which introduce photon path-length (PPL) differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A-Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO2 and H2O column abundances using observations taken at 1.61 μm (weak CO2 band) and 2.06 μm (strong CO2 band), while neglecting atmospheric scattering. The CO2 and H2O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which key off of different features in the spectra, provides the basis for cloud screening of the OCO-2 data set. To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (MODIS), aboard the Aqua platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning to allow throughputs of ≃ 30 %, agreement between the OCO-2 and MODIS cloud screening methods is found to be ≃ 85 % over four 16-day orbit repeat cycles in both the winter (December) and spring (April-May) for OCO-2 nadir-land, glint-land and glint-water observations. No major, systematic, spatial or temporal dependencies were found, although slight differences in the seasonal data sets do exist and validation is more problematic with increasing solar zenith angle and when surfaces are covered in snow and ice and have complex topography. To further analyze the performance of the cloud screening algorithms, an initial comparison of OCO-2 observations was made to collocated measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). These comparisons highlight the strength of the OCO-2 cloud screening algorithms in identifying high, thin clouds but suggest some difficulty in identifying some clouds near the surface, even when the optical thicknesses are greater than 1.

Remote Sensing of Aerosol and their Radiative Properties from the MODIS Instrument on EOS-Terra Satellite: First Results and Evaluation

NASA Technical Reports Server (NTRS)

Kaufman, Yoram; Tanre, Didier; Remer, Lorraine; Holben, Brent; Lau, William K.-M. (Technical Monitor)

2001-01-01

The MODIS instrument was launched on the NASA Terra satellite in Dec. 1999. Since last Oct., the sensor and the aerosol algorithm reached maturity and provide global daily retrievals of aerosol optical thickness and properties. MODIS has 36 spectral channels in the visible to IR with resolution down to 250 m. This allows accurate cloud screening and multi-spectral aerosol retrievals. We derive the aerosol optical thickness over the ocean and most of the land areas, distinguishing between fine (mainly man-made aerosol) and coarse aerosol particles. The information is more precise over the ocean where we derive also the effective radius and scattering asymmetry parameter of the aerosol. New methods to derive the aerosol single scattering albedo are also being developed. These measurements are use to track different aerosol sources, transport and the radiative forcing at the top and bottom of the atmosphere. The AErosol RObotic NETwork of ground based radiometers is used for global validation of the satellite derived optical thickness, size parameters and single scattering albedo and measure additional aerosol parameters that cannot be derived from space.

Determination of Ice Water Path in Ice-over-Water Cloud Systems Using Combined MODIS and AMSR-E Measurements

NASA Technical Reports Server (NTRS)

Huang, Jianping; Minnis, Patrick; Lin, Bing; Yi, Yuhong; Fan, T.-F.; Sun-Mack, Sunny; Ayers, J. K.

2006-01-01

To provide more accurate ice cloud properties for evaluating climate models, the updated version of multi-layered cloud retrieval system (MCRS) is used to retrieve ice water path (IWP) in ice-over-water cloud systems over global ocean using combined instrument data from the Aqua satellite. The liquid water path (LWP) of lower layer water clouds is estimated from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) measurements. With the lower layer LWP known, the properties of the upper-level ice clouds are then derived from Moderate Resolution Imaging Spectroradiometer measurements by matching simulated radiances from a two-cloud layer radiative transfer model. Comparisons with single-layer cirrus systems and surface-based radar retrievals show that the MCRS can significantly improve the accuracy and reduce the over-estimation of optical depth and ice water path retrievals for ice over-water cloud systems. During the period from December 2004 through February 2005, the mean daytime ice cloud optical depth and IWP for overlapped ice-over-water clouds over ocean from Aqua are 7.6 and 146.4 gm(sup -2), respectively, significantly less than the initial single layer retrievals of 17.3 and 322.3 gm(sup -2). The mean IWP for actual single-layer clouds was 128.2 gm(sup -2).

Cirrus Horizontal Heterogeneity Effects on Cloud Optical Properties Retrieved from MODIS VNIR to TIR Channels as a Function of the Spatial Resolution

NASA Astrophysics Data System (ADS)

Fauchez, T.; Platnick, S. E.; Sourdeval, O.; Wang, C.; Meyer, K.; Cornet, C.; Szczap, F.

2017-12-01

Cirrus are an important part of the Earth radiation budget but an assessment of their role yet remains highly uncertain. Cirrus optical properties such as Cloud Optical Thickness (COT) and ice crystal effective particle size (Re) are often retrieved with a combination of Visible/Near InfraRed (VNIR) and ShortWave-InfraRed (SWIR) reflectance channels. Alternatively, Thermal InfraRed (TIR) techniques, such as the Split Window Technique (SWT), have demonstrated better sensitivity to thin cirrus. However, current satellite operational products for both retrieval methods assume that cloudy pixels are horizontally homogeneous (Plane Parallel and Homogeneous Approximation (PPHA)) and independent (Independent Pixel Approximation (IPA)). The impact of these approximations on cirrus retrievals needs to be understood and, as far as possible, corrected. Horizontal heterogeneity effects can be more easily estimated and corrected in the TIR range because they are mainly dominated by the PPA bias, which primarily depends on the COT subpixel heterogeneity. For solar reflectance channels, in addition to the PPHA bias, the IPA can lead to significant retrieval errors if there is large photon transport between cloudy columns in addition to brightening and shadowing effects that are more difficult to quantify.The effects of cirrus horizontal heterogeneity are here studied on COT and Re retrievals obtained using simulated MODIS reflectances at 0.86 and 2.11 μm and radiances at 8.5, 11.0 and 12.0 μm, for spatial resolutions ranging from 50 m to 10 km. For each spatial resolution, simulated TOA reflectances and radiances are combined for cloud optical property retrievals with a research-level optimal estimation retrieval method (OEM). The impact of horizontal heterogeneity on the retrieved products is assessed for different solar geometries and various combinations of the five channels.

The influence of Cloud Longwave Scattering together with a state-of-the-art Ice Longwave Optical Parameterization in Climate Model Simulations

NASA Astrophysics Data System (ADS)

Chen, Y. H.; Kuo, C. P.; Huang, X.; Yang, P.

2017-12-01

Clouds play an important role in the Earth's radiation budget, and thus realistic and comprehensive treatments of cloud optical properties and cloud-sky radiative transfer are crucial for simulating weather and climate. However, most GCMs neglect LW scattering effects by clouds and tend to use inconsistent cloud SW and LW optical parameterizations. Recently, co-authors of this study have developed a new LW optical properties parameterization for ice clouds, which is based on ice cloud particle statistics from MODIS measurements and state-of-the-art scattering calculation. A two-stream multiple-scattering scheme has also been implemented into the RRTMG_LW, a widely used longwave radiation scheme by climate modeling centers. This study is to integrate both the new LW cloud-radiation scheme for ice clouds and the modified RRTMG_LW with scattering capability into the NCAR CESM to improve the cloud longwave radiation treatment. A number of single column model (SCM) simulations using the observation from the ARM SGP site on July 18 to August 4 in 1995 are carried out to assess the impact of new LW optical properties of clouds and scattering-enabled radiation scheme on simulated radiation budget and cloud radiative effect (CRE). The SCM simulation allows interaction between cloud and radiation schemes with other parameterizations, but the large-scale forcing is prescribed or nudged. Comparing to the results from the SCM of the standard CESM, the new ice cloud optical properties alone leads to an increase of LW CRE by 26.85 W m-2 in average, as well as an increase of the downward LW flux at surface by 6.48 W m-2. Enabling LW cloud scattering further increases the LW CRE by another 3.57 W m-2 and the downward LW flux at the surface by 0.2 W m-2. The change of LW CRE is mainly due to an increase of cloud top height, which enhances the LW CRE. A long-term simulation of CESM will be carried out to further understand the impact of such changes on simulated climates.

An Evaluation of Marine Boundary Layer Cloud Property Simulations in the Community Atmosphere Model Using Satellite Observations: Conventional Subgrid Parameterization versus CLUBB

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Hua; Zhang, Zhibo; Ma, Po-Lun

This paper presents a two-step evaluation of the marine boundary layer (MBL) cloud properties from two Community Atmospheric Model (version 5.3, CAM5) simulations, one based on the CAM5 standard parameterization schemes (CAM5-Base), and the other on the Cloud Layers Unified By Binormals (CLUBB) scheme (CAM5-CLUBB). In the first step, we compare the cloud properties directly from model outputs between the two simulations. We find that the CAM5-CLUBB run produces more MBL clouds in the tropical and subtropical large-scale descending regions. Moreover, the stratocumulus (Sc) to cumulus (Cu) cloud regime transition is much smoother in CAM5-CLUBB than in CAM5-Base. In addition,more » in CAM5-Base we find some grid cells with very small low cloud fraction (<20%) to have very high in-cloud water content (mixing ratio up to 400mg/kg). We find no such grid cells in the CAM5-CLUBB run. However, we also note that both simulations, especially CAM5-CLUBB, produce a significant amount of “empty” low cloud cells with significant cloud fraction (up to 70%) and near-zero in-cloud water content. In the second step, we use satellite observations from CERES, MODIS and CloudSat to evaluate the simulated MBL cloud properties by employing the COSP satellite simulators. We note that a feature of the COSP-MODIS simulator to mimic the minimum detection threshold of MODIS cloud masking removes much more low clouds from CAM5-CLUBB than it does from CAM5-Base. This leads to a surprising result — in the large-scale descending regions CAM5-CLUBB has a smaller COSP-MODIS cloud fraction and weaker shortwave cloud radiative forcing than CAM5-Base. A sensitivity study suggests that this is because CAM5-CLUBB suffers more from the above-mentioned “empty” clouds issue than CAM5-Base. The COSP-MODIS cloud droplet effective radius in CAM5-CLUBB shows a spatial increase from coastal St toward Cu, which is in qualitative agreement with MODIS observations. In contrast, COSP-MODIS cloud droplet effective radius in CAM5-Base almost remains a constant. In comparison with CloudSat observations, the histogram of the radar reflectivity from modeled MBL clouds is too narrow without a distinct separation between cloud and drizzle modes. Moreover, the probability of drizzle in both simulations is almost twice as high as the observation. Future studies are needed to understand the causes of these differences and their potential connection with the “empty” cloud issues in the model.« less

Comparison of Cloud Detection Using the CERES-MODIS Ed4 and LaRC AVHRR Cloud Masks and CALIPSO Vertical Feature Mask

NASA Astrophysics Data System (ADS)

Trepte, Q. Z.; Minnis, P.; Palikonda, R.; Bedka, K. M.; Sun-Mack, S.

2011-12-01

Accurate detection of cloud amount and distribution using satellite observations is crucial in determining cloud radiative forcing and earth energy budget. The CERES-MODIS (CM) Edition 4 cloud mask is a global cloud detection algorithm for application to Terra and Aqua MODIS data with the aid of other ancillary data sets. It is used operationally for the NASA's Cloud and Earth's Radiant Energy System (CERES) project. The LaRC AVHRR cloud mask, which uses only five spectral channels, is based on a subset of the CM cloud mask which employs twelve MODIS channels. The LaRC mask is applied to AVHRR data for the NOAA Climate Data Record Program. Comparisons among the CM Ed4, and LaRC AVHRR cloud masks and the CALIPSO Vertical Feature Mask (VFM) constitute a powerful means for validating and improving cloud detection globally. They also help us understand the strengths and limitations of the various cloud retrievals which use either active and passive satellite sensors. In this paper, individual comparisons will be presented for different types of clouds over various surfaces, including daytime and nighttime, and polar and non-polar regions. Additionally, the statistics of the global, regional, and zonal cloud occurrence and amount from the CERES Ed4, AVHRR cloud masks and CALIPSO VFM will be discussed.

A Solar Reflectance Method for Retrieving Cloud Optical Thickness and Droplet Size Over Snow and Ice Surfaces

NASA Technical Reports Server (NTRS)

Platnick, S.; Li, J. Y.; King, M. D.; Gerber, H.; Hobbs, P. V.

1999-01-01

Cloud optical thickness and effective radius retrievals from solar reflectance measurements are traditionally implemented using a combination of spectral channels that are absorbing and non-absorbing for water particles. Reflectances in non-absorbing channels (e.g., 0.67, 0.86, 1.2 micron spectral window bands) are largely dependent on cloud optical thickness, while longer wavelength absorbing channels (1.6, 2. 1, and 3.7 micron 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 devised. 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 NASA ER-2 from May - June 1998 during the Arctic FIRE-ACE field deployment. Data from several coordinated ER-2 and University of Washington CV-580 in situ 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 the in situ measurements. The initial success of the technique has implications for future operational satellite cloud retrieval algorithms in polar and wintertime regions.

The Observed Behavior of the Bias in MODIS-retrieved Cloud Droplet Effective Radius through MISR-MODIS Data Fusion

NASA Astrophysics Data System (ADS)

Fu, D.; Di Girolamo, L.; Liang, L.; Zhao, G.

2017-12-01

Listed as one of the Essential Climate Variables by the Global Climate Observing System, the effective radius (Re) of the cloud drop size distribution plays an important role in the energy and water cycles of the Earth system. Re is retrieved from several passive sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS), based on a visible and near-infrared bi-spectral technique that had its foundation more than a quarter century ago. This technique makes a wide range of assumptions, including 1-D radiative transfer, assumed single-mode drop size distribution, and cloud horizontal and vertical homogeneity. It is well known that deviations from these assumptions lead to bias in the retrieved Re. Recently, an effort to characterize the bias in MODIS-retrieved Re through MISR-MODIS data fusion revealed biases in the zonal-mean values of MODIS-retrieved Re that varied from 2 to 11 µm, depending on latitude (Liang et al., 2015). Here, in a push towards bias-correction of MODIS-retrieved Re, we further examine the bias with MISR-MODIS data fusion as it relates to other observed cloud properties, such as cloud-top height and the spatial variability of the radiance field, sun-view geometry, and the driving meteorology had from reanalysis data. Our results show interesting relationships in Re bias behavior with these observed properties, revealing that while Re bias do show a certain degree of dependence on some properties, no single property dominates the behavior in MODIS-retrieved Re bias.

Comparison of Marine Boundary Layer Cloud Properties From CERES-MODIS Edition 4 and DOE ARM AMF Measurements at the Azores

NASA Astrophysics Data System (ADS)

Dong, X.; Xi, B.; Minnis, P.; Sun-Mack, S.

2014-12-01

Marine Boundary Layer (MBL) cloud properties derived for the NASA CERES Project using Terra and Aqua MODIS data are compared with observations taken at DOE ARM Mobile Facility at the Azores site from Jun. 2009 to Dec. 2010. Cloud properties derived from ARM ground-based observations were averaged over a 1-hour interval centered at the satellite overpass time, while the CERES-MODIS (CM) results were averaged within a 30×30 km2 grid box centered over the Azores site. A total of 63 daytime and 92 nighttime single-layered overcast MBL cloud cases were selected from 19 months of ARM radar-lidar and satellite observations. The CM cloud-top/base heights (Htop/Hbase) were determined from cloud-top/base temperatures (Ttop/Tbase) using a regional boundary-layer lapse rate method. For daytime comparisons, the CM-derived Htop (Hbase), on average, is 0.063 km (0.068 km) higher (lower) than its ARM radar-lidar observed counterpart, and the CM-derived Ttop and Tbase are 0.9 K less and 2.5 K greater than the surface values with high correlations (R2=0.82 and 0.84, respectively). In general, the cloud-top comparisons agree better than cloud-base comparisons because the CM Tbase and Hbase are secondary product determined from Ttop and Htop. No significant day-night difference was found in the analyses. The comparisons of microphysical properties reveal that, when averaged over a 30x30 km2 area, the CM-retrieved cloud-droplet effective radius (re) is 1.3 µm larger than that from the ARM retrievals (12.8 µm). While the CM-retrieved cloud liquid water path (LWP) is 13.5 gm-2 less than its ARM counterpart (114.2 gm-2) due to its small optical depth (τ, 9.6 vs. 13.7). The differences are reduced by 50% when the CM averages are computed only using the MODIS pixel nearest the AMF site. Using effective radius retrieved at 2.1-µm channel to calculate LWP can reduce the difference between the CM and ARM from -13.7 to 2.1 gm-2. The 10% differences between the ARM and CM LWP and re retrievals are within the uncertainties of the ARM LWP (~ 20 gm-2) and re (~ 10%) retrievals, however, the 30% difference in τ is significant. Possible reasons contributed to this discrepancy increased sensitivities in τ from both surface retrievals when τ ~ 10 and topography. The τ differences vary with wind direction and are consistent with the island orography.

Cloud Statistics and Discrimination in the Polar Regions

NASA Astrophysics Data System (ADS)

Chan, M.; Comiso, J. C.

2012-12-01

Despite their important role in the climate system, cloud cover and their statistics are poorly known, especially in the polar regions, where clouds are difficult to discriminate from snow covered surfaces. The advent of the A-train, which included Aqua/MODIS, CALIPSO/CALIOP and CloudSat/CPR sensors has provided an opportunity to improve our ability to accurately characterize the cloud cover. MODIS provides global coverage at a relatively good temporal and spatial resolution while CALIOP and CPR provide limited nadir sampling but accurate characterization of the vertical structure and phase of the cloud cover. Over the polar regions, cloud detection from a passive sensors like MODIS is challenging because of the presence of cold and highly reflective surfaces such as snow, sea-ice, glaciers, and ice-sheet, which have surface signatures similar to those of clouds. On the other hand, active sensors such as CALIOP and CPR are not only very sensitive to the presence of clouds but can also provide information about its microphysical characteristics. However, these nadir-looking sensors have sparse spatial coverage and their global data can have data spatial gaps of up to 100 km. We developed a polar cloud detection system for MODIS that is trained using collocated data from CALIOP and CPR. In particular, we employ a machine learning system that reads the radiative profile observed by MODIS and determine whether the field of view is cloudy or clear. Results have shown that the improved cloud detection scheme performs better than typical cloud mask algorithms using a validation data set not used for training. A one-year data set was generated and results indicate that daytime cloud detection accuracies improved from 80.1% to 92.6% (over sea-ice) and 71.2% to 87.4% (over ice-sheet) with CALIOP data used as the baseline. Significant improvements are also observed during nighttime, where cloud detection accuracies increase by 19.8% (over sea-ice) and 11.6% (over ice-sheet). The immediate impact of the new algorithm is that it can minimize large biases of MODIS-derived cloud amount over the Polar Regions and thus a more realistic and high quality global cloud statistics. In particular, our results show that cloud fraction in the Arctic is typically 81.2 % during daytime and 84.0% during nighttime. This is significantly higher than the 71.8% and 58.5%, respectively, derived from standard MODIS cloud product.

Aerosol direct and indirect radiative effect over Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Georgoulias, Aristeidis; Alexandri, Georgia; Zanis, Prodromos; Ntogras, Christos; Poeschl, Ulrich; Kourtidis, Kostas

In this work, we present results from the QUADIEEMS project which is focused on the aerosol-cloud relations and the aerosol direct and indirect radiative effect over the region of Eastern Mediterranean. First, a gridded dataset at a resolution of 0.1x0.1 degrees (~10km) with aerosol and cloud related parameters was compiled, using level-2 satellite observations from MODIS TERRA (3/2000-12/2012) and AQUA (7/2002-12/2012). The aerosol gridded dataset has been validated against sunphotometric measurements from 12 AERONET ground stations, showing that generally MODIS overestimates aerosol optical depth (AOD550). Then, the AOD550 and fine mode ratio (FMR550) data from MODIS were combined with aerosol index (AI) data from the Earth Probe TOMS and OMI satellite sensors, wind field data from the ERA-interim reanalysis and AOD550 data for various aerosol types from the GOCART model and the MACC reanalysis to quantify the relative contribution of different aerosol types (marine, dust, anthropogenic, fine-mode natural) to the total AOD550. The aerosol-cloud relations over the region were investigated with the use of the joint high resolution aerosol-cloud gridded dataset. Specifically, we focused on the seasonal relations between the cloud droplet number concentration (CDNC) and AOD550. The aerosol direct and first indirect radiative effect was then calculated for each aerosol type separately making use of the aerosol relative contribution to the total AOD550, the CDND-AOD550 relations and satellite-based parameterizations. The direct radiative effect was also quantified using simulations from a regional climate model (REGCM4), simulations with a radiative transfer model (SBDART) and the three methods were finally intervalidated.

Ultra-clean Layers (UCLs) and Low Albedo Clouds ("gray clouds") in the Marine Boundary Layer - CSET aircraft data, 2-D bin spectral cloud parcel model, large eddy simulation and satellite observations from CALIPSO, MODIS and COSMIC

NASA Astrophysics Data System (ADS)

O, K. T.; Wood, R.; Bretherton, C. S.; Eastman, R. M.; Tseng, H. H.

2016-12-01

During the 2015 Cloud System Evolution in the Trades (CSET) field program (CSET, Jul-Aug 2015, subtropical NE Pacific), the NSF/NCAR G-V aircraft frequently encountered ultra clean layers (hereafter UCLs) with extremely low accumulation mode aerosol (i.e. diameter da> 100nm) concentration (hereafter Na), and low albedo ( 0.2) warm clouds (termed "gray clouds" in our study) with low droplet concentration (hereafter Nd). The analysis of CSET aircraft data shows that (1) UCLs and gray clouds are mostly commonly found at a height of 1.5-2km, typically close to the top of the MBL, (2) UCLs and gray cloud coverage as high as 40-60% between 135W and 155W (i.e. Sc-Cu transition region) but occur very infrequently east of 130W (i.e. shallow, near-coastal stratocumulus region), and (3) UCLs and gray clouds exhibit remarkably low turbulence compared with non-UCL clear sky and clouds. It should be noted that most previous aircraft sampling of low clouds occurred close to the Californian coast, so the prevalence of UCLs and gray clouds has not been previously noted. Based on the analysis of aircraft data, we hypothesize that gray clouds result from detrainment of cloud close to the top of precipitating trade cumuli, and UCLs are remnants of these layers when gray clouds evaporates. The simulations in our study are performed using 2-D bin spectral cloud parcel model and version 6.9 of the System for Atmospheric Modeling (SAM). Our idealized simulations suggest that collision-coalescence plays a crucial role in reducing Nd such that gray clouds can easily form via collision-coalescence in layers detrained from the cloud top at trade cumulus regime, but can not form at stratocumulus regime. Upon evaporation of gray clouds, only few accumulation mode aerosols are returned to the clear sky, leaving horizontally-extensive UCLs (i.e. clean clear sky). Analysis of CSET flight data and idealized model simulations both suggest cloud top/PBL height may play an important role in the formation of UCLs and gray clouds. In our satellite observation study, the comparison between PBL height (from COSMIC and MODIS) and fraction of low optical depth cloud (from MODIS and CALIPSO) at NEP trade cumulus regime (20-35N, 140-155W) also suggest a strong positive correlation.

MODIS infrared data applied to Popocatepetl's volcanic clouds

NASA Astrophysics Data System (ADS)

Rose, W. I.; Delgado-Granados, H.; Watson, I. M.; Matiella, M. A.; Escobar, D.; Gu, Y.

2003-04-01

Popocatepetl volcano, Mexico, has shown diverse activity for the past eight years and has been characterized by strong sulfur dioxide releases and ash eruptions of variable tropospheric height. We have begun study on the eruptive activity of December 2000 and January 2001, when Popocatepetl was showing prominent activity. MODIS data is abundant during this period, and we have applied a variety of algorithms which use infrared channels of MODIS and can potentially map and measure ash size and optical depth [Wen &Rose, 1994, J Geophys Res 99 5421-5431], sulfur dioxide mass [Realmuto et al, 1997, J. Geophys. Res., 102, 15057-15072; Prata et al, in press, AGU Volcanism &Atmosphere Monograph] and sulfate particle size and mass [Yu &Rose, 2000, AGU Monograph 116: 87-100]. Because of variable environmental conditions (clouds, winds) and characteristics of the activity (explosivity and rates of sulfur dioxide and ash releases) the data set studied offers a robust test of the various algorithms, and the data may also be compared to data collected as part of the volcanic monitoring effort, including COSPEC-based sulfur dioxide surveys. The data set will be used to evaluate which algorithms work best in various conditions. At abstract time work on the data is incomplete, but we expect that such data may provide information that is useful to the volcanologists studying Popocatepetl and the people who provide information for ash cloud hazards to aircraft.

Aerosol Optical Depth Changes in Version 4 CALIPSO Level 2 Product

NASA Technical Reports Server (NTRS)

Kim, Man-Hae; Omar, Ali H.; Tackett, Jason L.; Vaughan, Mark A.; Winker, David M.; Trepte, Charles R.; Hu, Yongxiang; Liu, Zhaoyan

2017-01-01

The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) version 4.10 (V4) products were released in November 2016 with substantial enhancements. There have been improvements in the V4 CALIOP level 2 aerosol optical depth (AOD) compared to V3 (version 3) due to various factors. AOD change from V3 to V4 is investigated by separating factors. CALIOP AOD was compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) and Aerosol Robotic Network (AERONET) for both V3 and V4.

Development of GK-2A cloud optical and microphysical properties retrieval algorithm

NASA Astrophysics Data System (ADS)

Yang, Y.; Yum, S. S.; Um, J.

2017-12-01

Cloud and aerosol radiative forcing is known to be one of the the largest uncertainties in climate change prediction. To reduce this uncertainty, remote sensing observation of cloud radiative and microphysical properties have been used since 1970s and the corresponding remote sensing techniques and instruments have been developed. As a part of such effort, Geo-KOMPSAT-2A (Geostationary Korea Multi-Purpose Satellite-2A, GK-2A) will be launched in 2018. On the GK-2A, the Advanced Meteorological Imager (AMI) is primary instrument which have 3 visible, 3 near-infrared, and 10 infrared channels. To retrieve optical and microphysical properties of clouds using AMI measurements, the preliminary version of new cloud retrieval algorithm for GK-2A was developed and several validation tests were conducted. This algorithm retrieves cloud optical thickness (COT), cloud effective radius (CER), liquid water path (LWP), and ice water path (IWP), so we named this algorithm as Daytime Cloud Optical thickness, Effective radius and liquid and ice Water path (DCOEW). The DCOEW uses cloud reflectance at visible and near-infrared channels as input data. An optimal estimation (OE) approach that requires appropriate a-priori values and measurement error information is used to retrieve COT and CER. LWP and IWP are calculated using empirical relationships between COT/CER and cloud water path that were determined previously. To validate retrieved cloud properties, we compared DCOEW output data with other operational satellite data. For COT and CER validation, we used two different data sets. To compare algorithms that use cloud reflectance at visible and near-IR channels as input data, MODIS MYD06 cloud product was selected. For the validation with cloud products that are based on microwave measurements, COT(2B-TAU)/CER(2C-ICE) data retrieved from CloudSat cloud profiling radar (W-band, 94 GHz) was used. For cloud water path validation, AMSR-2 Level-3 Cloud liquid water data was used. Detailed results will be shown at the conference.

Diurnal cycle and seasonal variation of cloud cover over the Tibetan Plateau as determined from Himawari-8 new-generation geostationary satellite data.

PubMed

Shang, Huazhe; Letu, Husi; Nakajima, Takashi Y; Wang, Ziming; Ma, Run; Wang, Tianxing; Lei, Yonghui; Ji, Dabin; Li, Shenshen; Shi, Jiancheng

2018-01-18

Analysis of cloud cover and its diurnal variation over the Tibetan Plateau (TP) is highly reliant on satellite data; however, the accuracy of cloud detection from both polar-orbiting and geostationary satellites over this area remains unclear. The new-generation geostationary Himawari-8 satellites provide high-resolution spatial and temporal information about clouds over the Tibetan Plateau. In this study, the cloud detection of MODIS and AHI is investigated and validated against CALIPSO measurements. For AHI and MODIS, the false alarm rate of AHI and MODIS in cloud identification over the TP was 7.51% and 1.94%, respectively, and the cloud hit rate was 73.55% and 80.15%, respectively. Using hourly cloud-cover data from the Himawari-8 satellites, we found that at the monthly scale, the diurnal cycle in cloud cover over the TP tends to increase throughout the day, with the minimum and maximum cloud fractions occurring at 10:00 a.m. and 18:00 p.m. local time. Due to the limited time resolution of polar-orbiting satellites, the underestimation of MODIS daytime average cloud cover is approximately 4.00% at the annual scale, with larger biases during the spring (5.40%) and winter (5.90%).

Retrieval of Aerosol Optical Depth Under Thin Cirrus from MODIS: Application to an Ocean Algorithm

NASA Technical Reports Server (NTRS)

Lee, Jaehwa; Hsu, Nai-Yung Christina; Sayer, Andrew Mark; Bettenhausen, Corey

2013-01-01

A strategy for retrieving aerosol optical depth (AOD) under conditions of thin cirrus coverage from the Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. We adopt an empirical method that derives the cirrus contribution to measured reflectance in seven bands from the visible to shortwave infrared (0.47, 0.55, 0.65, 0.86, 1.24, 1.63, and 2.12 µm, commonly used for AOD retrievals) by using the correlations between the top-of-atmosphere (TOA) reflectance at 1.38 micron and these bands. The 1.38 micron band is used due to its strong absorption by water vapor and allows us to extract the contribution of cirrus clouds to TOA reflectance and create cirrus-corrected TOA reflectances in the seven bands of interest. These cirrus-corrected TOA reflectances are then used in the aerosol retrieval algorithm to determine cirrus-corrected AOD. The cirrus correction algorithm reduces the cirrus contamination in the AOD data as shown by a decrease in both magnitude and spatial variability of AOD over areas contaminated by thin cirrus. Comparisons of retrieved AOD against Aerosol Robotic Network observations at Nauru in the equatorial Pacific reveal that the cirrus correction procedure improves the data quality: the percentage of data within the expected error +/-(0.03 + 0.05 ×AOD) increases from 40% to 80% for cirrus-corrected points only and from 80% to 86% for all points (i.e., both corrected and uncorrected retrievals). Statistical comparisons with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrievals are also carried out. A high correlation (R = 0.89) between the CALIOP cirrus optical depth and AOD correction magnitude suggests potential applicability of the cirrus correction procedure to other MODIS-like sensors.

Invisible Cirrus Clouds

NASA Technical Reports Server (NTRS)

2002-01-01

The Moderate-resolution Imaging Spectroradiometer's (MODIS') cloud detection capability is so sensitive that it can detect clouds that would be indistinguishable to the human eye. This pair of images highlights MODIS' ability to detect what scientists call 'sub-visible cirrus.' The image on top shows the scene using data collected in the visible part of the electromagnetic spectrum-the part our eyes can see. Clouds are apparent in the center and lower right of the image, while the rest of the image appears to be relatively clear. However, data collected at 1.38um (lower image) show that a thick layer of previously undetected cirrus clouds obscures the entire scene. These kinds of cirrus are called 'sub-visible' because they can't be detected using only visible light. MODIS' 1.38um channel detects electromagnetic radiation in the infrared region of the spectrum. These images were made from data collected on April 4, 2000. Image courtesy Mark Gray, MODIS Atmosphere Team

Correcting for trace gas absorption when retrieving aerosol optical depth from satellite observations of reflected shortwave radiation

NASA Astrophysics Data System (ADS)

Patadia, Falguni; Levy, Robert C.; Mattoo, Shana

2018-06-01

Retrieving aerosol optical depth (AOD) from top-of-atmosphere (TOA) satellite-measured radiance requires separating the aerosol signal from the total observed signal. Total TOA radiance includes signal from the underlying surface and from atmospheric constituents such as aerosols, clouds and gases. Multispectral retrieval algorithms, such as the dark-target (DT) algorithm that operates upon the Moderate Resolution Imaging Spectroradiometer (MODIS, on board Terra and Aqua satellites) and Visible Infrared Imaging Radiometer Suite (VIIRS, on board Suomi-NPP) sensors, use wavelength bands in window regions. However, while small, the gas absorptions in these bands are non-negligible and require correction. In this paper, we use the High-resolution TRANsmission (HITRAN) database and Line-By-Line Radiative Transfer Model (LBLRTM) to derive consistent gas corrections for both MODIS and VIIRS wavelength bands. Absorptions from H2O, CO2 and O3 are considered, as well as other trace gases. Even though MODIS and VIIRS bands are similar, they are different enough that applying MODIS-specific gas corrections to VIIRS observations results in an underestimate of global mean AOD (by 0.01), but with much larger regional AOD biases of up to 0.07. As recent studies have been attempting to create a long-term data record by joining multiple satellite data sets, including MODIS and VIIRS, the consistency of gas correction has become even more crucial.

Global statistics of liquid water content and effective number concentration of water clouds over ocean derived from combined CALIPSO and MODIS measurements

NASA Astrophysics Data System (ADS)

Hu, Y.; Vaughan, M.; McClain, C.; Behrenfeld, M.; Maring, H.; Anderson, D.; Sun-Mack, S.; Flittner, D.; Huang, J.; Wielicki, B.; Minnis, P.; Weimer, C.; Trepte, C.; Kuehn, R.

2007-06-01

This study presents an empirical relation that links the volume extinction coefficients of water clouds, the layer integrated depolarization ratios measured by lidar, and the effective radii of water clouds derived from collocated passive sensor observations. Based on Monte Carlo simulations of CALIPSO lidar observations, this method combines the cloud effective radius reported by MODIS with the lidar depolarization ratios measured by CALIPSO to estimate both the liquid water content and the effective number concentration of water clouds. The method is applied to collocated CALIPSO and MODIS measurements obtained during July and October of 2006, and January 2007. Global statistics of the cloud liquid water content and effective number concentration are presented.

Remote sensing of smoke, clouds, and radiation using AVIRIS during SCAR experiments

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Remer, Lorraine; Kaufman, Yorman J.

1995-01-01

During the past two years, researchers from several institutes joined together to take part in two SCAR experiments. The SCAR-A (Sulfates, Clouds And Radiation - Atlantic) took place in the mid-Atlantic region of the United States in July, 1993. remote sensing data were acquired with the Airborne Visible Infrared Imaging Spectrometer (AVIRIS), the MODIS Airborne Simulator (MAS), and a RC-10 mapping camera from an ER-2 aircraft at 20 km. In situ measurements of aerosol and cloud microphysical properties were made with a variety of instruments equipped on the University of Washington's C-131A research aircraft. Ground based measurements of aerosol optical depths and particle size distributions were made using a network of sunphotometers. The main purpose of SCAR-A experiment was to study the optical, physical and chemical properties of sulfate aerosols and their interaction with clouds and radiation. Sulfate particles are believed to affect the energy balance of the earth by directly reflecting solar radiation back to space and by increasing the cloud albedo. The SCAR-C (Smoke, Clouds And Radiation - California) took place on the west coast areas during September - October of 1994. Sets of aircraft and ground-based instruments, similar to those used during SCAR-A, were used during SCAR-C. Remote sensing of fires and smoke from AVIRIS and MAS imagers on the ER-2 aircraft was combined with a complete in situ characterization of the aerosol and trace gases from the C-131A aircraft of the University of Washington and the Cesna aircraft from the U.S. Forest Service. The comprehensive data base acquired during SCAR-A and SCAR-C will contribute to a better understanding of the role of clouds and aerosols in global change studies. The data will also be used to develop satellite remote sensing algorithms from MODIS on the Earth Observing System.

Sensitivity of Aerosol Multi-Sensor Daily Data Intercomparison to the Level 3 Dataday Definition

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory; Lary, David; Shen, Suhung; Lynnes, Christopher

2010-01-01

Topics include: why people use Level 3 products, why someone might go wrong with Level 3 products, differences in L3 from different sensors, Level 3 data day definition, MODIS vs. MODIS, AOD MODIS Terra vs. Aqua in Pacific, AOD Aqua MODIS vs. MISR correlation map, MODIS vs MISR on Terra, MODIS atmospheric data day definition, orbit time difference for Terra and Aqua 2009-01-06, maximum time difference for Terra (Calendar day), artifact explains, data day definitions, local time distribution, spatial (local time) data day definition, maximum time difference between Terra and Aqua, Removing the artifact in 16-day AOD correlation, MODIS cloud top pressure, and MODIS Terra and Aqua vs. AIRS cloud top pressure.

Comparison of cloud optical depth and cloud mask applying BRDF model-based background surface reflectance

NASA Astrophysics Data System (ADS)

Kim, H. W.; Yeom, J. M.; Woo, S. H.

2017-12-01

Over the thin cloud region, satellite can simultaneously detect the reflectance from thin clouds and land surface. Since the mixed reflectance is not the exact cloud information, the background surface reflectance should be eliminated to accurately distinguish thin cloud such as cirrus. In the previous research, Kim et al (2017) was developed the cloud masking algorithm using the Geostationary Ocean Color Imager (GOCI), which is one of significant instruments for Communication, Ocean, and Meteorology Satellite (COMS). Although GOCI has 8 spectral channels including visible and near infra-red spectral ranges, the cloud masking has quantitatively reasonable result when comparing with MODIS cloud mask (Collection 6 MYD35). Especially, we noticed that this cloud masking algorithm is more specialized in thin cloud detections through the validation with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data. Because this cloud masking method was concentrated on eliminating background surface effects from the top-of-atmosphere (TOA) reflectance. Applying the difference between TOA reflectance and the bi-directional reflectance distribution function (BRDF) model-based background surface reflectance, cloud areas both thick cloud and thin cloud can be discriminated without infra-red channels which were mostly used for detecting clouds. Moreover, when the cloud mask result was utilized as the input data when simulating BRDF model and the optimized BRDF model-based surface reflectance was used for the optimized cloud masking, the probability of detection (POD) has higher value than POD of the original cloud mask. In this study, we examine the correlation between cloud optical depth (COD) and its cloud mask result. Cloud optical depths mostly depend on the cloud thickness, the characteristic of contents, and the size of cloud contents. COD ranges from less than 0.1 for thin clouds to over 1000 for the huge cumulus due to scattering by droplets. With the cloud optical depth of CALIPSO, the cloud masking result can be more improved since we can figure out how deep cloud is. To validate the cloud mask and the correlation result, the atmospheric retrieval will be computed to compare the difference between TOA reflectance and the simulated surface reflectance.

Improvements of top-of-atmosphere and surface irradiance computations with CALIPSO-, CloudSat-, and MODIS-derived cloud and aerosol properties

NASA Astrophysics Data System (ADS)

Kato, Seiji; Rose, Fred G.; Sun-Mack, Sunny; Miller, Walter F.; Chen, Yan; Rutan, David A.; Stephens, Graeme L.; Loeb, Norman G.; Minnis, Patrick; Wielicki, Bruce A.; Winker, David M.; Charlock, Thomas P.; Stackhouse, Paul W., Jr.; Xu, Kuan-Man; Collins, William D.

2011-10-01

One year of instantaneous top-of-atmosphere (TOA) and surface shortwave and longwave irradiances are computed using cloud and aerosol properties derived from instruments on the A-Train Constellation: the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, the CloudSat Cloud Profiling Radar (CPR), and the Aqua Moderate Resolution Imaging Spectrometer (MODIS). When modeled irradiances are compared with those computed with cloud properties derived from MODIS radiances by a Clouds and the Earth's Radiant Energy System (CERES) cloud algorithm, the global and annual mean of modeled instantaneous TOA irradiances decreases by 12.5 W m-2 (5.0%) for reflected shortwave and 2.5 W m-2 (1.1%) for longwave irradiances. As a result, the global annual mean of instantaneous TOA irradiances agrees better with CERES-derived irradiances to within 0.5W m-2 (out of 237.8 W m-2) for reflected shortwave and 2.6W m-2 (out of 240.1 W m-2) for longwave irradiances. In addition, the global annual mean of instantaneous surface downward longwave irradiances increases by 3.6 W m-2 (1.0%) when CALIOP- and CPR-derived cloud properties are used. The global annual mean of instantaneous surface downward shortwave irradiances also increases by 8.6 W m-2 (1.6%), indicating that the net surface irradiance increases when CALIOP- and CPR-derived cloud properties are used. Increasing the surface downward longwave irradiance is caused by larger cloud fractions (the global annual mean by 0.11, 0.04 excluding clouds with optical thickness less than 0.3) and lower cloud base heights (the global annual mean by 1.6 km). The increase of the surface downward longwave irradiance in the Arctic exceeds 10 W m-2 (˜4%) in winter because CALIOP and CPR detect more clouds in comparison with the cloud detection by the CERES cloud algorithm during polar night. The global annual mean surface downward longwave irradiance of 345.4 W m-2 is estimated by combining the modeled instantaneous surface longwave irradiance computed with CALIOP and CPR cloud profiles with the global annual mean longwave irradiance from the CERES product (AVG), which includes the diurnal variation of the irradiance. The estimated bias error is -1.5 W m-2 and the uncertainty is 6.9 W m-2. The uncertainty is predominately caused by the near-surface temperature and column water vapor amount uncertainties.

Evaluation of NCAR CAM5 Simulated Marine Boundary Layer Cloud Properties Using a Combination of Satellite and Surface Observations

NASA Astrophysics Data System (ADS)

Zhang, Z.; Song, H.; Wang, M.; Ghan, S. J.; Dong, X.

2016-12-01

he main objective of this study is to systematically evaluate the MBL cloud properties simulated in CAM5 family models using a combination of satellite-based CloudSat/MODIS observations and ground-based observations from the ARM Azores site, with a special focus on MBL cloud microphysics and warm rain process. First, we will present a global evaluation based on satellite observations and retrievals. We will compare global cloud properties (e.g., cloud fraction, cloud vertical structure, cloud CER, COT, and LWP, as well as drizzle frequency and intensity diagnosed using the CAM5-COSP instrumental simulators) simulated in the CAM5 models with the collocated CloudSat and MODIS observations. We will also present some preliminary results from a regional evaluation based mainly on ground observations from ARM Azores site. We will compare MBL cloud properties simulated in CAM5 models over the ARM Azores site with collocated satellite (MODIS and CloudSat) and ground-based observations from the ARM site.

Principles in Remote Sensing of Aerosol from MODIS Over Land and Ocean

NASA Technical Reports Server (NTRS)

Remer, L. A.; Kaufman, Y. J.; Tanre, D.; Chu, D. A.

1999-01-01

The well-calibrated spectral radiances measured by MODIS will be processed to retrieve daily aerosol properties that include optical thickness and mass loading over land and optical thickness, the mean particle size of the dominant mode and the ratio between aerosol modes over ocean. In addition, after launch, aerosol single scattering albedo will be calculated as an experimental product. The retrieval process over land is based on a dark target method that identifies appropriate targets in the mid-IR channels and uses an empirical relationship found between the mid-ER and the visible channels to estimate surface reflectance in the visible from the mid-HZ reflectance measured by satellite. The method employs new aerosol models for industrial, smoke and dust aerosol. The process for retrieving aerosol over the ocean makes use of the wide spectral band from 0.55-2.13 microns and a look-up table constructed from combinations of five accumulation modes and five coarse modes. Both the over land and over ocean algorithms have been validated with satellite and airborne radiance measurements. We estimate that MODIS will be able to measure aerosol optical thickness (t) to within 0.05 +/- 0.2t over land and to within 0.05 +/- 0.05t over ocean. Much of the earth's surface is located far from aerosol sources and experience very low aerosol optical thickness. Will the accuracy expected from MODIS retrievals be sufficient to measure the global aerosol direct and indirect forcing? We are attempting to answer this question using global model results and cloud climatology.

Using Airborne High Spectral Resolution Lidar Data to Evaluate Combined Active Plus Passive Retrievals of Aerosol Extinction Profiles

NASA Technical Reports Server (NTRS)

Burton, S. P.; Ferrare, R. A.; Hostetler, C. A.; Hair, J. W.; Kittaka, C.; Vaughn, M. A.; Remer, L. A.

2010-01-01

We derive aerosol extinction profiles from airborne and space-based lidar backscatter signals by constraining the retrieval with column aerosol optical thickness (AOT), with no need to rely on assumptions about aerosol type or lidar ratio. The backscatter data were acquired by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. The HSRL also simultaneously measures aerosol extinction coefficients independently using the high spectral resolution lidar technique, thereby providing an ideal data set for evaluating the retrieval. We retrieve aerosol extinction profiles from both HSRL and CALIOP attenuated backscatter data constrained with HSRL, Moderate-Resolution Imaging Spectroradiometer (MODIS), and Multiangle Imaging Spectroradiometer column AOT. The resulting profiles are compared with the aerosol extinction measured by HSRL. Retrievals are limited to cases where the column aerosol thickness is greater than 0.2 over land and 0.15 over water. In the case of large AOT, the results using the Aqua MODIS constraint over water are poorer than Aqua MODIS over land or Terra MODIS. The poorer results relate to an apparent bias in Aqua MODIS AOT over water observed in August 2007. This apparent bias is still under investigation. Finally, aerosol extinction coefficients are derived from CALIPSO backscatter data using AOT from Aqua MODIS for 28 profiles over land and 9 over water. They agree with coincident measurements by the airborne HSRL to within +/-0.016/km +/- 20% for at least two-thirds of land points and within +/-0.028/km +/- 20% for at least two-thirds of ocean points.

A consideration of the availableness of MODIS data to assess a volcanic ash fall

NASA Astrophysics Data System (ADS)

Tomiyama, N.; Yonezawa, C.; Yamakoshi, T.

It is important to grasp the situation of the ash fall at short interval for a volcanic disaster-prevention. Clouds and volcanic smokes reduce the opportunities to observe a volcano by a satellite's optical sensor. Therefore it is preferable to use data of a sensor that is able to observe same area with high frequency. MODIS sees every point on the earth every 1-2 days and provides NDVI data with 250m spatial resolutions. The purpose of this study is to consider the availableness of MODIS data to assess the situation of the volcanic ash fall. The test site is Miyake-jima, one of the active volcanic island in Japan. It is verified that a rate of change of NDVI between before and after erruptions correlates with the amounts of ash fall.

A new chemistry option in WRF/Chem v. 3.4 for the simulation of direct and indirect aerosol effects using VBS: evaluation against IMPACT-EUCAARI data

NASA Astrophysics Data System (ADS)

Tuccella, P.; Curci, G.; Grell, G. A.; Visconti, G.; Crumeroylle, S.; Schwarzenboeck, A.; Mensah, A. A.

2015-02-01

A parameterization for secondary organic aerosol (SOA) production based on the volatility basis set (VBS) approach has been coupled with microphysics and radiative scheme in WRF/Chem model. The new chemistry option called "RACM/MADE/VBS" was evaluated on a cloud resolving scale against ground-based and aircraft measurements collected during the IMPACT-EUCAARI campaign, and complemented with satellite data from MODIS. The day-to-day variability and the diurnal cycle of ozone (O3) and nitrogen oxides (NOx) at the surface is captured by the model. Surface aerosol mass of sulphate (SO4), nitrate (NO3), ammonium (NH4), and organic matter (OM) is simulated with a correlation larger than 0.55. WRF/Chem captures the vertical profile of the aerosol mass in both the planetary boundary layer (PBL) and free troposphere (FT) as a function of the synoptic condition, but the model does not capture the full range of the measured concentrations. Predicted OM concentration is at the lower end of the observed mass. The bias may be attributable to the missing aqueous chemistry processes of organic compounds, the uncertainties in meteorological fields, the assumption on the deposition velocity of condensable organic vapours, and the uncertainties in the anthropogenic emissions of primary organic carbon. Aerosol particle number concentration (condensation nuclei, CN) is overestimated by a factor 1.4 and 1.7 within PBL and FT, respectively. Model bias is most likely attributable to the uncertainties of primary particle emissions (mostly in the PBL) and to the nucleation rate. The overestimation of simulated cloud condensation nuclei (CCN) is more contained with respect to that of CN. The CCN efficiency, which is a measure of the ability of aerosol particles to nucleate cloud droplets, is underestimated by a factor of 1.5 and 3.8 in the PBL and FT, respectively. The comparison with MODIS data shows that the model overestimates the aerosol optical thickness (AOT). The domain averages (for one day) are 0.38 ± 0.12 and 0.42 ± 0.10 for MODIS and WRF/Chem data, respectively. Cloud water path (CWP) is overestimated on average by a factor of 1.7, whereas modelled cloud optical thickness (COT) agrees with observations within 10%. In a sensitivity test where the SOA was not included, simulated CWP is reduced by 40%, and its distribution function shifts toward lower values with respect to the reference run with SOA. The sensitivity test exhibits also 10% more optically thin clouds (COT < 40) and an average COT roughly halved. Moreover, the run with SOA shows convective clouds with an enhanced content of liquid and frozen hydrometers, and stronger updrafts and downdrafts. Considering that the previous version of WRF/Chem coupled with a modal aerosol module predicted very low SOA content (SORGAM mechanism) the new proposed option may lead to a better characterization of aerosol-cloud feedbacks.

Impact of aerosols, dust, water vapor and clouds on fair weather PG and implications for the Carnegie curve

NASA Astrophysics Data System (ADS)

Kourtidis, Konstantinos; Georgoulias, Aristeidis

2017-04-01

We studied the impact of anthropogenic aerosols, fine mode natural aerosols, Saharan dust, atmospheric water vapor, cloud fraction, cloud optical depth and cloud top height on the magnitude of fair weather PG at the rural station of Xanthi. Fair weather PG was measured in situ while the other parameters were obtained from the MODIS instrument onboard the Terra and Aqua satellites. All of the above parameteres were found to impact fair weather PG magnitude. Regarding aerosols, the impact was larger for Saharan dust and fine mode natural aerosols whereas regarding clouds the impact was larger for cloud fraction while less than that of aerosols. Water vapour and ice precipitable water were also found to influence fair weather PG. Since aerosols and water are ubiquitous in the atmosphere and exhibit large spatial and temporal variability, we postulate that our understanding of the Carnegie curve might need revision.

MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

NASA Technical Reports Server (NTRS)

Riggs, George A.; Hall, Dorothy K.

2010-01-01

Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

Global statistics of liquid water content and effective number density of water clouds over ocean derived from combined CALIPSO and MODIS measurements

NASA Astrophysics Data System (ADS)

Hu, Y.; Vaughan, M.; McClain, C.; Behrenfeld, M.; Maring, H.; Anderson, D.; Sun-Mack, S.; Flittner, D.; Huang, J.; Wielicki, B.; Minnis, P.; Weimer, C.; Trepte, C.; Kuehn, R.

2007-03-01

This study presents an empirical relation that links layer integrated depolarization ratios, the extinction coefficients, and effective radii of water clouds, based on Monte Carlo simulations of CALIPSO lidar observations. Combined with cloud effective radius retrieved from MODIS, cloud liquid water content and effective number density of water clouds are estimated from CALIPSO lidar depolarization measurements in this study. Global statistics of the cloud liquid water content and effective number density are presented.

Two MODIS Aerosol Products over Ocean on the Terra and Aqua CERES SSF Datasets.

NASA Astrophysics Data System (ADS)

Ignatov, Alexander; Minnis, Patrick; Loeb, Norman; Wielicki, Bruce; Miller, Walter; Sun-Mack, Sunny; Tanré, Didier; Remer, Lorraine; Laszlo, Istvan; Geier, Erika

2005-04-01

Understanding the impact of aerosols on the earth's radiation budget and the long-term climate record requires consistent measurements of aerosol properties and radiative fluxes. The Clouds and the Earth's Radiant Energy System (CERES) Science Team combines satellite-based retrievals of aerosols, clouds, and radiative fluxes into Single Scanner Footprint (SSF) datasets from the Terra and Aqua satellites. Over ocean, two aerosol products are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) using different sampling and aerosol algorithms. The primary, or M, product is taken from the standard multispectral aerosol product developed by the MODIS aerosol group while a simpler, secondary [Advanced Very High Resolution Radiometer (AVHRR) like], or A, product is derived by the CERES Science Team using a different cloud clearing method and a single-channel aerosol algorithm. Two aerosol optical depths (AOD), τA1 and τA2, are derived from MODIS bands 1 (0.644 μm) and 6 (1.632 μm) resembling the AVHRR/3 channels 1 and 3A, respectively. On Aqua the retrievals are made in band 7 (2.119 μm) because of poor quality data from band 6. The respective Ångström exponents can be derived from the values of τ. The A product serves as a backup for the M product. More importantly, the overlap of these aerosol products is essential for placing the 20+ year heritage AVHRR aerosol record in the context of more advanced aerosol sensors and algorithms such as that used for the M product.This study documents the M and A products, highlighting their CERES SSF specifics. Based on 2 weeks of global Terra data, coincident M and A AODs are found to be strongly correlated in both bands. However, both domains in which the M and A aerosols are available, and the respective τ/α statistics significantly differ because of discrepancies in sampling due to differences in cloud and sun-glint screening. In both aerosol products, correlation is observed between the retrieved aerosol parameters (τ/α) and ambient cloud amount, with the dependence in the M product being more pronounced than in the A product.

Retrieval of ice cloud properties from Himawari-8 satellite measurements by Voronoi ice particle model

NASA Astrophysics Data System (ADS)

Letu, H.; Nagao, T. M.; Nakajima, T. Y.; Ishimoto, H.; Riedi, J.; Shang, H.

2017-12-01

Ice cloud property product from satellite measurements is applicable in climate change study, numerical weather prediction, as well as atmospheric study. Ishimoto et al., (2010) and Letu et al., (2016) developed a single scattering property of the highly irregular ice particle model, called the Voronoi model for developing ice cloud product of the GCOM-C satellite program. It is investigated that Voronoi model has a good performance on retrieval of the ice cloud properties by comparing it with other well-known scattering models. Cloud property algorithm (Nakajima et al., 1995, Ishida and Nakajima., 2009, Ishimoto et al., 2009, Letu et al., 2012, 2014, 2016) of the GCOM-C satellite program is improved to produce the Himawari-8/AHI cloud products based on the variation of the solar zenith angle. Himawari-8 is the new-generational geostationary meteorological satellite, which is successfully launched by the Japan Meteorological Agency (JMA) on 7 October 2014. In this study, ice cloud optical and microphysical properties are simulated from RSTAR radiative transfer code by using various model. Scattering property of the Voronoi model is investigated for developing the AHI ice cloud products. Furthermore, optical and microphysical properties of the ice clouds are retrieved from Himawari-8/AHI satellite measurements. Finally, retrieval results from Himawari-8/AHI are compared to MODIS-C6 cloud property products for validation of the AHI cloud products.

A new chemistry option in WRF-Chem v. 3.4 for the simulation of direct and indirect aerosol effects using VBS: evaluation against IMPACT-EUCAARI data

NASA Astrophysics Data System (ADS)

Tuccella, P.; Curci, G.; Grell, G. A.; Visconti, G.; Crumeyrolle, S.; Schwarzenboeck, A.; Mensah, A. A.

2015-09-01

A parameterization for secondary organic aerosol (SOA) production based on the volatility basis set (VBS) approach has been coupled with microphysics and radiative schemes in the Weather Research and Forecasting model with Chemistry (WRF-Chem) model. The new chemistry option called "RACM-MADE-VBS-AQCHEM" was evaluated on a cloud resolving scale against ground-based and aircraft measurements collected during the IMPACT-EUCAARI (Intensive Cloud Aerosol Measurement Campaign - European Integrated project on Aerosol Cloud Climate and Air quality interaction) campaign, and complemented with satellite data from MODIS. The day-to-day variability and the diurnal cycle of ozone (O3) and nitrogen oxides (NOx) at the surface are captured by the model. Surface aerosol mass concentrations of sulfate (SO4), nitrate (NO3), ammonium (NH4), and organic matter (OM) are simulated with correlations larger than 0.55. WRF-Chem captures the vertical profile of the aerosol mass concentration in both the planetary boundary layer (PBL) and free troposphere (FT) as a function of the synoptic condition, but the model does not capture the full range of the measured concentrations. Predicted OM concentration is at the lower end of the observed mass concentrations. The bias may be attributable to the missing aqueous chemistry processes of organic compounds and to uncertainties in meteorological fields. A key role could be played by assumptions on the VBS approach such as the SOA formation pathways, oxidation rate, and dry deposition velocity of organic condensable vapours. Another source of error in simulating SOA is the uncertainties in the anthropogenic emissions of primary organic carbon. Aerosol particle number concentration (condensation nuclei, CN) is overestimated by a factor of 1.4 and 1.7 within the PBL and FT, respectively. Model bias is most likely attributable to the uncertainties of primary particle emissions (mostly in the PBL) and to the nucleation rate. Simulated cloud condensation nuclei (CCN) are also overestimated, but the bias is more contained with respect to that of CN. The CCN efficiency, which is a characterization of the ability of aerosol particles to nucleate cloud droplets, is underestimated by a factor of 1.5 and 3.8 in the PBL and FT, respectively. The comparison with MODIS data shows that the model overestimates the aerosol optical thickness (AOT). The domain averages (for 1 day) are 0.38 ± 0.12 and 0.42 ± 0.10 for MODIS and WRF-Chem data, respectively. The droplet effective radius (Re) in liquid-phase clouds is underestimated by a factor of 1.5; the cloud liquid water path (LWP) is overestimated by a factor of 1.1-1.6. The consequence is the overestimation of average liquid cloud optical thickness (COT) from a few percent up to 42 %. The predicted cloud water path (CWP) in all phases displays a bias in the range +41-80 %, whereas the bias of COT is about 15 %. In sensitivity tests where we excluded SOA, the skills of the model in reproducing the observed patterns and average values of the microphysical and optical properties of liquid and all phase clouds decreases. Moreover, the run without SOA (NOSOA) shows convective clouds with an enhanced content of liquid and frozen hydrometers, and stronger updrafts and downdrafts. Considering that the previous version of WRF-Chem coupled with a modal aerosol module predicted very low SOA content (secondary organic aerosol model (SORGAM) mechanism) the new proposed option may lead to a better characterization of aerosol-cloud feedbacks.

Six years of surface remote sensing of stratiform warm clouds in marine and continental air over Mace Head, Ireland

NASA Astrophysics Data System (ADS)

Preißler, Jana; Martucci, Giovanni; Saponaro, Giulia; Ovadnevaite, Jurgita; Vaishya, Aditya; Kolmonen, Pekka; Ceburnis, Darius; Sogacheva, Larisa; de Leeuw, Gerrit; O'Dowd, Colin

2016-12-01

A total of 118 stratiform water clouds were observed by ground-based remote sensing instruments at the Mace Head Atmospheric Research Station on the west coast of Ireland from 2009 to 2015. Microphysical and optical characteristics of these clouds were studied as well as the impact of aerosols on these properties. Microphysical and optical cloud properties were derived using the algorithm SYRSOC (SYnergistic Remote Sensing Of Clouds). Ground-based in situ measurements of aerosol concentrations and the transport path of air masses at cloud level were investigated as well. The cloud properties were studied in dependence of the prevailing air mass at cloud level and season. We found higher cloud droplet number concentrations (CDNC) and smaller effective radii (reff) with greater pollution. Median CDNC ranged from 60 cm-3 in marine air masses to 160 cm-3 in continental air. Median reff ranged from 8 μm in polluted conditions to 10 μm in marine air. Effective droplet size distributions were broader in marine than in continental cases. Cloud optical thickness (COT) and albedo were lower in cleaner air masses and higher in more polluted conditions, with medians ranging from 2.1 to 4.9 and 0.22 to 0.39, respectively. However, calculation of COT and albedo was strongly affected by liquid water path (LWP) and departure from adiabatic conditions. A comparison of SYRSOC results with MODIS (Moderate-Resolution Imaging Spectroradiometer) observations showed large differences for LWP and COT but good agreement for reff with a linear fit with slope near 1 and offset of -1 μm.

Towards Continuity in Cloud Properties from MODIS and Suomi-NPP Polar-Orbiting Sensors

NASA Astrophysics Data System (ADS)

Baum, B. A.; Menzel, P.; Gladkova, I.; Heidinger, A. K.

2015-12-01

The intent of this talk is to discuss the progress and issues involved with developing a continuous record of cloud properties since 1978, beginning with the High Resolution Infrared Radiation Sounder (HIRS), then MODIS on the NASA Terra/Aqua platforms, and into the future from merged CrIS and VIIRS data. The MODIS measurements include infrared (IR) window radiances at 8.5-, 11- and 12-μm and four 15-μm channels in the broad CO2 absorption band. Cloud top pressure/height and emissivity are derived using a technique in which the strength is in retrievals for mid-to-high clouds but less so for low clouds where there is little thermal contrast with the surface. Additionally, MODIS provides a decadal IR cloud phase product. The goal now is to extend this continuity from HIRS and MODIS to the S-NPP era. However, there is one large drawback to consider: VIIRS has no infrared (IR) absorption channels. The lack of at least one IR absorption channel on VIIRS degrades the accuracy of the cloud properties. There is a solution: we can construct a 13.3-μm channel from a combination of VIIRS and CrIS (Cross-track Infrared Sounder). The approach involves using the high spatial resolution VIIRS IR window channels in combination with a lower spatial resolution 13.3-μm channel derived using CrIS high spectral resolution measurements. The result is a 13.3-μm pseudo-channel at the VIIRS pixel spatial resolution of 750 m (i.e., M-band resolution). The radiometric accuracy of this approach was tested using MODIS and AIRS, and found to be within 1-2%. The availability of the pseudo-channel increases the potential for achieving continuity between MODIS and S-NPP. Since future platforms will likely continue with a pairing of an imager and hyperspectral sounder, this work lays a foundation for future cloud product continuity. We will show how the use of this new channel will impact the cloud height and phase products.

Extending MODIS Deep Blue Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: First Results

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Shinozuka, Y.; Schmid, B.

2015-01-01

Absorbing smoke or mineral dust aerosols above clouds (AAC) are a frequent occurrence in certain regions and seasons. Operational aerosol retrievals from sensors like MODIS omit AAC because they are designed to work only over cloud-free scenes. However, AAC can in principle be quantified by these sensors in some situations (e.g. Jethva et al., 2013; Meyer et al., 2013). We present a summary of some analyses of the potential of MODIS-like instruments for this purpose, along with two case studies using airborne observations from the Ames Airborne Tracking Sunphotometer (AATS; http://geo.arc.nasa.gov/sgg/AATS-website/) as a validation data source for a preliminary AAC algorithm applied to MODIS measurements. AAC retrievals will eventually be added to the MODIS Deep Blue (Hsu et al., 2013) processing chain.

Assessment of aerosol indirect effects over Indian subcontinent using long term MODIS aerosol and cloud data

NASA Astrophysics Data System (ADS)

Das, Saurabh; Maitra, Animesh; Saha, Upal; De, Arijit

Aerosols have direct consequences on climate research and in climate change study due to its role in radiative forcing. The modulation of cloud properties due to the presence of aerosol is another important factor in understanding of the climate change scenario. However, the relationship between these two is mostly indirect as the meteorological conditions have a strong impact on the relationship. Cloud effective radius and decreases in precipitation efficiency are interlinked with the increase of aerosols. The net effect is that the cloud liquid water path and cloud lifetime increase with AOD. Though these facts are included in the global climate models (GCM), the quantitative estimation of aerosol indirect efficiency (AIE) varied widely. Some recent studies indicate an increasing trend of the aerosol optical depth over the Indian landmass. The anthropogenic activities are linked with this increase in aerosols. In general, aerosol increase can affect the cloud radius and leads to formation of non-precipitating cloud. However, the chemical composition of aerosols may also be an important factor. It is therefore necessary to have better understanding of the relationship for predicting the future climate which may be affected by such human activities. In this paper, the relation of aerosol optical depth (AOD) with cloud effective radius (CER) has been investigated over the Indian subcontinent using the long term MODIS observations. MODIS can able to provide reliable AOD information over the land surface. It also able to provide information of the cloud effective radius of the same observation point. A grid-wise correlation analysis can thus be performed to estimate the relation between AOD and CER. Result indicates both positive and negative AIE of AOD on CER. To identify the possible reason for such variability in the AIE, the role of anthropogenic aerosols and water vapor is investigated. The study on the efficiency of aerosol indirect effect indicates that a large number of grids with positive efficiency correspond to the water vapor amount of less than 2 mm whereas most of the grids have negative efficiency for water vapor amounts greater than 2 mm. Consequently, humidification of aerosols has also been examined for Indian region, which indicates that the variability in this relation may not be fully explained only by the contribution of water vapor. The role of aerosol sizes on this relation is also estimated by differentiating between fine mode and coarse mode aerosol. The presence of fine mode aerosols as estimated by model simulation and satellite observations show that the combined effect of water vapor and aerosol size can explain the observed positive and negative AIE more effectively. The results have important consequences on the GCM by incorporating the AIE more precisely.

Enhancement of the MODIS Snow and Ice Product Suite Utilizing Image Segmentation

NASA Technical Reports Server (NTRS)

Tilton, James C.; Hall, Dorothy K.; Riggs, George A.

2006-01-01

A problem has been noticed with the current NODIS Snow and Ice Product in that fringes of certain snow fields are labeled as "cloud" whereas close inspection of the data indicates that the correct labeling is a non-cloud category such as snow or land. This occurs because the current MODIS Snow and Ice Product generation algorithm relies solely on the MODIS Cloud Mask Product for the labeling of image pixels as cloud. It is proposed here that information obtained from image segmentation can be used to determine when it is appropriate to override the cloud indication from the cloud mask product. Initial tests show that this approach can significantly reduce the cloud "fringing" in modified snow cover labeling. More comprehensive testing is required to determine whether or not this approach consistently improves the accuracy of the snow and ice product.

Beyond MODIS: Developing an aerosol climate data record

NASA Astrophysics Data System (ADS)

Levy, R. C.; Mattoo, S.; Munchak, L. A.; Patadia, F.; Laszlo, I.; Holz, R.

2013-12-01

As defined by the National Research Council, a climate data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. As one of our most pressing research questions concerns changes in global direct aerosol radiative forcing (DARF), creating an aerosol CDR is of high importance. To reduce our uncertainties in DARF, we need uncertainty in global aerosol optical depth (AOD) reduced to ×0.02 or better, or about 10% of global mean AOD (~0.15-0.20). To quantify aerosol trends with significance, we also need a stable time series at least 20-30 years. By this Fall-2013 AGU meeting, the Moderate Resolution Imaging Spectrometer (MODIS) has been flying on NASA's Terra and Aqua satellites for 14 years and 11.5 years, respectively. During this time, we have fine-tuned the aerosol retrieval algorithms and data processing protocols, resulting in a well characterized product of aerosol optical depth (AOD). MODIS AOD has been extensively compared to ground-based sunphotometer data, showing per-retrieval expected error (EE) of ×(0.03 + 5%) over ocean, and has been generally adopted as a robust and stable environmental data record (EDR). With the 2011 launch of the Visible and Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP, we have begun a new aerosol time series. The VIIRS AOD product has stabilized to the point where, compared to ground-based AERONET sunphotometer, the VIIRS AOD is within similar EE envelope as MODIS. Thus, if VIIRS continues to perform as expected, it too can provide a robust and stable aerosol EDR. What will it take to stitch MODIS and VIIRS into a robust aerosol CDR? Based on the recent experience of MODIS 'Collection 6' development, there are many details of aerosol retrieval that each lead to ×0.01 uncertainties in global AOD. These include 'radiative transfer' assumptions such as calculations for gas absorption and sea-level Rayleigh optical depth, 'decision making' assumptions such as cloud masking and pixel selection, as well as 'retrieval' assumptions such as aerosol type, and surface reflectance model. Also there are instrument issues such as calibration and geo-location, which even on the level of 1-2%, will lead to 10% error in retrieved AOD. At this point, however, many of these issues have been solved, or are being quantified for MODIS and VIIRS. In the past year, we created a generic dark-target aerosol retrieval algorithm, which can be applied to MODIS, VIIRS, or any other sensor with a similar set of wavelength bands. We applied the same radiative transfer codes for creating lookup tables, the same protocols for deriving non-aerosol assumptions, and the same criteria for cloud masking. Although there are still inconsistencies to work out, this generic algorithm is being applied to selected months having VIIRS/MODIS overlap. Comparing to AERONET, and with each other, we quantify the statistical agreement between MODIS and VIIRS, both for the official algorithms run on each sensor, as well as for our generic algorithm run on both.

Method for validating cloud mask obtained from satellite measurements using ground-based sky camera.

PubMed

Letu, Husi; Nagao, Takashi M; Nakajima, Takashi Y; Matsumae, Yoshiaki

2014-11-01

Error propagation in Earth's atmospheric, oceanic, and land surface parameters of the satellite products caused by misclassification of the cloud mask is a critical issue for improving the accuracy of satellite products. Thus, characterizing the accuracy of the cloud mask is important for investigating the influence of the cloud mask on satellite products. In this study, we proposed a method for validating multiwavelength satellite data derived cloud masks using ground-based sky camera (GSC) data. First, a cloud cover algorithm for GSC data has been developed using sky index and bright index. Then, Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data derived cloud masks by two cloud-screening algorithms (i.e., MOD35 and CLAUDIA) were validated using the GSC cloud mask. The results indicate that MOD35 is likely to classify ambiguous pixels as "cloudy," whereas CLAUDIA is likely to classify them as "clear." Furthermore, the influence of error propagations caused by misclassification of the MOD35 and CLAUDIA cloud masks on MODIS derived reflectance, brightness temperature, and normalized difference vegetation index (NDVI) in clear and cloudy pixels was investigated using sky camera data. It shows that the influence of the error propagation by the MOD35 cloud mask on the MODIS derived monthly mean reflectance, brightness temperature, and NDVI for clear pixels is significantly smaller than for the CLAUDIA cloud mask; the influence of the error propagation by the CLAUDIA cloud mask on MODIS derived monthly mean cloud products for cloudy pixels is significantly smaller than that by the MOD35 cloud mask.

Observed Land Impacts on Clouds, Water Vapor, and Rainfall at Continental Scales

NASA Technical Reports Server (NTRS)

Jin, Menglin; King, Michael D.

2005-01-01

How do the continents affect large-scale hydrological cycles? How important can one continent be to the climate system? To address these questions, 4-years of National Aeronautics and Space Administration (NASA) Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations, Tropical Rainfall Measuring Mission (TRMM) observations, and the Global Precipitation Climatology Project (GPCP) global precipitation analysis, were used to assess the land impacts on clouds, rainfall, and water vapor at continental scales. At these scales, the observations illustrate that continents are integrated regions that enhance the seasonality of atmospheric and surface hydrological parameters. Specifically, the continents of Eurasia and North America enhance the seasonality of cloud optical thickness, cirrus fraction, rainfall, and water vapor. Over land, both liquid water and ice cloud effective radii are smaller than over oceans primarily because land has more aerosol particles. In addition, different continents have similar impacts on hydrological variables in terms of seasonality, but differ in magnitude. For example, in winter, North America and Eurasia increase cloud optical thickness to 17.5 and 16, respectively, while in summer, Eurasia has much smaller cloud optical thicknesses than North America. Such different land impacts are determined by each continent s geographical condition, land cover, and land use. These new understandings help further address the land-ocean contrasts on global climate, help validate global climate model simulated land-atmosphere interactions, and help interpret climate change over land.

Stereoscopic, thermal, and true deep cumulus cloud top heights

NASA Astrophysics Data System (ADS)

Llewellyn-Jones, D. T.; Corlett, G. K.; Lawrence, S. P.; Remedios, J. J.; Sherwood, S. C.; Chae, J.; Minnis, P.; McGill, M.

2004-05-01

We compare cloud-top height estimates from several sensors: thermal tops from GOES-8 and MODIS, stereoscopic tops from MISR, and directly measured heights from the Goddard Cloud Physics Lidar on board the ER-2, all collected during the CRYSTAL-FACE field campaign. Comparisons reveal a persistent 1-2 km underestimation of cloud-top heights by thermal imagery, even when the finite optical extinctions near cloud top and in thin overlying cirrus are taken into account. The most severe underestimates occur for the tallest clouds. The MISR "best-sinds" and lidar estimates disagree in very similar ways with thermally estimated tops, which we take as evidence of excellent performance by MISR. Encouraged by this, we use MISR to examine variations in cloud penetration and thermal top height errors in several locations of tropical deep convection over multiple seasons. The goals of this are, first, to learn how cloud penetration depends on the near-tropopause environment; and second, to gain further insight into the mysterious underestimation of tops by thermal imagery.

Sources and Variability of Aerosols and Aerosol-Cloud Interactions in the Arctic

NASA Astrophysics Data System (ADS)

Liu, H.; Zhang, B.; Taylor, P. C.; Moore, R.; Barahona, D.; Fairlie, T. D.; Chen, G.; Ham, S. H.; Kato, S.

2017-12-01

Arctic sea ice in recent decades has significantly declined. This requires understanding of the Arctic surface energy balance, of which clouds are a major driver. However, the mechanisms for the formation and evolution of clouds in the Arctic and the roles of aerosols therein are highly uncertain. Here we conduct data analysis and global model simulations to examine the sources and variability of aerosols and aerosol-cloud interactions in the Arctic. We use the MERRA-2 reanalysis data (2006-present) from the NASA Global Modeling and Assimilation Office (GMAO) to (1) quantify contributions of different aerosol types to the aerosol budget and aerosol optical depths in the Arctic, (2) ­examine aerosol distributions and variability and diagnose the major pathways for mid-latitude pollution transport to the Arctic, including their seasonal and interannual variability, and (3) characterize the distribution and variability of clouds (cloud optical depth, cloud fraction, cloud liquid and ice water path, cloud top height) in the Arctic. We compare MERRA-2 aerosol and cloud properties with those from C3M, a 3-D aerosol and cloud data product developed at NASA Langley Research Center and merged from multiple A-Train satellite (CERES, CloudSat, CALIPSO, and MODIS) observations. We also conduct perturbation experiments using the NASA GEOS-5 chemistry-climate model (with GOCART aerosol module coupled with two-moment cloud microphysics), and discuss the roles of various types of aerosols in the formation and evolution of clouds in the Arctic.

Validation of Satellite Derived Cloud Properties Over the Southeastern Pacific

NASA Astrophysics Data System (ADS)

Ayers, J.; Minnis, P.; Zuidema, P.; Sun-Mack, S.; Palikonda, R.; Nguyen, L.; Fairall, C.

2005-12-01

Satellite measurements of cloud properties and the radiation budget are essential for understanding meso- and large-scale processes that determine the variability in climate over the southeastern Pacific. Of particular interest in this region is the prevalent stratocumulus cloud deck. The stratocumulus albedos are directly related to cloud microphysical properties that need to be accurately characterized in Global Climate Models (GCMs) to properly estimate the Earth's radiation budget. Meteorological observations in this region are sparse causing large uncertainties in initialized model fields. Remote sensing from satellites can provide a wealth of information about the clouds in this region, but it is vital to validate the remotely sensed parameters and to understand their relationship to other parameters that are not directly observed by the satellites. The variety of measurements from the R/V Roger Revelle during the 2003 STRATUS cruise and from the R/V Ron Brown during EPIC 2001 and the 2004 STRATUS cruises are suitable for validating and improving the interpretation of the satellite derived cloud properties. In this study, satellite-derived cloud properties including coverage, height, optical depth, and liquid water path are compared with in situ measurements taken during the EPIC and STRATUS cruises. The remotely sensed values are derived from Geostationary Operational Environmental Satellite (GOES) imager data, Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellites, and from the Visible and Infrared Scanner (VIRS) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. The products from this study will include regional monthly cloud climatologies derived from the GOES data for the 2003 and 2004 cruises as well as micro and macro physical cloud property retrievals centered over the ship tracks from MODIS and VIRS.

An Automatic Cloud Mask Algorithm Based on Time Series of MODIS Measurements

NASA Technical Reports Server (NTRS)

Lyapustin, Alexei; Wang, Yujie; Frey, R.

2008-01-01

Quality of aerosol retrievals and atmospheric correction depends strongly on accuracy of the cloud mask (CM) algorithm. The heritage CM algorithms developed for AVHRR and MODIS use the latest sensor measurements of spectral reflectance and brightness temperature and perform processing at the pixel level. The algorithms are threshold-based and empirically tuned. They don't explicitly address the classical problem of cloud search, wherein the baseline clear-skies scene is defined for comparison. Here, we report on a new CM algorithm which explicitly builds and maintains a reference clear-skies image of the surface (refcm) using a time series of MODIS measurements. The new algorithm, developed as part of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm for MODIS, relies on fact that clear-skies images of the same surface area have a common textural pattern, defined by the surface topography, boundaries of rivers and lakes, distribution of soils and vegetation etc. This pattern changes slowly given the daily rate of global Earth observations, whereas clouds introduce high-frequency random disturbances. Under clear skies, consecutive gridded images of the same surface area have a high covariance, whereas in presence of clouds covariance is usually low. This idea is central to initialization of refcm which is used to derive cloud mask in combination with spectral and brightness temperature tests. The refcm is continuously updated with the latest clear-skies MODIS measurements, thus adapting to seasonal and rapid surface changes. The algorithm is enhanced by an internal dynamic land-water-snow classification coupled with a surface change mask. An initial comparison shows that the new algorithm offers the potential to perform better than the MODIS MOD35 cloud mask in situations where the land surface is changing rapidly, and over Earth regions covered by snow and ice.

Ground and satellite-based remote sensing of mineral dust using AERI spectra and MODIS thermal infrared window brightness temperatures

NASA Astrophysics Data System (ADS)

Hansell, Richard Allen, Jr.

The radiative effects of dust aerosol on our climate system have yet to be fully understood and remain a topic of contemporary research. To investigate these effects, detection/retrieval methods for dust events over major dust outbreak and transport areas have been developed using satellite and ground-based approaches. To this end, both the shortwave and longwave surface radiative forcing of dust aerosol were investigated. The ground-based remote sensing approach uses the Atmospheric Emitted Radiance Interferometer brightness temperature spectra to detect mineral dust events and to retrieve their properties. Taking advantage of the high spectral resolution of the AERI instrument, absorptive differences in prescribed thermal IR window sub-band channels were exploited to differentiate dust from cirrus clouds. AERI data collected during the UAE2 at Al-Ain UAE was employed for dust retrieval. Assuming a specified dust composition model a priori and using the light scattering programs of T-matrix and the finite difference time domain methods for oblate spheroids and hexagonal plates, respectively, dust optical depths have been retrieved and compared to those inferred from a collocated and coincident AERONET sun-photometer dataset. The retrieved optical depths were then used to determine the dust longwave surface forcing during the UAE2. Likewise, dust shortwave surface forcing is investigated employing a differential technique from previous field studies. The satellite-based approach uses MODIS thermal infrared brightness temperature window data for the simultaneous detection/separation of mineral dust and cirrus clouds. Based on the spectral variability of dust emissivity at the 3.75, 8.6, 11 and 12 mum wavelengths, the D*-parameter, BTD-slope and BTD3-11 tests are combined to identify dust and cirrus. MODIS data for the three dust-laden scenes have been analyzed to demonstrate the effectiveness of this detection/separation method. Detected daytime dust and cloud coverage for the Persian Gulf case compare reasonably well to those from the "Deep Blue" algorithm developed at NASA-GSFC. The nighttime dust/cloud detection for the cases surrounding Cape Verde and Niger, West Africa has been validated by comparing to coincident and collocated ground-based micro-pulse lidar measurements.

Evaluating Satellite Retrievals of Smoke Aerosol above Clouds using Airborne High Spectral Resolution Lidar Measurements during ORACLES

NASA Astrophysics Data System (ADS)

Ferrare, R. A.; Burton, S. P.; Cook, A. L.; Harper, D. B.; Hostetler, C. A.; Hair, J. W.; Vaughan, M.; Hu, Y.; Fenn, M. A.; Clayton, M.; Scarino, A. J.; Jethva, H. T.; Sayer, A. M.; Meyer, K.; Torres, O.; Josset, D. B.; Redemann, J.

2017-12-01

The NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL-2) provided extensive measurements of smoke above shallow marine clouds while deployed from the NASA ER-2 aircraft during the NASA EV-S Observations of Aerosols above Clouds and their Interactions (ORACLES) mission. During the first ORACLES field campaign in September 2016, the ER-2 was deployed from Walvis Bay, Namibia and conducted flights over the southeastern Atlantic Ocean. HSRL-2 measured profiles of aerosol backscattering, extinction and aerosol optical depth (AOD) at 355 and 532 nm and aerosol backscattering and depolarization at 1064 nm and so provided an excellent characterization of the widespread smoke layers above shallow marine clouds. OMI, MODIS, and CALIOP satellite retrievals of above cloud AOD (ACAOD) are compared to the HSRL-2 measurements. The OMI above-cloud aerosols data product (OMACA) ACAOD product relies on the spectral contrast produced by aerosol absorption in two near-UV measurements (354 and 388 nm) to derive ACAOD. Two MODIS ACAOD products are examined; the first ("multichannel') relies on the spectral contrast in aerosol absorption derived from reflectance measurements at six MODIS channels from the visible to the shortwave infrared (swIR). The second method is an extension of the "Deep Blue" method and differs from the multichannel method in that it does not use swIR channels. The CALIOP V4 operational and "depolarization ratio (DR)" methods of retrieving ACAOD are also examined. The MODIS and OMI ACAOD values were well correlated (r2>0.6) with the HSRL-2 ACAOD values; bias differences were generally less than about 0.1 at 532 nm (10-30%). The CALIOP operational retrievals missed a significant amount of aerosol and so were biased low by 50-75% compared to HSRL-2. In contrast, the CALIOP DR method produced ACAOD values in excellent agreement (bias differences less than 0.03 (5%)) with HSRL-2. Aerosol extinction profiles computed for the smoke layer using the CALIOP attenuated backscatter profiles and constrained by the CALIOP DR ACAOD retrievals are also found to agree well on average with coincident HSRL-2 extinction profiles. These constrained CALIOP extinction profiles are used to characterize the smoke distribution over this region.

Optical Thickness and Effective Radius Retrievals of Liquid Water Clouds over Ice and Snow Surface

NASA Technical Reports Server (NTRS)

Platnick, S.; King, M. D.; Tsay, S.-C.; Arnold, G. T.; Gerber, H.; Hobbs, P. V.; Rangno, A.

1999-01-01

Cloud optical thickness and effective radius retrievals from solar reflectance measurements traditionally depend on a combination of spectral channels that are absorbing and non-absorbing for liquid water droplets. Reflectances in non-absorbing channels (e.g., 0.67, 0.86 micrometer bands) are largely dependent on cloud optical thickness, while longer wavelength absorbing channels (1.6, 2.1, and 3.7 micrometer window bands) provide cloud particle size information. Retrievals are complicated by the presence of an underlying ice/snow surface. At the shorter wavelengths, sea ice is both bright and highly variable, significantly increasing cloud retrieval uncertainty. However, reflectances at the longer wavelengths are relatively small and may be comparable to that of dark open water. Sea ice spectral albedos derived from Cloud Absorption Radiometer (CAR) measurements during April 1992 and June 1995 Arctic field deployments are used to illustrate these statements. A modification to the traditional retrieval technique is devised. The new algorithm uses a combination of absorbing spectral channels for which the snow/ice albedo is relatively small. Using this approach, preliminary retrievals have been made with the MODIS Airborne Simulator (MAS) imager flown aboard the NASA ER-2 during FIRE-ACE. Data from coordinated ER-2 and University of Washington CV-580 aircraft observations of liquid water stratus clouds on June 3 and June 6, 1998 have been examined. Size retrievals are compared with in situ cloud profile measurements of effective radius made with the CV-580 PMS FSSP probe, and optical thickness retrievals are compared with extinction profiles derived from the Gerber Scientific "g-meter" probe. MAS retrievals are shown to be in good agreement with the in situ measurements.

Use of MODIS Cloud Top Pressure to Improve Assimilation Yields of AIRS Radiances in GSI

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Srikishen, Jayanthi

2014-01-01

Radiances from hyperspectral sounders such as the Atmospheric Infrared Sounder (AIRS) are routinely assimilated both globally and regionally in operational numerical weather prediction (NWP) systems using the Gridpoint Statistical Interpolation (GSI) data assimilation system. However, only thinned, cloud-free radiances from a 281-channel subset are used, so the overall percentage of these observations that are assimilated is somewhere on the order of 5%. Cloud checks are performed within GSI to determine which channels peak above cloud top; inaccuracies may lead to less assimilated radiances or introduction of biases from cloud-contaminated radiances.Relatively large footprint from AIRS may not optimally represent small-scale cloud features that might be better resolved by higher-resolution imagers like the Moderate Resolution Imaging Spectroradiometer (MODIS). Objective of this project is to "swap" the MODIS-derived cloud top pressure (CTP) for that designated by the AIRS-only quality control within GSI to test the hypothesis that better representation of cloud features will result in higher assimilated radiance yields and improved forecasts.

Investigation of Cloud Properties and Atmospheric Profiles with MODIS

NASA Technical Reports Server (NTRS)

Menzel, Paul; Ackerman, Steve; Moeller, Chris; Gumley, Liam; Strabala, Kathy; Frey, Richard; Prins, Elaine; LaPorte, Dan; Wolf, Walter

1997-01-01

The WINter Cloud Experiment (WINCE) was directed and supported by personnel from the University of Wisconsin in January and February. Data sets of good quality were collected by the MODIS Airborne Simulator (MAS) and other instruments on the NASA ER2; they will be used to develop and validate cloud detection and cloud property retrievals over winter scenes (especially over snow). Software development focused on utilities needed for all of the UW product executables; preparations for Version 2 software deliveries were almost completed. A significant effort was made, in cooperation with SBRS and MCST, in characterizing and understanding MODIS PFM thermal infrared performance; crosstalk in the longwave infrared channels continues to get considerable attention.

Comparison of MODIS and VIIRS Snow Cover Products for the 2016 Hydrological Year

NASA Astrophysics Data System (ADS)

Klein, A. G.; Thapa, S.

2017-12-01

The VIIRS (Visible Infrared Imaging Radiometer Suite) instrument on board the Suomi-NPP satellite aims to provide long-term continuity of several environmental data series including snow cover initiated with MODIS. While it is speculated that MODIS and VIIRS snow cover products may differ because of their differing spatial resolutions and spectral coverage quantitative comparisons between their snow products are currently limited. Therefore this study intercompares MODIS and VIIRS snow products for the 2016 Hydrological Year over the Midwestern United States and southern Canada. Two hundred and forty-four swath snow products from MODIS/Aqua (MYD10L2) and the VIIRS EDR (VSCMO/binary) were intercompared using confusion matrices, comparison maps and false color imagery. Thresholding the MODIS NDSI Snow Cover product at a snow cover fraction of 30% generated binary snow maps most comparable to the NOAA VIIRS binary snow product. Overall agreement between MODIS and VIIRS was found to be approximately 98%. This exceeds the VIIRS accuracy requirements of 90% probability of correct typing. Agreement was highest during the winter but lower during late fall and spring. Comparability was lowest over forest. MODIS and VIIRS often mapped snow/no-snow transition zones as cloud. The assessment of total snow and cloud pixels and comparison snow maps of MODIS and VIIRS indicates that VIIRS is mapping more snow cover and less cloud cover compared to MODIS. This is evidenced by the average area of snow in MYD10L2 and VSCMO being 5.72% and 11.43%, no-snow 26.65% and 28.67%, and cloud 65.02% and 59.91%, respectively. Visual comparisons depict good qualitative agreement between snow cover area visible in MODIS and VIIRS false color imagery and mapped in their respective snow cover products. While VIIRS and MODIS have similar capacity to map snow cover, VIIRS has the potential to more accurately map snow cover area for the successive development of climate data records.

Cirrus Cloud Optical and Microphysical Property Retrievals from eMAS During SEAC4RS Using Bi-Spectral Reflectance Measurements Within the 1.88 micron Water Vapor Absorption Band

NASA Technical Reports Server (NTRS)

Meyer, K.; Platnick, S.; Arnold, G. T.; Holz, R. E.; Veglio, P.; Yorks, J.; Wang, C.

2016-01-01

Previous bi-spectral imager retrievals of cloud optical thickness (COT) and effective particle radius (CER) based on the Nakajima and King (1990) approach, such as those of the operational MODIS cloud optical property retrieval product (MOD06), have typically paired a non-absorbing visible or near-infrared wavelength, sensitive to COT, with an absorbing shortwave or midwave infrared wavelength sensitive to CER. However, in practice it is only necessary to select two spectral channels that exhibit a strong contrast in cloud particle absorption. Here it is shown, using eMAS observations obtained during NASAs SEAC4RS field campaign, that selecting two absorbing wavelength channels within the broader 1.88 micron water vapor absorption band, namely the 1.83 and 1.93 micron channels that have sufficient differences in ice crystal single scattering albedo, can yield COT and CER retrievals for thin to moderately thick single-layer cirrus that are reasonably consistent with other solar and IR imager-based and lidar-based retrievals. A distinct advantage of this channel selection for cirrus cloud retrievals is that the below cloud water vapor absorption minimizes the surface contribution to measured cloudy TOA reflectance, in particular compared to the solar window channels used in heritage retrievals such as MOD06. This reduces retrieval uncertainty resulting from errors in the surface reflectance assumption, as well as reduces the frequency of retrieval failures for thin cirrus clouds.

Cirrus cloud optical and microphysical property retrievals from eMAS during SEAC4RS using bi-spectral reflectance measurements within the 1.88 µm water vapor absorption band

NASA Astrophysics Data System (ADS)

Meyer, Kerry; Platnick, Steven; Arnold, G. Thomas; Holz, Robert E.; Veglio, Paolo; Yorks, John; Wang, Chenxi

2016-04-01

Previous bi-spectral imager retrievals of cloud optical thickness (COT) and effective particle radius (CER) based on the Nakajima and King (1990) approach, such as those of the operational MODIS cloud optical property retrieval product (MOD06), have typically paired a non-absorbing visible or near-infrared wavelength, sensitive to COT, with an absorbing shortwave or mid-wave infrared wavelength sensitive to CER. However, in practice it is only necessary to select two spectral channels that exhibit a strong contrast in cloud particle absorption. Here it is shown, using eMAS observations obtained during NASA's SEAC4RS field campaign, that selecting two absorbing wavelength channels within the broader 1.88 µm water vapor absorption band, namely the 1.83 and 1.93 µm channels that have sufficient differences in ice crystal single scattering albedo, can yield COT and CER retrievals for thin to moderately thick single-layer cirrus that are reasonably consistent with other solar and IR imager-based and lidar-based retrievals. A distinct advantage of this channel selection for cirrus cloud retrievals is that the below-cloud water vapor absorption minimizes the surface contribution to measured cloudy top-of-atmosphere reflectance, in particular compared to the solar window channels used in heritage retrievals such as MOD06. This reduces retrieval uncertainty resulting from errors in the surface reflectance assumption and reduces the frequency of retrieval failures for thin cirrus clouds.

Indices for estimating fractional snow cover in the western Tibetan Plateau

NASA Astrophysics Data System (ADS)

Shreve, Cheney M.; Okin, Gregory S.; Painter, Thomas H.

Snow cover in the Tibetan Plateau is highly variable in space and time and plays a key role in ecological processes of this cold-desert ecosystem. Resolution of passive microwave data is too low for regional-scale estimates of snow cover on the Tibetan Plateau, requiring an alternate data source. Optically derived snow indices allow for more accurate quantification of snow cover using higher-resolution datasets subject to the constraint of cloud cover. This paper introduces a new optical snow index and assesses four optically derived MODIS snow indices using Landsat-based validation scenes: MODIS Snow-Covered Area and Grain Size (MODSCAG), Relative Multiple Endmember Spectral Mixture Analysis (RMESMA), Relative Spectral Mixture Analysis (RSMA) and the normalized-difference snow index (NDSI). Pearson correlation coefficients were positively correlated with the validation datasets for all four optical snow indices, suggesting each provides a good measure of total snow extent. At the 95% confidence level, linear least-squares regression showed that MODSCAG and RMESMA had accuracy comparable to validation scenes. Fusion of optical snow indices with passive microwave products, which provide snow depth and snow water equivalent, has the potential to contribute to hydrologic and energy-balance modeling in the Tibetan Plateau.

Changes in cloud properties over East Asia deduced from the CLARA-A2 satellite data record

NASA Astrophysics Data System (ADS)

Benas, Nikos; Fokke Meirink, Jan; Hollmann, Rainer; Karlsson, Karl-Göran; Stengel, Martin

2017-04-01

Studies on cloud properties and processes, and their role in the Earth's changing climate, have advanced during the past decades. A significant part of this advance was enabled by satellite measurements, which offer global and continuous monitoring. Lately, a new satellite-based cloud data record was released: the CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data - second edition (CLARA-A2) includes high resolution cloud macro- and micro-physical properties derived from the AVHRR instruments on board NOAA and MetOp polar orbiters. Based on this data record, an analysis of cloud property changes over East Asia during the 12-year period 2004-2015 was performed. Significant changes were found in both optical and geometric cloud properties, including increases in cloud liquid water path and top height. The Cloud Droplet Number Concentration (CDNC) was specifically studied in order to gain further insight into possible connections between aerosol and cloud processes. To this end, aerosol and cloud observations from MODIS, covering the same area and period, were included in the analysis.

Transitions of cloud-topped marine boundary layers characterized by AIRS, MODIS, and a large eddy simulation model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yue, Qing; Kahn, Brian; Xiao, Heng

2013-08-16

Cloud top entrainment instability (CTEI) is a hypothesized positive feedback between entrainment mixing and evaporative cooling near the cloud top. Previous theoretical and numerical modeling studies have shown that the persistence or breakup of marine boundary layer (MBL) clouds may be sensitive to the CTEI parameter. Collocated thermodynamic profile and cloud observations obtained from the Atmospheric Infrared Sounder (AIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) instruments are used to quantify the relationship between the CTEI parameter and the cloud-topped MBL transition from stratocumulus to trade cumulus in the northeastern Pacific Ocean. Results derived from AIRS and MODIS are compared withmore » numerical results from the UCLA large eddy simulation (LES) model for both well-mixed and decoupled MBLs. The satellite and model results both demonstrate a clear correlation between the CTEI parameter and MBL cloud fraction. Despite fundamental differences between LES steady state results and the instantaneous snapshot type of observations from satellites, significant correlations for both the instantaneous pixel-scale observations and the long-term averaged spatial patterns between the CTEI parameter and MBL cloud fraction are found from the satellite observations and are consistent with LES results. This suggests the potential of using AIRS and MODIS to quantify global and temporal characteristics of the cloud-topped MBL transition.« less

Impact of aerosol microphysics on cloud optical properties and implications to atmospheric oxidation capacity

NASA Astrophysics Data System (ADS)

Luo, G.; Yu, F.

2016-12-01

GEOS-Chem, presently used by many research groups, is a state-of-the-art global 3-D model of atmospheric composition driven by assimilated meteorology from the Goddard Earth Observing System. Our comparisons of GEOS-5 cloud properties, used in photolysis rate calculation, with MODIS retrievals show that GEOS-5 underestimates cloud optical depth (COD) by a factor of more than 2 over most regions. Our further analysis indicates that the COD underestimation in the released GEOS-5 meteorology products is likely to be associated with the fact that the GEOS-5 doesn't take into account the impact of aerosol on cloud microphysics and optical properties. A new COD parameterization (called NewC thereafter), which re-calculates COD from GEOS-5 water content and GEOS-Chem simulated size-resolved particle properties, cloud condensation nuclei abundance, and cloud droplet number concentration, has been developed and incorporated into GEOS-Chem. The NewC increases the GEOS-5 derived annual mean CODs averaged between 60ºS and 60ºN from 2.0 to 4.3, in much better agreement with corresponding MODIS value of 4.3. The enhanced COD based on NewC scheme reduces global average boundary layer OH concentration by 9.8%. Zonal averaged OH is increased 3-7% above clouds due to backscattering and decreased 10-15% below clouds due to the attenuation of solar radiation. The global mean OH concentration simulated by GEOS-Chem driven by GEOS-5 COD and NewC COD are respectively12.9 × 105molec cm-3 and 12.2 × 105molec cm-3, with the latter closer to the ACCMIP multi-model estimation (11.7±1 105molec cm-3). Surface OH concentrations over major anthropogenic regions such as Eastern US, Europe, and East Asia decrease by up to -18.6%, -14.4%, and -19.9%, respectively. The relative change of surface OH concentration appears to be the largest over the Amazon rainforest, reaching up to -30%. After switching from old COD to NewC COD, GEOS-Chem simulated column HCHO and surface isoprene over Amazon region are enhanced 12% and 20%, respectively. At the Eastern United States, column HCHO and surface isoprene are enhanced 5% and 15%, respectively. Seasonal variation and regional characteristics of the impact of aerosol microphysics on cloud properties and implications to atmospheric oxidation capacity and tropospheric compositions will be discussed.

Clear-sky remote sensing in the vicinity of clouds: what we learned from MODIS and CALIPSO

NASA Astrophysics Data System (ADS)

Marshak, Alexander; Varnai, Tamas; Wen, Guoyong; Cahalan, Robert

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.

The MODIS Aerosol Algorithm: Critical Evaluation and Plans for Collection 6

NASA Technical Reports Server (NTRS)

Remer, Lorraine

2010-01-01

For ten years the MODIS aerosol algorithm has been applied to measured MODIS radiances to produce a continuous set of aerosol products, over land and ocean. The MODIS aerosol products are widely used by the scientific and applied science communities for variety of purposes that span operational air quality forecasting in estimates o[ clear-sky direct radiative effects over ocean and aerosol-cloud interactions. The products undergo continual evaluation, including self-consistency checks and comparisons with highly accurate ground-based instruments. The result of these evaluation exercises is a quantitative understanding of the strengths and weaknesses of the retrieval, where and when the products are accurate and the situations where and when accuracy degrades. We intend 10 present results of the most recent critical evaluations including the first comparison of the over ocean products against the shipboard aerosol optical depth measurements of the Marine Aerosol Network (MAN), the demonstration of the lack of sensitivity to size parameter in the over land products and identification of residual problems and regional issues. While the current data set is undergoing evaluation, we are preparing for the next data processing, labeled Collection 6. Collection 6 will include transparent Quality Flags, a 3 km aerosol product and the 500m resolution cloud mask used within the aerosol n:bicvu|. These new products and adjustments to algorithm assumptions should provide users with more options and greater control, as they adapt the product for their own purposes.

Estimation de la superficie du couvert nival a partir d'une combinaison des donnees de teledetection MODIS et AMSR-E dans un contexte de prevision des crues printanieres au Quebec

NASA Astrophysics Data System (ADS)

Bergeron, Jean

Snow cover estimation is a principal source of error for spring streamflow simulations in Québec, Canada. Optical and near infrared remote sensing can improve snow cover area (SCA) estimation due to high spatial resolution but is limited by cloud cover and incoming solar radiation. Passive microwave remote sensing is complementary by its near-transparence to cloud cover and independence to incoming solar radiation, but is limited by its coarse spatial resolution. The study aims to create an improved SCA product from blended passive microwave (AMSR-E daily L3 Brightness Temperature) and optical (MODIS Terra and Aqua daily snow cover L3) remote sensing data in order to improve estimation of river streamflow caused by snowmelt with Québec's operational MOHYSE hydrological model through direct-insertion of the blended SCA product in a coupled snowmelt module (SPH-AV). SCA estimated from AMSR-E data is first compared with SCA estimated with MODIS, as well as with in situ snow depth measurements. Results show good agreement (+95%) between AMSR-E-derived and MODIS-derived SCA products in spring but comparisons with Environment Canada ground stations and SCA derived from Advanced Very High Resolution Radiometer (AVHRR) data show lesser agreements (83 % and 74% respectively). Results also show that AMSR-E generally underestimates SCA. Assimilating the blended snow product in SPH-AV coupled with MOHYSE yields significant improvement of simulated streamflow for the aux Écorces et au Saumon rivers overall when compared with simulations with no update during thaw events, These improvements are similar to results driven by biweekly ground data. Assimilation of remotely-sensed passive microwave data was also found to have little positive impact on springflood forecast due to the difficulty in differentiating melting snow from snow-free surfaces. Considering the direct-insertion and Newtonian nudging assimilation methods, the study also shows the latter method to be superior to the former, notably when assimilating noisy data. Keywords: Snow cover, spring streamflow, MODIS, AMSR-E, hydrological model.

Chlorophyll-a Estimation Around the Antarctica Peninsula Using Satellite Algorithms: Hints from Field Water Leaving Reflectance

PubMed Central

Zeng, Chen; Xu, Huiping; Fischer, Andrew M.

2016-01-01

Ocean color remote sensing significantly contributes to our understanding of phytoplankton distribution and abundance and primary productivity in the Southern Ocean (SO). However, the current SO in situ optical database is still insufficient and unevenly distributed. This limits the ability to produce robust and accurate measurements of satellite-based chlorophyll. Based on data collected on cruises around the Antarctica Peninsula (AP) on January 2014 and 2016, this research intends to enhance our knowledge of SO water and atmospheric optical characteristics and address satellite algorithm deficiency of ocean color products. We collected high resolution in situ water leaving reflectance (±1 nm band resolution), simultaneous in situ chlorophyll-a concentrations and satellite (MODIS and VIIRS) water leaving reflectance. Field samples show that clouds have a great impact on the visible green bands and are difficult to detect because NASA protocols apply the NIR band as a cloud contamination threshold. When compared to global case I water, water around the AP has lower water leaving reflectance and a narrower blue-green band ratio, which explains chlorophyll-a underestimation in high chlorophyll-a regions and overestimation in low chlorophyll-a regions. VIIRS shows higher spatial coverage and detection accuracy than MODIS. After coefficient improvement, VIIRS is able to predict chlorophyll a with 53% accuracy. PMID:27941596

Chlorophyll-a Estimation Around the Antarctica Peninsula Using Satellite Algorithms: Hints from Field Water Leaving Reflectance.

PubMed

Zeng, Chen; Xu, Huiping; Fischer, Andrew M

2016-12-07

Ocean color remote sensing significantly contributes to our understanding of phytoplankton distribution and abundance and primary productivity in the Southern Ocean (SO). However, the current SO in situ optical database is still insufficient and unevenly distributed. This limits the ability to produce robust and accurate measurements of satellite-based chlorophyll. Based on data collected on cruises around the Antarctica Peninsula (AP) on January 2014 and 2016, this research intends to enhance our knowledge of SO water and atmospheric optical characteristics and address satellite algorithm deficiency of ocean color products. We collected high resolution in situ water leaving reflectance (±1 nm band resolution), simultaneous in situ chlorophyll-a concentrations and satellite (MODIS and VIIRS) water leaving reflectance. Field samples show that clouds have a great impact on the visible green bands and are difficult to detect because NASA protocols apply the NIR band as a cloud contamination threshold. When compared to global case I water, water around the AP has lower water leaving reflectance and a narrower blue-green band ratio, which explains chlorophyll-a underestimation in high chlorophyll-a regions and overestimation in low chlorophyll-a regions. VIIRS shows higher spatial coverage and detection accuracy than MODIS. After coefficient improvement, VIIRS is able to predict chlorophyll a with 53% accuracy.

Comparison between volcanic ash satellite retrievals and FALL3D transport model

NASA Astrophysics Data System (ADS)

Corradini, Stefano; Merucci, Luca; Folch, Arnau

2010-05-01

Volcanic eruptions represent one of the most important sources of natural pollution because of the large emission of gas and solid particles into the atmosphere. Volcanic clouds can contain different gas species (mainly H2O, CO2, SO2 and HCl) and a mix of silicate-bearing ash particles in the size range from 0.1 μm to few mm. Determining the properties, movement and extent of volcanic ash clouds is an important scientific, economic, and public safety issue because of the harmful effects on environment, public health and aviation. In particular, real-time tracking and forecasting of volcanic clouds is key for aviation safety. Several encounters of en-route aircrafts with volcanic ash clouds have demonstrated the harming effects of fine ash particles on modern aircrafts. Alongside these considerations, the economical consequences caused by disruption of airports must be also taken into account. Both security and economical issues require robust and affordable ash cloud detection and trajectory forecasting, ideally combining remote sensing and modeling. We perform a quantitative comparison between Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of volcanic ash cloud mass and Aerosol Optical Depth (AOD) with the FALL3D ash dispersal model. MODIS, aboard the NASA-Terra and NASA-Aqua polar satellites, is a multispectral instrument with 36 spectral bands from Visible (VIS) to Thermal InfraRed (TIR) and spatial resolution varying between 250 and 1000 m at nadir. The MODIS channels centered around 11 and 12 mm have been used for the ash retrievals through the Brightness Temperature Difference algorithm and MODTRAN simulations. FALL3D is a 3-D time-dependent Eulerian model for the transport and deposition of volcanic particles that outputs, among other variables, cloud column mass and AOD. We consider the Mt. Etna volcano 2002 eruptive event as a test case. Results show a good agreement between the mean AOT retrieved and the spatial ash dispersion in the different images, while the modeled FALL3D total mass retrieved results significantly overestimated.

Investigation of cloud properties and atmospheric stability with MODIS

NASA Technical Reports Server (NTRS)

Menzel, Paul

1995-01-01

In the past six months several milestones were accomplished. The MODIS Airborne Simulator (MAS) was flown in a 50 channel configuration for the first time in January 1995 and the data were calibrated and validated; in the same field campaign the approach for validating MODIS radiances using the MAS and High resolution Interferometer Sounder (HIS) instruments was successfully tested on GOES-8. Cloud masks for two scenes (one winter and the other summer) of AVHRR local area coverage from the Gulf of Mexico to Canada were processed and forwarded to the SDST for MODIS Science Team investigation; a variety of surface and cloud scenes were evident. Beta software preparations continued with incorporation of the EOS SDP Toolkit. SCAR-C data was processed and presented at the biomass burning conference. Preparations for SCAR-B accelerated with generation of a home page for access to real time satellite data related to biomass burning; this will be available to the scientists in Brazil via internet on the World Wide Web. The CO2 cloud algorithm was compared to other algorithms that differ in their construction of clear radiance fields. The HIRS global cloud climatology was completed for six years. The MODIS science team meeting was attended by five of the UW scientists.

Diurnal spatial distributions of aerosol optical and cloud micro-macrophysics properties in Africa based on MODIS observations

NASA Astrophysics Data System (ADS)

Ntwali, Didier; Chen, Hongbin

2018-06-01

The diurnal spatial distribution of both natural and anthropogenic aerosols, as well as liquid and ice cloud micro-macrophysics have been evaluated over Africa using Terra and Aqua MODIS collection 6 products. The variability of aerosol optical depth (AOD), Ångström exponent (AE), liquid and ice cloud microphysics (Liquid cloud effective radius LCER, Ice cloud effective radius ICER) and cloud macrophysics (Liquid cloud optical thickness LCOT, Liquid cloud water path LCWP, Ice cloud optical thickness ICOT, Ice cloud water path ICWP) parameters were investigated from the morning to afternoon over Africa from 2010 to 2014. In both the morning (Terra) and afternoon (Aqua) heavy pollution (AOD ≥ 0.6) occurs in the coastal and central areas (between 120 N-170 N and 100 E-150 E) of West of Africa (WA), Central of Africa (CA) (0.50 S-70S and 100 E-250 E),. Moderate pollution (0.3 < AOD < 0.6) often occurs in West and North of Africa (between 50 N-270 N and 160 W-50E), and clean environmental (AOD < 0.3) conditions are common in South of Africa (SA), East of Africa (EA) and some regions in North of Africa (NA). The West-North of Africa (WNA) and Central-South of Africa (CSA) regions are dominated by dust (AE < 0.7) and biomass burning (AE > 1.2) aerosols. The mixture of dust and biomass burning aerosols (0.7 < AE < 1.2) are found at the coastal areas in West of Africa (CoWA) and Central of Africa (CA) (50 N-80N and 100 E-340 E), particularly in the morning and afternoon respectively. The LCER often decrease from the morning to the afternoon in all seasons, but an increase occur from the morning to the afternoon in CSA (50 S-220 S) in DJF, both CA (20 S-50N) and CoWA in JJA and SON. The ICER increase from the morning to afternoon in all seasons over Africa and decreases in South of Africa (50 S-200 S) in DJF. The LCOT increases from the morning to afternoon in NA and SA while a decrease occur in CA in all seasons. The LCWP increase in many regions of Africa in all seasons while a decrease occurs in CoWA during JJA. The ICOT and ICWP show a remarkable increase from the morning to afternoon in regions dominated by biomass burning (CSA) compared to regions dominated by dust (WNA) aerosols in DJF, MAM and SON. Dust aerosols are mainly distributed in WNA by northerly and westerly winds in both January and April, southerly and southwesterly winds in July, and southerly and southwesterly winds in October, while biomass burning aerosols are mainly distributed in CSA by the northerly and northeasterly winds in January, easterly winds in April, July and October. The diurnal variability of cloud parameters is associated with both convective processes and cloud types. The knowledge of interactions between natural and anthropogenic aerosols with liquid and ice cloud microphysics parameters could contribute to improve aerosol and cloud remote sensing retrieval.

Neural Network (NN) retrievals of Stratocumulus cloud properties using multi-angle polarimetric observations during ORACLES

NASA Astrophysics Data System (ADS)

Segal-Rosenhaimer, M.; Knobelspiesse, K. D.; Redemann, J.; Cairns, B.; Alexandrov, M. D.

2016-12-01

The ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign is taking place in the South-East Atlantic during the Austral Spring for three consecutive years from 2016-2018. The study area encompasses one of the Earth's three semi-permanent subtropical Stratocumulus (Sc) cloud decks, and experiences very large aerosol optical depths, mainly biomass burning, originating from Africa. Over time, cloud optical depth (COD), lifetime and cloud microphysics (number concentration, effective radii Reff and precipitation) are expected to be influenced by indirect aerosol effects. These changes play a key role in the energetic balance of the region, and are part of the core investigation objectives of the ORACLES campaign, which acquires measurements of clean and polluted scenes of above cloud aerosols (ACA). Simultaneous retrievals of aerosol and cloud optical properties are being developed (e.g. MODIS, OMI), but still challenging, especially for passive, single viewing angle instruments. By comparison, multiangle polarimetric instruments like RSP (Research Scanning Polarimeter) show promise for detection and quantification of ACA, however, there are no operational retrieval algorithms available yet. Here we describe a new algorithm to retrieve cloud and aerosol optical properties from observations by RSP flown on the ER-2 and P-3 during the 2016 ORACLES campaign. The algorithm is based on training a NN, and is intended to retrieve aerosol and cloud properties simultaneously. However, the first step was to establish the retrieval scheme for low level Sc cloud optical properties. The NN training was based on simulated RSP total and polarized radiances for a range of COD, Reff, and effective variances, spanning 7 wavelength bands and 152 viewing zenith angles. Random and correlated noise were added to the simulations to achieve a more realistic representation of the signals. Before introducing the input variables to the network, the signals are projected on a principle component plane that retains the maximal signal information but minimizes the noise contribution. We will discuss parameter choices for the network and present preliminary results of cloud retrievals from ORACLES, compared with standard RSP low-level cloud retrieval method that has been validated against in situ observations.

Estimating trace gas and aerosol emissions over South America: Relationship between fire radiative energy released and aerosol optical depth observations

NASA Astrophysics Data System (ADS)

Pereira, Gabriel; Freitas, Saulo R.; Moraes, Elisabete Caria; Ferreira, Nelson Jesus; Shimabukuro, Yosio Edemir; Rao, Vadlamudi Brahmananda; Longo, Karla M.

2009-12-01

Contemporary human activities such as tropical deforestation, land clearing for agriculture, pest control and grassland management lead to biomass burning, which in turn leads to land-cover changes. However, biomass burning emissions are not correctly measured and the methods to assess these emissions form a part of current research area. The traditional methods for estimating aerosols and trace gases released into the atmosphere generally use emission factors associated with fuel loading and moisture characteristics and other parameters that are hard to estimate in near real-time applications. In this paper, fire radiative power (FRP) products were extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) and from the Geostationary Operational Environmental Satellites (GOES) fire products and new South America generic biomes FRE-based smoke aerosol emission coefficients were derived and applied in 2002 South America fire season. The inventory estimated by MODIS and GOES FRP measurements were included in Coupled Aerosol-Tracer Transport model coupled to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) and evaluated with ground truth collected in Large Scale Biosphere-Atmosphere Smoke, Aerosols, Clouds, rainfall, and Climate (SMOCC) and Radiation, Cloud, and Climate Interactions (RaCCI). Although the linear regression showed that GOES FRP overestimates MODIS FRP observations, the use of a common external parameter such as MODIS aerosol optical depth product could minimize the difference between sensors. The relationship between the PM 2.5μm (Particulate Matter with diameter less than 2.5 μm) and CO (Carbon Monoxide) model shows a good agreement with SMOCC/RaCCI data in the general pattern of temporal evolution. The results showed high correlations, with values between 0.80 and 0.95 (significant at 0.5 level by student t test), for the CATT-BRAMS simulations with PM 2.5μm and CO.

The Q Continuum: Encounter with the Cloud Mask

NASA Astrophysics Data System (ADS)

Ackerman, S. A.; Frey, R.; Holz, R.; Philips, C.; Dutcher, S.

2017-12-01

We are developing a common cloud mask for MODIS and VIIRS observations, referred to as the MODIS VIIRS Continuity Mask (MVCM). Our focus is on extending the MODIS-heritage cloud detection approach in order to generate appropriate climate data records for clouds and climate studies. The MVCM is based on heritage from the MODIS cloud mask (MOD35 and MYD35) and employs a series of tests on MODIS reflectances and brightness temperatures. Cloud detection is based on contrasts (i.e., cloud versus background surface) at pixel resolution. The MVCM follows the same approach. These cloud masks use multiple cloud detection tests to indicate the confidence level that the observation is of a clear-sky scene. The outcome of a test ranges from 0 (cloudy) to 1 (clear-sky scene). Because of overlap in the sensitivities of the various spectral tests to the type of cloud, each test is considered in one of several groups. The final cloud mask is determined from the product of the minimum confidence of each group and is referred to as the Q value as defined in Ackerman et al (1998). In MOD35 and MYD35 processing, the Q value is not output, rather predetermined Q values determine the result: If Q ≥ .99 the scene is clear; .95 ≤ Q < .99 the pixel is probably a clear scene, .66 ≤ Q < .95 is probably cloudy and Q < .66 is cloudy. Thus representing Q discretely and not as a continuum. For the MVCM, the numerical value of the Q is output along with the classification of clear, probably clear, probably cloudy, and cloudy. Through comparisons with collocated CALIOP and MODIS observations, we will assess the categorization of the Q values as a function of scene type ). While validation studies have indicated the utility and statistical correctness of the cloud mask approach, the algorithm does not possess immeasurable power and perfection. This comparison will assess the time and space dependence of Q and assure that the laws of physics are followed, at least according to normal human notions. Using CALIOP as representing truth, a receiver operating characteristic curve (ROC) will be analyzed to determine the optimum Q for various scenes and seasons, thus providing a continuum of discriminating thresholds.

Apperception of Clouds in AIRS Data

NASA Technical Reports Server (NTRS)

Huang, Hung-Lung; Smith, William L.

2005-01-01

Our capacity to simulate the radiative characteristics of the Earth system has advanced greatly over the past decade. However, new space based measurements show that idealized simulations might not adequately represent the complexity of nature. For example, AIRS simulated multi-layer cloud clearing research provides an excellent groundwork for early Atmospheric Infra-Red Sounder (AIRS) operational cloud clearing and atmospheric profile retrieval. However, it doesn't reflect the complicated reality of clouds over land and coastal areas. Thus far, operational AIRS/AMSU (Advanced Microwave Sounding Unit) cloud clearing is not only of low yield but also of unsatisfying quality. This is not an argument for avoiding this challenging task, rather a powerful argument for exploring other synergistic approaches, and for adapting these strategies toward improving both indirect and direct use of cloudy infrared sounding data. Ample evidence is shown in this paper that the indirect use of cloudy sounding data by way of cloud clearing is sub-optimal for data assimilation. Improvements are needed in quality control, retrieval yield, and overall cloud clearing retrieval performance. For example, cloud clearing over land, especially over the desert surface, has led to much degraded retrieval quality and often a very low yield of quality controlled cloud cleared radiances. If these indirect cloud cleared radiances are instead to be directly assimilated into NWP models, great caution must be used. Our limited and preliminary cloud clearing results from AIRS/AMSU (with the use of MODIS data) and an AIRS/MODIS synergistic approach have, however, shown that higher spatial resolution multispectral imagery data can provide much needed quality control of the AIRS/AMSU cloud clearing retrieval. When AIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) are used synergistically, a higher spatial resolution over difficult terrain (especially desert areas) can be achieved and with a much improved accuracy. Preliminary statistical analyses of cloud cleared radiances derived from (1) operational AIRS/AMSU, (2) operational AIRS/AMSU plus the use of MODIS data as quality control, and (3) AIRS/MODIS synergistic single channel and two field of views cloud clearing are Our capacity to simulate the radiative characteristics of the Earth system has

Diurnal, Seasonal, and Interannual Variations of Cloud Properties Derived for CERES From Imager Data

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Young, David F.; Sun-Mack, Sunny; Trepte, Qing Z.; Chen, Yan; Brown, Richard R.; Gibson, Sharon; Heck, Patrick W.

2004-01-01

Simultaneous measurement of the radiation and cloud fields on a global basis is a key component in the effort to understand and model the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project, begun in 1998, is meeting this need. Broadband shortwave (SW) and longwave radiance measurements taken by the CERES scanners at resolutions between 10 and 20 km on the Tropical Rainfall Measuring Mission (TRMM), Terra, and Aqua satellites are matched to simultaneous retrievals of cloud height, phase, particle size, water path, and optical depth OD from the TRMM Visible Infrared Scanner (VIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Besides aiding the interpretation of the broadband radiances, the CERES cloud properties are valuable for understanding cloud variations at a variety of scales. In this paper, the resulting CERES cloud data taken to date are averaged at several temporal scales to examine the temporal and spatial variability of the cloud properties on a global scale at a 1 resolution.

Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

NASA Astrophysics Data System (ADS)

de Leeuw, Gerrit; Sogacheva, Larisa; Rodriguez, Edith; Kourtidis, Konstantinos; Georgoulias, Aristeidis K.; Alexandri, Georgia; Amiridis, Vassilis; Proestakis, Emmanouil; Marinou, Eleni; Xue, Yong; van der A, Ronald

2018-02-01

The retrieval of aerosol properties from satellite observations provides their spatial distribution over a wide area in cloud-free conditions. As such, they complement ground-based measurements by providing information over sparsely instrumented areas, albeit that significant differences may exist in both the type of information obtained and the temporal information from satellite and ground-based observations. In this paper, information from different types of satellite-based instruments is used to provide a 3-D climatology of aerosol properties over mainland China, i.e., vertical profiles of extinction coefficients from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a lidar flying aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and the column-integrated extinction (aerosol optical depth - AOD) available from three radiometers: the European Space Agency (ESA)'s Along-Track Scanning Radiometer version 2 (ATSR-2), Advanced Along-Track Scanning Radiometer (AATSR) (together referred to as ATSR) and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite, together spanning the period 1995-2015. AOD data are retrieved from ATSR using the ATSR dual view (ADV) v2.31 algorithm, while for MODIS Collection 6 (C6) the AOD data set is used that was obtained from merging the AODs obtained from the dark target (DT) and deep blue (DB) algorithms, further referred to as the DTDB merged AOD product. These data sets are validated and differences are compared using Aerosol Robotic Network (AERONET) version 2 L2.0 AOD data as reference. The results show that, over China, ATSR slightly underestimates the AOD and MODIS slightly overestimates the AOD. Consequently, ATSR AOD is overall lower than that from MODIS, and the difference increases with increasing AOD. The comparison also shows that neither of the ATSR and MODIS AOD data sets is better than the other one everywhere. However, ATSR ADV has limitations over bright surfaces which the MODIS DB was designed for. To allow for comparison of MODIS C6 results with previous analyses where MODIS Collection 5.1 (C5.1) data were used, also the difference between the C6 and C5.1 merged DTDB data sets from MODIS/Terra over China is briefly discussed. The AOD data sets show strong seasonal differences and the seasonal features vary with latitude and longitude across China. Two-decadal AOD time series, averaged over all of mainland China, are presented and briefly discussed. Using the 17 years of ATSR data as the basis and MODIS/Terra to follow the temporal evolution in recent years when the environmental satellite Envisat was lost requires a comparison of the data sets for the overlapping period to show their complementarity. ATSR precedes the MODIS time series between 1995 and 2000 and shows a distinct increase in the AOD over this period. The two data series show similar variations during the overlapping period between 2000 and 2011, with minima and maxima in the same years. MODIS extends this time series beyond the end of the Envisat period in 2012, showing decreasing AOD.

The Collection 6 'dark-target' MODIS Aerosol Products

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Mattoo, Shana; Munchak, Leigh A.; Kleidman, Richard G.; Patadia, Falguni; Gupta, Pawan; Remer, Lorraine

2013-01-01

Aerosol retrieval algorithms are applied to Moderate resolution Imaging Spectroradiometer (MODIS) sensors on both Terra and Aqua, creating two streams of decade-plus aerosol information. Products of aerosol optical depth (AOD) and aerosol size are used for many applications, but the primary concern is that these global products are comprehensive and consistent enough for use in climate studies. One of our major customers is the international modeling comparison study known as AEROCOM, which relies on the MODIS data as a benchmark. In order to keep up with the needs of AEROCOM and other MODIS data users, while utilizing new science and tools, we have improved the algorithms and products. The code, and the associated products, will be known as Collection 6 (C6). While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. In its entirety, the C6 algorithm is comprised of three sub-algorithms for retrieving aerosol properties over different surfaces: These include the dark-target DT algorithms to retrieve over (1) ocean and (2) vegetated-dark-soiled land, plus the (3) Deep Blue (DB) algorithm, originally developed to retrieve over desert-arid land. Focusing on the two DT algorithms, we have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to 84) to increase pole-ward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such as topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence in the retrieval, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time as we have introduced algorithm changes, we have also accounted for upstream changes including: new instrument calibration, revised land-sea masking, and changed cloud masking. Upstream changes also impact the coverage and global statistics of the retrieved AOD. Although our responsibility is to the DT code and products, we have also added a product that merges DT and DB product over semi-arid land surfaces to provide a more gap-free dataset, primarily for visualization purposes. Preliminary validation shows that compared to surface-based sunphotometer data, the C6, Level 2 (along swath) DT-products compare at least as well as those from C5. C6 will include new diagnostic information about clouds in the aerosol field, including an aerosol cloud mask at 500 m resolution, and calculations of the distance to the nearest cloud from clear pixels. Finally, we have revised the strategy for aggregating and averaging the Level 2 (swath) data to become Level 3 (gridded) data. All together, the changes to the DT algorithms will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. Changes in calibration will have more impact to Terras time series, especially over land. This will result in a significant reduction in artificial differences in the Terra and Aqua datasets, and will stabilize the MODIS data as a target for AEROCOM studie

Cloud Photogrammetry from Space

NASA Astrophysics Data System (ADS)

Zaksek, K.; Gerst, A.; von der Lieth, J.; Ganci, G.; Hort, M.

2015-04-01

The most commonly used method for satellite cloud top height (CTH) compares brightness temperature of the cloud with the atmospheric temperature profile. Because of the uncertainties of this method, we propose a photogrammetric approach. As clouds can move with high velocities, even instruments with multiple cameras are not appropriate for accurate CTH estimation. Here we present two solutions. The first is based on the parallax between data retrieved from geostationary (SEVIRI, HRV band; 1000 m spatial resolution) and polar orbiting satellites (MODIS, band 1; 250 m spatial resolution). The procedure works well if the data from both satellites are retrieved nearly simultaneously. However, MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection in the atmosphere we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. CTH is then estimated by intersection of corresponding lines-of-view from MODIS and interpolated SEVIRI data. The second method is based on NASA program Crew Earth observations from the International Space Station (ISS). The ISS has a lower orbit than most operational satellites, resulting in a shorter minimal time between two images, which is needed to produce a suitable parallax. In addition, images made by the ISS crew are taken by a full frame sensor and not a push broom scanner that most operational satellites use. Such data make it possible to observe also short time evolution of clouds.

Photogrammetric retrieval of volcanic ash cloud top height from SEVIRI and MODIS

NASA Astrophysics Data System (ADS)

Zakšek, Klemen; Hort, Matthias; Zaletelj, Janez; Langmann, Bärbel

2013-04-01

Even if erupting in remote areas, volcanoes can have a significant impact on the modern society due to volcanic ash dispersion in the atmosphere. The ash does not affect merely air traffic - its transport in the atmosphere and its deposition on land and in the oceans may also significantly influence the climate through modifications of atmospheric CO2. The emphasis of this contribution is the retrieval of volcanic ash plume height (ACTH). ACTH is important information especially for air traffic but also to predict ash transport and to estimate the mass flux of the ejected material. ACTH is usually estimated from ground measurements, pilot reports, or satellite remote sensing. But ground based instruments are often not available at remote volcanoes and also the pilots reports are a matter of chance. Volcanic ash cloud top height (ACTH) can be monitored on the global level using satellite remote sensing. The most often used method compares brightness temperature of the cloud with the atmospheric temperature profile. Because of uncertainties of this method (unknown emissivity of the ash cloud, tropopause, etc.) we propose photogrammetric methods based on the parallax between data retrieved from geostationary (SEVIRI) and polar orbiting satellites (MODIS). The parallax is estimated using automatic image matching in three level image pyramids. The procedure works well if the data from both satellites are retrieved nearly simultaneously. MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. ACTH is then estimated by intersection of corresponding lines-of-view from MODIS and interpolated SEVIRI data. The proposed method was tested using MODIS band 1 and SEVIRI HRV band for the case of the Eyjafjallajökull eruption in April 2010. The parallax between MODIS and SEVIRI data can reach over 30 km which implies ACTH of more than 12 km. The accuracy of ACTH was estimated to 0.6 km. The limitation of this procedure is that it has difficulties with automatic image matching if the ash cloud is not opaque.

Mesoscale modeling of smoke radiative feedback over the Sahel region

NASA Astrophysics Data System (ADS)

Yang, Z.; Wang, J.; Ichoku, C. M.; Ellison, L.; Zhang, F.; Yue, Y.

2013-12-01

This study employs satellite observations and a fully-coupled meteorology-chemistry-aerosol model, Weather Research and Forecasting model with Chemistry (WRF-Chem) to study the smoke radative feedback on surface energy budget, boundary layer processes, and atmospheric lapse rate in February 2008 over the Sahel region. The smoke emission inventories we use come from various sources, including but not limited to the Fire Locating and Modeling of Burning Emissions (FLAMBE) developed by NRL and the Fire Energetic and Emissions Research (FEER) developed by NASA GSFC. Model performance is evaluated using numerous satellite and ground-based datasets: MODIS true color images, ground-based Aerosol Optical Depth (AOD) measurements from AERONET, MODIS AOD retrievals, and Cloud-Aerosol Lidar data with Orthogonal Polarization (CALIOP) atmospheric backscattering and extinction products. Specification of smoke injection height of 650 m in WRF-Chem yields aerosol vertical profiles that are most consistent with CALIOP observations of aerosol layer height. Statistically, 5% of the CALIPSO valid measurements of aerosols in February 2008 show aerosol layers either above the clouds or between the clouds, reinforcing the importance of the aerosol vertical distribution for quantifying aerosol impact on climate in the Sahel region. The results further show that the smoke radiative feedbacks are sensitive to assumptions of black carbon and organic carbon ratio in the particle emission inventory. Also investigated is the smoke semi-direct effect as a function of cloud fraction.

Validation of AIRS/AMSU Cloud Retrievals Using MODIS Cloud Analyses

NASA Technical Reports Server (NTRS)

Molnar, Gyula I.; Susskind, Joel

2005-01-01

The AIRS/AMSU (flying on the EOS-AQUA satellite) sounding retrieval methodology allows for the retrieval of key atmospheric/surface parameters under partially cloudy conditions (Susskind et al.). In addition, cloud parameters are also derived from the AIRS/AMSU observations. Within each AIRS footprint, cloud parameters at up to 2 cloud layers are determined with differing cloud top pressures and effective (product of infrared emissivity at 11 microns and physical cloud fraction) cloud fractions. However, so far the AIRS cloud product has not been rigorously evaluated/validated. Fortunately, collocated/coincident radiances measured by MODIS/AQUA (at a much lower spectral resolution but roughly an order of-magnitude higher spatial resolution than that of AIRS) are used to determine analogous cloud products from MODIS. This allows us for a rather rare and interesting possibility: the intercomparisons and mutual validation of imager vs. sounder-based cloud products obtained from the same satellite positions. First, we present results of small-scale (granules) instantaneous intercomparisons. Next, we will evaluate differences of temporally averaged (monthly) means as well as the representation of inter-annual variability of cloud parameters as presented by the two cloud data sets. In particular, we present statistical differences in the retrieved parameters of cloud fraction and cloud top pressure. We will investigate what type of cloud systems are retrieved most consistently (if any) with both retrieval schemes, and attempt to assess reasons behind statistically significant differences.

A-Train Aerosol Observations Preliminary Comparisons with AeroCom Models and Pathways to Observationally Based All-Sky Estimates

NASA Technical Reports Server (NTRS)

Redemann, J.; Livingston, J.; Shinozuka, Y.; Kacenelenbogen, M.; Russell, P.; LeBlanc, S.; Vaughan, M.; Ferrare, R.; Hostetler, C.; Rogers, R.;

Cloud vortices

NASA Image and Video Library

2015-11-02

Cloud vortices off Heard Island, south Indian Ocean. The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA’s Aqua satellite captured this true-color image of sea ice off Heard Island on Nov 2, 2015 at 5:02 AM EST (09:20 UTC). Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team

Three-dimensional variational assimilation of MODIS aerosol optical depth: Implementation and application to a dust storm over East Asia

NASA Astrophysics Data System (ADS)

Liu, Zhiquan; Liu, Quanhua; Lin, Hui-Chuan; Schwartz, Craig S.; Lee, Yen-Huei; Wang, Tijian

2011-12-01

Assimilation of the Moderate Resolution Imaging Spectroradiometer (MODIS) total aerosol optical depth (AOD) retrieval products (at 550 nm wavelength) from both Terra and Aqua satellites have been developed within the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) three-dimensional variational (3DVAR) data assimilation system. This newly developed algorithm allows, in a one-step procedure, the analysis of 3-D mass concentration of 14 aerosol variables from the Goddard Chemistry Aerosol Radiation and Transport (GOCART) module. The Community Radiative Transfer Model (CRTM) was extended to calculate AOD using GOCART aerosol variables as input. Both the AOD forward model and corresponding Jacobian model were developed within the CRTM and used in the 3DVAR minimization algorithm to compute the AOD cost function and its gradient with respect to 3-D aerosol mass concentration. The impact of MODIS AOD data assimilation was demonstrated by application to a dust storm from 17 to 24 March 2010 over East Asia. The aerosol analyses initialized Weather Research and Forecasting/Chemistry (WRF/Chem) model forecasts. Results indicate that assimilating MODIS AOD substantially improves aerosol analyses and subsequent forecasts when compared to MODIS AOD, independent AOD observations from the Aerosol Robotic Network (AERONET) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, and surface PM10 (particulate matter with diameters less than 10 μm) observations. The newly developed AOD data assimilation system can serve as a tool to improve simulations of dust storms and general air quality analyses and forecasts.

Summertime Coincident Observations of Ice Water Path in the Visible/Near-IR, Radar, and Microwave Frequencies

NASA Technical Reports Server (NTRS)

Pittman, Jasna V.; Robertson, Franklin R.; Atkinson, Robert J.

2008-01-01

Accurate representation of the physical and radiative properties of clouds in climate models continues to be a challenge. At present, both remote sensing observations and modeling of microphysical properties of clouds rely heavily on parameterizations or assumptions on particle size distribution (PSD) and cloud phase. In this study, we compare Ice Water Path (IWP), an important physical and radiative property that provides the amount of ice present in a cloud column, using measurements obtained via three different retrieval strategies. The datasets we use in this study include Visible/Near-IR IWP from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument flying aboard the Aqua satellite, Radar-only IWP from the CloudSat instrument operating at 94 GHz, and NOAA/NESDIS operational IWP from the 89 and 157 GHz channels of the Microwave Humidity Sounder (MHS) instrument flying aboard the NOAA-18 satellite. In the Visible/Near-IR, IWP is derived from observations of optical thickness and effective radius. CloudSat IWP is determined from measurements of cloud backscatter and assumed PSD. MHS IWP retrievals depend on scattering measurements at two different, non-water absorbing channels, 89 and 157 GHz. In order to compare IWP obtained from these different techniques and collected at different vertical and horizontal resolutions, we examine summertime cases in the tropics (30S - 30N) when all 3 satellites are within 4 minutes of each other (approximately 1500 km). All measurements are then gridded to a common 15 km x 15 km box determined by MHS. In a grid box comparison, we find CloudSat to report the highest IWP followed by MODIS, followed by MHS. In a statistical comparison, probability density distributions show MHS with the highest frequencies at IWP of 100-1000 g/m(exp 2) and CloudSat with the longest tail reporting IWP of several thousands g/m(exp 2). For IWP greater than 30 g/m(exp 2), MODIS is consistently higher than CloudSat, and it is higher at the lower IWPs but lower at the higher IWPs that overlap with MHS. Some of these differences can be attributed to the limitations of the measuring techniques themselves, but some can result from the assumptions made in the algorithms that generate the IWP product. We investigate this issue by creating categories based on various conditions such as cloud type, precipitation presence, underlying liquid water content, and surface type (land vs. ocean) and by comparing the performance of the IWP products under each condition.

Retrieval of Areal-averaged Spectral Surface Albedo from Transmission Data Alone: Computationally Simple and Fast Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kassianov, Evgueni I.; Barnard, James C.; Flynn, Connor J.

We introduce and evaluate a simple retrieval of areal-averaged surface albedo using ground-based measurements of atmospheric transmission alone at five wavelengths (415, 500, 615, 673 and 870nm), under fully overcast conditions. Our retrieval is based on a one-line semi-analytical equation and widely accepted assumptions regarding the weak spectral dependence of cloud optical properties, such as cloud optical depth and asymmetry parameter, in the visible and near-infrared spectral range. To illustrate the performance of our retrieval, we use as input measurements of spectral atmospheric transmission from Multi-Filter Rotating Shadowband Radiometer (MFRSR). These MFRSR data are collected at two well-established continental sitesmore » in the United States supported by the U.S. Department of Energy’s (DOE’s) Atmospheric Radiation Measurement (ARM) Program and National Oceanic and Atmospheric Administration (NOAA). The areal-averaged albedos obtained from the MFRSR are compared with collocated and coincident Moderate Resolution Imaging Spectroradiometer (MODIS) white-sky albedo. In particular, these comparisons are made at four MFRSR wavelengths (500, 615, 673 and 870nm) and for four seasons (winter, spring, summer and fall) at the ARM site using multi-year (2008-2013) MFRSR and MODIS data. Good agreement, on average, for these wavelengths results in small values (≤0.01) of the corresponding root mean square errors (RMSEs) for these two sites. The obtained RMSEs are comparable with those obtained previously for the shortwave albedos (MODIS-derived versus tower-measured) for these sites during growing seasons. We also demonstrate good agreement between tower-based daily-averaged surface albedos measured for “nearby” overcast and non-overcast days. Thus, our retrieval originally developed for overcast conditions likely can be extended for non-overcast days by interpolating between overcast retrievals.« less

Minimum aerosol layer detection sensitivities and their subsequent impacts on aerosol optical thickness retrievals in CALIPSO level 2 data products

NASA Astrophysics Data System (ADS)

Toth, Travis D.; Campbell, James R.; Reid, Jeffrey S.; Tackett, Jason L.; Vaughan, Mark A.; Zhang, Jianglong; Marquis, Jared W.

2018-01-01

Due to instrument sensitivities and algorithm detection limits, level 2 (L2) Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) 532 nm aerosol extinction profile retrievals are often populated with retrieval fill values (RFVs), which indicate the absence of detectable levels of aerosol within the profile. In this study, using 4 years (2007-2008 and 2010-2011) of CALIOP version 3 L2 aerosol data, the occurrence frequency of daytime CALIOP profiles containing all RFVs (all-RFV profiles) is studied. In the CALIOP data products, the aerosol optical thickness (AOT) of any all-RFV profile is reported as being zero, which may introduce a bias in CALIOP-based AOT climatologies. For this study, we derive revised estimates of AOT for all-RFV profiles using collocated Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target (DT) and, where available, AErosol RObotic NEtwork (AERONET) data. Globally, all-RFV profiles comprise roughly 71 % of all daytime CALIOP L2 aerosol profiles (i.e., including completely attenuated profiles), accounting for nearly half (45 %) of all daytime cloud-free L2 aerosol profiles. The mean collocated MODIS DT (AERONET) 550 nm AOT is found to be near 0.06 (0.08) for CALIOP all-RFV profiles. We further estimate a global mean aerosol extinction profile, a so-called noise floor, for CALIOP all-RFV profiles. The global mean CALIOP AOT is then recomputed by replacing RFV values with the derived noise-floor values for both all-RFV and non-all-RFV profiles. This process yields an improvement in the agreement of CALIOP and MODIS over-ocean AOT.

Advantageous GOES IR results for ash mapping at high latitudes: Cleveland eruptions 2001

USGS Publications Warehouse

Gu, Yingxin; Rose, William I.; Schneider, D.J.; Bluth, G.J.S.; Watson, I.M.

2005-01-01

The February 2001 eruption of Cleveland Volcano, Alaska allowed for comparisons of volcanic ash detection using two-band thermal infrared (10-12 ??m) remote sensing from MODIS, AVHRR, and GOES 10. Results show that high latitude GOES volcanic cloud sensing the range of about 50 to 65??N is significantly enhanced. For the Cleveland volcanic clouds the MODIS and AVHRR data have zenith angles 6-65 degrees and the GOES has zenith angles that are around 70 degrees. The enhancements are explained by distortion in the satellite view of the cloud's lateral extent because the satellite zenith angles result in a "side-looking" aspect and longer path lengths through the volcanic cloud. The shape of the cloud with respect to the GOES look angle also influences the results. The MODIS and AVHRR data give consistent retrievals of the ash cloud evolution over time and are good corrections for the GOES data. Copyright 2005 by the American Geophysical Union.

Retrievals of Profiles of Fine And Coarse Aerosols Using Lidar And Radiometric Space Measurements

NASA Technical Reports Server (NTRS)

Kaufman, Yoram; Tanre, Didier; Leon, Jean-Francois; Pelon, Jacques; Lau, William K. M. (Technical Monitor)

2002-01-01

In couple of years we expect the launch of the CALIPSO lidar spaceborne mission designed to observe aerosols and clouds. CALIPSO will collect profiles of the lidar attenuated backscattering coefficients in two spectral wavelengths (0.53 and 1.06 microns). Observations are provided along the track of the satellite around the globe from pole to pole. The attenuated backscattering coefficients are sensitive to the vertical distribution of aerosol particles, their shape and size. However the information is insufficient to be mapped into unique aerosol physical properties and vertical distribution. Infinite number of physical solutions can reconstruct the same two wavelength backscattered profile measured from space. CALIPSO will fly in formation with the Aqua satellite and the MODIS spectro-radiometer on board. Spectral radiances measured by MODIS in six channels between 0.55 and 2.13 microns simultaneously with the CALIPSO observations can constrain the solutions and resolve this ambiguity, albeit under some assumptions. In this paper we describe the inversion method and apply it to aircraft lidar and MODIS data collected over a dust storm off the coast of West Africa during the SHADE experiment. It is shown that the product of the single scattering albedo, omega, and the phase function, P, for backscattering can be retrieved from the synergism between measurements avoiding a priori hypotheses required for inverting lidar measurements alone. The resultant value of (omega)P(180 deg.) = 0.016/sr are significantly different from what is expected using Mie theory, but are in good agreement with recent results obtained from lidar observations of dust episodes. The inversion is robust in the presence of noise of 10% and 20% in the lidar signal in the 0.53 and 1.06 pm channels respectively. Calibration errors of the lidar of 5 to 10% can cause an error in optical thickness of 20 to 40% respectively in the tested cases. The lidar calibration errors cause degradation in the ability to fit the MODIS data. Therefore the MODIS measurements can be used to identify the calibration problem and correct for it. The CALIPSO-MODIS measurements of the profiles of fine and coarse aerosols, together with CALIPSO measurements of clouds vertical distribution, is expected to be critically important in understanding aerosol transport across continents and political boundaries, and to study aerosol-cloud interaction and its effect on precipitation and global forcing of climate.

The Impact of Horizontal and Temporal Resolution on Convection and Precipitation with High-Resolution GEOS-5

NASA Technical Reports Server (NTRS)

Putman, William P.

2012-01-01

Using a high-resolution non-hydrostatic version of GEOS-5 with the cubed-sphere finite-volume dynamical core, the impact of spatial and temporal resolution on cloud properties will be evaluated. There are indications from examining convective cluster development in high resolution GEOS-5 forecasts that the temporal resolution within the model may playas significant a role as horizontal resolution. Comparing modeled convective cloud clusters versus satellite observations of brightness temperature, we have found that improved. temporal resolution in GEOS-S accounts for a significant portion of the improvements in the statistical distribution of convective cloud clusters. Using satellite simulators in GEOS-S we will compare the cloud optical properties of GEOS-S at various spatial and temporal resolutions with those observed from MODIS. The potential impact of these results on tropical cyclone formation and intensity will be examined as well.

Comparison of monthly nighttime cloud fraction products from MODIS and AIRS and ground-based camera over Manila Observatory (14.64N, 121.07E)

NASA Astrophysics Data System (ADS)

Gacal, G. F. B.; Lagrosas, N.

2017-12-01

Cloud detection nowadays is primarily achieved by the utilization of various sensors aboard satellites. These include MODIS Aqua, MODIS Terra, and AIRS with products that include nighttime cloud fraction. Ground-based instruments are, however, only secondary to these satellites when it comes to cloud detection. Nonetheless, these ground-based instruments (e.g., LIDARs, ceilometers, and sky-cameras) offer significant datasets about a particular region's cloud cover values. For nighttime operations of cloud detection instruments, satellite-based instruments are more reliably and prominently used than ground-based ones. Therefore if a ground-based instrument for nighttime operations is operated, it ought to produce reliable scientific datasets. The objective of this study is to do a comparison between the results of a nighttime ground-based instrument (sky-camera) and that of MODIS Aqua and MODIS Terra. A Canon Powershot A2300 is placed ontop of Manila Observatory (14.64N, 121.07E) and is configured to take images of the night sky at 5min intervals. To detect pixels with clouds, the pictures are converted to grayscale format. Thresholding technique is used to screen pixels with cloud and pixels without clouds. If the pixel value is greater than 17, it is considered as a cloud; otherwise, a noncloud (Gacal et al., 2016). This algorithm is applied to the data gathered from Oct 2015 to Oct 2016. A scatter plot between satellite cloud fraction in the area covering the area 14.2877N, 120.9869E, 14.7711N and 121.4539E and ground cloud cover is graphed to find the monthly correlation. During wet season (June - November), the satellite nighttime cloud fraction vs ground measured cloud cover produce an acceptable R2 (Aqua= 0.74, Terra= 0.71, AIRS= 0.76). However, during dry season, poor R2 values are obtained (AIRS= 0.39, Aqua & Terra = 0.01). The high correlation during wet season can be attributed to a high probability that the camera and satellite see the same clouds. However during dry season, the satellite sees high altitude clouds and the camera can not detect these clouds from the ground as it relies on city lights reflected from low level clouds. With this acknowledged disparity, the ground-based camera has the advantage of detecting haze and thin clouds near the ground that are hardly or not detected by the satellites.

Parametrization of Land Surface Temperature Fields with Optical and Microwave Remote Sensing in Brazil's Atlantic Forest

NASA Astrophysics Data System (ADS)

McDonald, K. C.; Khan, A.; Carnaval, A. C.

2016-12-01

Brazil is home to two of the largest and most biodiverse ecosystems in the world, primarily encompassed in forests and wetlands. A main region of interest in this project is Brazil's Atlantic Forest (AF). Although this forest is only a fraction of the size of the Amazon rainforest, it harbors significant biological richness, making it one of the world's major hotspots for biodiversity. The AF is located on the East to Southeast region of Brazil, bordering the Atlantic Ocean. As luscious and biologically rich as this region is, the area covered by the Atlantic Forest has been diminishing over past decades, mainly due to human influences and effects of climate change. We examine 1 km resolution Land Surface Temperature (LST) data from NASA's Moderate-resolution Imaging Spectroradiometer (MODIS) combined with 25 km resolution radiometric temperature derived from NASA's Advanced Microwave Scanning Radiometer on EOS (AMSR-E) to develop a capability employing both in combination to assess LST. Since AMSR-E is a microwave remote sensing instrument, products derived from its measurements are minimally effected by cloud cover. On the other hand, MODIS data are heavily influenced by cloud cover. We employ a statistical downscaling technique to the coarse-resolution AMSR-E datasets to enhance its spatial resolution to match that of MODIS. Our approach employs 16-day composite MODIS LST data in combination with synergistic ASMR-E radiometric brightness temperature data to develop a combined, downscaled dataset. Our goal is to use this integrated LST retrieval with complementary in situ station data to examine associated influences on regional biodiversity

Refinements to HIRS CO2 Slicing Algorithm with Results Compared to CALIOP and MODIS

NASA Astrophysics Data System (ADS)

Frey, R.; Menzel, P.

2012-12-01

This poster reports on the refinement of a cloud top property algorithm using High-resolution Infrared Radiation Sounder (HIRS) measurements. The HIRS sensor has been flown on fifteen satellites from TIROS-N through NOAA-19 and MetOp-A forming a continuous 30 year cloud data record. Cloud Top Pressure and effective emissivity (cloud fraction multiplied by cloud emissivity) are derived using the 15 μm spectral bands in the CO2 absorption band, implementing the CO2 slicing technique which is strong for high semi-transparent clouds but weak for low clouds with little thermal contrast from clear skies. We report on algorithm adjustments suggested from MODIS cloud record validations and the inclusion of collocated AVHRR cloud fraction data from the PATMOS-x algorithm. Reprocessing results for 2008 are shown using NOAA-18 HIRS and collocated CALIOP data for validation, as well as comparisons to MODIS monthly mean values. Adjustments to the cloud algorithm include (a) using CO2 slicing for all ice and mixed phase clouds and infrared window determinations for all water clouds, (b) determining the cloud top pressure from the most opaque CO2 spectral band pair seeing the cloud, (c) reducing the cloud detection threshold for the CO2 slicing algorithm to include conditions of smaller radiance differences that are often due to thin ice clouds, and (d) identifying stratospheric clouds when an opaque band is warmer than a less opaque band.

Shortwave direct radiative effects of above-cloud aerosols over global oceans derived from 8 years of CALIOP and MODIS observations

NASA Astrophysics Data System (ADS)

Zhang, Zhibo; Meyer, Kerry; Yu, Hongbin; Platnick, Steven; Colarco, Peter; Liu, Zhaoyan; Oreopoulos, Lazaros

2016-03-01

In this paper, we studied the frequency of occurrence and shortwave direct radiative effects (DREs) of above-cloud aerosols (ACAs) over global oceans using 8 years (2007-2014) of collocated CALIOP and MODIS observations. Similar to previous work, we found high ACA occurrence in four regions: southeastern (SE) Atlantic region, where ACAs are mostly light-absorbing aerosols, i.e., smoke and polluted dust according to CALIOP classification, originating from biomass burning over the African Savanna; tropical northeastern (TNE) Atlantic and the Arabian Sea, where ACAs are predominantly windblown dust from the Sahara and Arabian deserts, respectively; and the northwestern (NW) Pacific, where ACAs are mostly transported smoke and polluted dusts from Asian. From radiative transfer simulations based on CALIOP-MODIS observations and a set of the preselected aerosol optical models, we found the DREs of ACAs at the top of atmosphere (TOA) to be positive (i.e., warming) in the SE Atlantic and NW Pacific regions, but negative (i.e., cooling) in the TNE Atlantic Ocean and the Arabian Sea. The cancellation of positive and negative regional DREs results in a global ocean annual mean diurnally averaged cloudy-sky DRE of 0.015 W m-2 (range of -0.03 to 0.06 W m-2) at TOA. The DREs at surface and within the atmosphere are -0.15 W m-2 (range of -0.09 to -0.21 W m-2), and 0.17 W m-2 (range of 0.11 to 0.24 W m-2), respectively. The regional and seasonal mean DREs are much stronger. For example, in the SE Atlantic region, the JJA (July-August) seasonal mean cloudy-sky DRE is about 0.7 W m-2 (range of 0.2 to 1.2 W m-2) at TOA. All our DRE computations are publicly available1. The uncertainty in our DRE computations is mainly caused by the uncertainties in the aerosol optical properties, in particular aerosol absorption, the uncertainties in the CALIOP operational aerosol optical thickness retrieval, and the ignorance of cloud and potential aerosol diurnal cycle. In situ and remotely sensed measurements of ACA from future field campaigns and satellite missions and improved lidar retrieval algorithm, in particular vertical feature masking, would help reduce the uncertainty.

Shortwave Direct Radiative Effects of Above-Cloud Aerosols Over Global Oceans Derived From 8 Years of CALIOP and MODIS Observations

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Meyer, Kerry; Yu, Hongbin; Platnick, Steven; Colarco, Peter; Liu, Zhaoyan; Oraiopoulos, Lazaros

2016-01-01

In this paper, we studied the frequency of occurrence and shortwave direct radiative effects (DREs) of above-cloud aerosols (ACAs) over global oceans using 8 years (2007-2014) of collocated CALIOP and MODIS observations. Similar to previous work, we found high ACA occurrence in four regions: southeastern (SE) Atlantic region, where ACAs are mostly light-absorbing aerosols, i.e., smoke and polluted dust according to CALIOP classification, originating from biomass burning over the African Savanna; tropical northeastern (TNE) Atlantic and the Arabian Sea, where ACAs are predominantly windblown dust from the Sahara and Arabian deserts, respectively; and the northwestern (NW) Pacific, where ACAs are mostly transported smoke and polluted dusts from Asia. From radiative transfer simulations based on CALIOP-MODIS observations and a set of the preselected aerosol optical models, we found the DREs of ACAs at the top of atmosphere (TOA) to be positive (i.e., warming) in the SE Atlantic and NW Pacific regions, but negative (i.e., cooling) in the TNE Atlantic Ocean and the Arabian Sea. The cancellation of positive and negative regional DREs results in a global ocean annual mean diurnally averaged cloudy-sky DRE of 0.015 W m(exp. -2) [range of -0.03 to 0.06 W m (exp. -2)] at TOA. The DREs at surface and within the atmosphere are -0.015 W m(exp. -2) [range of -0.09 to -0.21 W m(exp. -2)], and 0.17 W m(exp. -2) [range of 0.11 to 0.24 W m(exp. -2)], respectively. The regional and seasonal mean DREs are much stronger. For example, in the SE Atlantic region, the JJA (July-August) seasonal mean cloudy-sky DRE is about 0.7 W m(exp. -2) [range of 0.2 to 1.2 W m(exp. -2)] at TOA. All our DRE computations are publicly available. The uncertainty in our DRE computations is mainly caused by the uncertainties in the aerosol optical properties, in particular aerosol absorption, the uncertainties in the CALIOP operational aerosol optical thickness retrieval, and the ignorance of cloud and potential aerosol diurnal cycle. In situ and remotely sensed measurements of ACA from future field campaigns and satellite missions and improved lidar retrieval algorithm, in particular vertical feature masking, would help reduce the uncertainty.

MODIS Data from the GES DISC DAAC: Moderate-Resolution Imaging Spectroradiometer (MODIS)

NASA Technical Reports Server (NTRS)

2002-01-01

The Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC) is responsible for the distribution of the Level 1 data, and the higher levels of all Ocean and Atmosphere products (Land products are distributed through the Land Processes (LP) DAAC DAAC, and the Snow and Ice products are distributed though the National Snow and Ice Data Center (NSIDC) DAAC). Ocean products include sea surface temperature (SST), concentrations of chlorophyll, pigment and coccolithophores, fluorescence, absorptions, and primary productivity. Atmosphere products include aerosols, atmospheric water vapor, clouds and cloud masks, and atmospheric profiles from 20 layers. While most MODIS data products are archived in the Hierarchical Data Format-Earth Observing System (HDF-EOS 2.7) format, the ocean binned products and primary productivity products (Level 4) are in the native HDF4 format. MODIS Level 1 and 2 data are of the Swath type and are packaged in files representing five minutes of Files for Level 3 and 4 are global products at daily, weekly, monthly or yearly resolutions. Apart from the ocean binned and Level 4 products, these are in Grid type, and the maps are in the Cylindrical Equidistant projection with rectangular grid. Terra viewing (scenes of approximately 2000 by 2330 km). MODIS data have several levels of maturity. Most products are released with a provisional level of maturity and only announced as validated after rigorous testing by the MODIS Science Teams. MODIS/Terra Level 1, and all MODIS/Terra 11 micron SST products are announced as validated. At the time of this publication, the MODIS Data Support Team (MDST) is working with the Ocean Science Team toward announcing the validated status of the remainder of MODIS/Terra Ocean products. MODIS/Aqua Level 1 and cloud mask products are released with provisional maturity.

Cloud occurrences and cloud radiative effects (CREs) from CERES-CALIPSO-CloudSat-MODIS (CCCM) and CloudSat radar-lidar (RL) products

NASA Astrophysics Data System (ADS)

Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Winker, David; L'Ecuyer, Tristan; Mace, Gerald G.; Painemal, David; Sun-Mack, Sunny; Chen, Yan; Miller, Walter F.

2017-08-01

Two kinds of cloud products obtained from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, and Moderate Resolution Imaging Spectroradiometer (MODIS) are compared and analyzed in this study: Clouds and the Earth's Radiant Energy System (CERES)-CALIPSO-CloudSat-MODIS (CCCM) product and CloudSat radar-lidar products such as GEOPROF-LIDAR and FLXHR-LIDAR. Compared to GEOPROF-LIDAR, low-level (<1 km) cloud occurrences in CCCM are larger over tropical oceans because the CCCM algorithm uses a more relaxed threshold of cloud-aerosol discrimination score for CALIPSO Vertical Feature Mask product. In contrast, midlevel (1-8 km) cloud occurrences in GEOPROF-LIDAR are larger than CCCM at high latitudes (>40°). The difference occurs when hydrometeors are detected by CALIPSO lidar but are undetected by CloudSat radar. In the comparison of cloud radiative effects (CREs), global mean differences between CCCM and FLXHR-LIDAR are mostly smaller than 5 W m-2, while noticeable regional differences are found. For example, CCCM shortwave (SW) and longwave (LW) CREs are larger than FXLHR-LIDAR along the west coasts of Africa and America because the GEOPROF-LIDAR algorithm misses shallow marine boundary layer clouds. In addition, FLXHR-LIDAR SW CREs are larger than the CCCM counterpart over tropical oceans away from the west coasts of America. Over midlatitude storm-track regions, CCCM SW and LW CREs are larger than the FLXHR-LIDAR counterpart.

[A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

PubMed

Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

2011-04-01

An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

Using multi-source satellite data to assess snow-cover change in Qinghai-Tibetan Plateau in last decade

NASA Astrophysics Data System (ADS)

Jiang, Y.; Chen, F.; Gao, Y.; Barlage, M. J.

2017-12-01

Snow cover in Qinghai-Tibetan Plateau (QTP) is a critical component of water cycle and affects regional climate of East Asia. Satellite data from three different sources (i.e., FY3A/B/C, MODIS and IMS) were used to analyze the QTP fractional-snow-cover (FSC) change and associated uncertainties in the last decade. To reduce the high percentage of cloud in FY3A/B/C and MODIS, a four-step cloud removal procedure was applied and effectively reduced the cloud percentage from 40.8-56.1% to 2.2­-­3.3%. The averaged error introduced by the cloud removal procedure was about 2% estimated by a random sampling method. Results show that the snow cover in QTP significantly decreased in recent 5 years. Three data sets (FY3B, MODIS and IMS) showed significant decreased annual FSC at all elevation bands from 2012-2016, and a significant shorter snow season with delayed snow onset and earlier melting. Both IMS and MODIS had a slightly decline annual FSC from 2000 to 3000 m, while MODIS FSC slightly decreased in 2002-2016 and IMS FSC slightly increased from 2006-2016 in the region with elevation higher than 3000 m. Results also show significant uncertainties among the five data sets (FY3A/B/C, MODIS, IMS), although they showed similar fluctuations of daily FSC. IMS had largest snow-cover extent and highest daily FSC due to its multi data sources. FY3A/C and MODIS (observed in the morning) had around 5% higher mean FSC than FY3B (observed in the afternoon) due to the 3 hours detection time gap. The relative error of daily FSC (taking MODIS as `truth') between FY3A/B/C, IMS and MODIS is 23%, -35%, 8% and 63%, respectively, averaged in five elevation bands in 2015-2017.

Observations of Three-Dimensional Radiative Effects that Influence Satellite Retrievals of Cloud Properties

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Marshak, Alexander; Lau, William K. M. (Technical Monitor)

2001-01-01

This paper examines three-dimensional (3D) radiative effects, which arise from horizontal radiative interactions between areas that have different cloud properties. Earlier studies have argued that these effects can cause significant uncertainties in current satellite retrievals of cloud properties, because the retrievals rely on one-dimensional (1D) theory and do not consider the effects of horizontal changes in cloud properties. This study addresses two questions: which retrieved cloud properties are influenced by 3D radiative effects, and where 3D effects tend to occur? The influence of 3D effects is detected from the wayside illumination and shadowing make clouds appear asymmetric: Areas appear brighter if the cloud top surface is tilted toward, rather than away from, the Sun. The analysis of 30 images by the Moderate Resolution Imaging Spectroradiometer (MODIS) reveals that retrievals of cloud optical thickness and cloud water content are most influenced by 3D effects, whereas retrievals of cloud particle size are much less affected. The results also indicate that while 3D effects are strongest at cloud edges, cloud top variability in cloud interiors, even in overcast regions, also produces considerable 3D effects. Finally, significant 3D effects are found in a wide variety of situations, ranging from thin clouds to thick ones and from low clouds to high ones.

The Dependence of Cloud Property Trend Detection on Absolute Calibration Accuracy of Passive Satellite Sensors

NASA Astrophysics Data System (ADS)

Shea, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Zelinka, M. D.

2016-12-01

Detecting trends in climate variables on global, decadal scales requires highly accurate, stable measurements and retrieval algorithms. Trend uncertainty depends on its magnitude, natural variability, and instrument and retrieval algorithm accuracy and stability. We applied a climate accuracy framework to quantify the impact of absolute calibration on cloud property trend uncertainty. The cloud properties studied were cloud fraction, effective temperature, optical thickness, and effective radius retrieved using the Clouds and the Earth's Radiant Energy System (CERES) Cloud Property Retrieval System, which uses Moderate-resolution Imaging Spectroradiometer measurements (MODIS). Modeling experiments from the fifth phase of the Climate Model Intercomparison Project (CMIP5) agree that net cloud feedback is likely positive but disagree regarding its magnitude, mainly due to uncertainty in shortwave cloud feedback. With the climate accuracy framework we determined the time to detect trends for instruments with various calibration accuracies. We estimated a relationship between cloud property trend uncertainty, cloud feedback, and Equilibrium Climate Sensitivity and also between effective radius trend uncertainty and aerosol indirect effect trends. The direct relationship between instrument accuracy requirements and climate model output provides the level of instrument absolute accuracy needed to reduce climate model projection uncertainty. Different cloud types have varied radiative impacts on the climate system depending on several attributes, such as their thermodynamic phase, altitude, and optical thickness. Therefore, we also conducted these studies by cloud types for a clearer understanding of instrument accuracy requirements needed to detect changes in their cloud properties. Combining this information with the radiative impact of different cloud types helps to prioritize among requirements for future satellite sensors and understanding the climate detection capabilities of existing sensors.

Comparison of Cloud and Aerosol Detection between CERES Edition 3 Cloud Mask and CALIPSO Version 2 Data Products

NASA Astrophysics Data System (ADS)

Trepte, Qing; Minnis, Patrick; Sun-Mack, Sunny; Trepte, Charles

Clouds and aerosol play important roles in the global climate system. Accurately detecting their presence, altitude, and properties using satellite radiance measurements is a crucial first step in determining their influence on surface and top-of-atmosphere radiative fluxes. This paper presents a comparison analysis of a new version of the Clouds and Earth's Radiant Energy System (CERES) Edition 3 cloud detection algorithms using Aqua MODIS data with the recently released Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Version 2 Vertical Feature Mask (VFM). Improvements in CERES Edition 3 cloud mask include dust detection, thin cirrus tests, enhanced low cloud detection at night, and a smoother transition from mid-latitude to polar regions. For the CALIPSO Version 2 data set, changes to the lidar calibration can result in significant improvements to its identification of optically thick aerosol layers. The Aqua and CALIPSO satellites, part of the A-train satellite constellation, provide a unique opportunity for validating passive sensor cloud and aerosol detection using an active sensor. In this paper, individual comparison cases will be discussed for different types of clouds and aerosols over various surfaces, for daytime and nighttime conditions, and for regions ranging from the tropics to the poles. Examples will include an assessment of the CERES detection algorithm for optically thin cirrus, marine stratus, and polar night clouds as well as its ability to characterize Saharan dust plumes off the African coast. With the CALIPSO lidar's unique ability to probe the vertical structure of clouds and aerosol layers, it provides an excellent validation data set for cloud detection algorithms, especially for polar nighttime clouds.

Ground-based and satellite optical investigation of the atmosphere and surface of Antarctica

NASA Astrophysics Data System (ADS)

Malinka, Aleksey; Blarel, Luc; Chaikovskaya, Ludmila; Chaikovsky, Anatoli; Denishchik-Nelubina, Natalia; Denisov, Sergei; Dick, Vladimir; Fedaranka, Anton; Goloub, Philippe; Katsev, Iosif; Korol, Michail; Lapyonok, Aleksandr; Podvin, Thierr; Prikhach, Alexander; Svidinsky, Vadim; Zege, Eleonora

2018-04-01

This presentation contains the results of the 10-year research of Belarusian Antarctic expeditions. The set of instruments consists of a lidar, an albedometer, and a scanning sky radiometer CIMEL. Besides, the data from satellite radiometer MODIS were used to characterize the snow cover. The works focus on the study of aerosol, cloud and snow characteristics in the Antarctic, and their links with the long range transport of atmospheric pollutants and climate changes.

Enhanced Satellite Remote Sensing of Coastal Waters Using Spatially Improved Bio-Optical Products from SNPP-VIIRS

DTIC Science & Technology

2015-01-01

a spatial resolution of 250-m. The Gumley et al. computation for MODIS sharpening is given as a ratio of high to low resolution top of the atmosphere...NIR) correction (Stumpf, Arnone, Gould, Martinolich, & Ransibrahamanakul, 2003). Standard flagswere used tomask interference from land, clouds , sun...technique This new approach expands on the methodology described by Gumley et al. (2010), with somemodifications. We will compute a sim- ilar spatial

Monitoring of 2007 wildfires in GA and CA by GOES Aerosol/Smoke Product (ASP): Comparisons to MODIS and CALIPSO

NASA Astrophysics Data System (ADS)

Xu, C.; Kondragunta, S.

2008-05-01

The purpose of this study is to understand the potential for using the GOES Aerosol/Smoke Product (GASP) to monitor wild fires over the United States. GASP AOD is retrieved using visible imagery from Geostationary Operational Environment Satellite (GOES) at 30 minute interval. This high temporal estimate of AOD provides significantly dense information of air quality in near real time. Hourly or daily animations of GASP aerosol optical depth for smoke plumes suggest that development and variation of wild fires can be determined by GASP. Also, the performances of GASP AOD are compared to other satellite data from MODerate-resolution Imaging Spectro- radiometers (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The results reveal that GOES AOD has same level performance for monitoring wild fires as those of MODIS and CALIPSO. Therefore, we believe that the retrieval accuracy of GOES is adequate for monitoring larger outbreaks of aerosol events.

Positive relationship between liquid cloud droplet effective radius and aerosol optical depth over Eastern China from satellite data

NASA Astrophysics Data System (ADS)

Tang, Jinping; Wang, Pucai; Mickley, Loretta J.; Xia, Xiangao; Liao, Hong; Yue, Xu; Sun, Li; Xia, Junrong

2014-02-01

Correlations between water cloud effective radius (CER) and aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) are examined over seven sub-regions in Eastern China for 2003-2012. Water phase cloud is defined as having a cloud top pressure greater than 800 hPa. Significant negative correlation coefficients (r = -0.79 ˜ -0.94) between AOD and CER are derived over the East Sea and the South China Sea for grid cells with AOD < 0.3. However, positive correlations (r = 0.01-0.91) are calculated for cells with AOD > 0.3. In contrast, significant positive correlations (r = 0.67-0.95) are derived over the Eastern China mainland and Yellow Sea. Further analysis for North China Plain shows that variations in wind speed and relative humidity may account for such positive correlations. Southerly winds carry high levels of pollutants and abundant water vapor, resulting in coincident increases in both AOD and CER in North China Plain, while the northerly winds transport dry and clean air from high latitudes, leading to decreases in AOD and CER. Both processes contribute to the positive correlations between AOD and CER over Eastern China, suggesting that the influence of background weather conditions need to be considered when studying the interactions between aerosol and cloud.

Improving correlations between MODIS aerosol optical thickness and ground-based PM 2.5 observations through 3D spatial analyses

NASA Astrophysics Data System (ADS)

Hutchison, Keith D.; Faruqui, Shazia J.; Smith, Solar

The Center for Space Research (CSR) continues to focus on developing methods to improve correlations between satellite-based aerosol optical thickness (AOT) values and ground-based, air pollution observations made at continuous ambient monitoring sites (CAMS) operated by the Texas commission on environmental quality (TCEQ). Strong correlations and improved understanding of the relationships between satellite and ground observations are needed to formulate reliable real-time predictions of air quality using data accessed from the moderate resolution imaging spectroradiometer (MODIS) at the CSR direct-broadcast ground station. In this paper, improvements in these correlations are demonstrated first as a result of the evolution in the MODIS retrieval algorithms. Further improvement is then shown using procedures that compensate for differences in horizontal spatial scales between the nominal 10-km MODIS AOT products and CAMS point measurements. Finally, airborne light detection and ranging (lidar) observations, collected during the Texas Air Quality Study of 2000, are used to examine aerosol profile concentrations, which may vary greatly between aerosol classes as a result of the sources, chemical composition, and meteorological conditions that govern transport processes. Further improvement in correlations is demonstrated with this limited dataset using insights into aerosol profile information inferred from the vertical motion vectors in a trajectory-based forecast model. Analyses are ongoing to verify these procedures on a variety of aerosol classes using data collected by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (Calipso) lidar.

Retrieving Aerosol in a Cloudy Environment: Aerosol Availability as a Function of Spatial and Temporal Resolution

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Mattoo, Shana; Levy, Robert C.; Heidinger, Andrew; Pierce, R. Bradley; Chin, Mian

2011-01-01

The challenge of using satellite observations to retrieve aerosol properties in a cloudy environment is to prevent contamination of the aerosol signal from clouds, while maintaining sufficient aerosol product yield to satisfy specific applications. We investigate aerosol retrieval availability at different instrument pixel resolutions, using the standard MODIS aerosol cloud mask applied to MODIS data and a new GOES-R cloud mask applied to GOES data for a domain covering North America and surrounding oceans. Aerosol availability is not the same as the cloud free fraction and takes into account the technqiues used in the MODIS algorithm to avoid clouds, reduce noise and maintain sufficient numbers of aerosol retrievals. The inherent spatial resolution of each instrument, 0.5x0.5 km for MODIS and 1x1 km for GOES, is systematically degraded to 1x1 km, 2x2 km, 4x4 km and 8x8 km resolutions and then analyzed as to how that degradation would affect the availability of an aerosol retrieval, assuming an aerosol product resolution at 8x8 km. The results show that as pixel size increases, availability decreases until at 8x8 km 70% to 85% of the retrievals available at 0.5 km have been lost. The diurnal pattern of aerosol retrieval availability examined for one day in the summer suggests that coarse resolution sensors (i.e., 4x4 km or 8x8 km) may be able to retrieve aerosol early in the morning that would otherwise be missed at the time of current polar orbiting satellites, but not the diurnal aerosol properties due to cloud cover developed during the day. In contrast finer resolution sensors (i.e., 1x1 km or 2x2 km) have much better opportunity to retrieve aerosols in the partly cloudy scenes and better chance of returning the diurnal aerosol properties. Large differences in the results of the two cloud masks designed for MODIS aerosol and GOES cloud products strongly reinforce that cloud masks must be developed with specific purposes in mind and that a generic cloud mask applied to an independent aerosol retrieval will likely fail.

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

PubMed Central

Chang, Howard H.; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei

2017-01-01

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, ~70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations. PMID:29057838

Determinants of Low Cloud Properties - An Artificial Neural Network Approach Using Observation Data Sets

NASA Astrophysics Data System (ADS)

Andersen, Hendrik; Cermak, Jan

2015-04-01

This contribution studies the determinants of low cloud properties based on the application of various global observation data sets in machine learning algorithms. Clouds play a crucial role in the climate system as their radiative properties and precipitation patterns significantly impact the Earth's energy balance. Cloud properties are determined by environmental conditions, as cloud formation requires the availability of water vapour ("precipitable water") and condensation nuclei in sufficiently saturated conditions. A main challenge in the research of aerosol-cloud interactions is the separation of aerosol effects from meteorological influence. To gain understanding of the processes that govern low cloud properties in order to increase accuracy of climate models and predictions of future changes in the climate system is thus of great importance. In this study, artificial neural networks are used to relate a selection of predictors (meteorological parameters, aerosol loading) to a set of predictands (cloud microphysical and optical properties). As meteorological parameters, wind direction and velocity, sea level pressure, static stability of the lower troposphere, atmospheric water vapour and temperature at the surface are used (re-analysis data by the European Centre for Medium-Range Weather Forecasts). In addition to meteorological conditions, aerosol loading is used as a predictor of cloud properties (MODIS collection 6 aerosol optical depth). The statistical model reveals significant relationships between predictors and predictands and is able to represent the aerosol-cloud-meteorology system better than frequently used bivariate relationships. The most important predictors can be identified by the additional error when excluding one predictor at a time. The sensitivity of each predictand to each of the predictors is analyzed.

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

NASA Technical Reports Server (NTRS)

Belle, Jessica H.; Chang, Howard H.; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei; Liu, Yang

2017-01-01

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, approximately 70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations.

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition.

PubMed

Belle, Jessica H; Chang, Howard H; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei; Liu, Yang

2017-10-18

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM 2.5 ) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, ~70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM 2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM 2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM 2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM 2.5 concentrations.

Evaluation of MODIS-Derived Cloud Fraction Using Surface Observations at Low-, Mid- and High Latitude DOE ARM sites

NASA Astrophysics Data System (ADS)

Wang, Yang; Zhao, Chuanfeng

2016-04-01

Clouds play essential roles in the Earth's energy and water cycle, and Cloud Fraction (CF) is one of the most important cloud parameters. The CF from Moderate Resolution Imaging Spectroradiometer (MODIS) has been widely used, whereas the time representation of these instantaneous CF values is not clear. In this study, we evaluate MODIS-derived CF by using continuous, day-and-night radar/lidar CF from the Atmospheric Radiation Measurement (ARM) program Active Remote Sensing of CLouds (ARSCL) product and the total sky cover (TSC) day-time CF datasets. Inter-comparisons between MODIS and surface CFs for time period from 2000 to 2011 are performed for three climate regimes as represented by the ARM sites of Southern Great Plains (SGP), Manus, Papua New Guinea (PNG) and North Slope of Alaska (NSA). We first choose both the TSC and ARSCL CFs averaged over 1 hour around the two passing time of satellite, which are around 10:30 AM and 1:30 PM local time. Then two kind of analyses have been done. One is the spatial variation analysis and the other is temporal variation analysis. For the spatial variation analysis, we compare the 1-hour averaged cloud fractions from TSC and ARSCL around 10:30 AM and 1:30 PM with the instantaneous cloud fractions from MODIS but with different spatial resolution. By obtaining the RMS errors and ratio of average values of CFs for these inter-comparisons, the optimal CF-matching spatial resolutions for MODIS regarding to TSC and ARSCL are obtained which are both 30 km radius of circle. We also find that the optimal matching spatial resolution increases when the ground observation average time increases. For the temporal analysis, we first analyze the diurnal variation of the cloud fraction based on the surface CFs from TSC and ARSCL from which we can see the daily representation of cloud fraction observed at 10:30 AM and 1:30 PM. Then we make a statistical comparison of daily and monthly cloud fraction between using all time observation and using the 1-hour averaged observations at both 10:30 AM and 1:30 PM. Comparison results will be shown in our paper. It shows a high correlation coefficient of 0.95 (0.93) for observations from TSC (ARSCL). The ratios of daily (monthly) averaged cloud fraction between using all time and using the time satellite passes are 0.87(0.92) and 0.86(0.97) for TSC and ARSCL, respectively. This suggests that considerable errors could be introduced while using the cloud fraction at two fixed time points (10:30 AM and 1:30 PM) to represent the daily cloud fraction.

Effects of ice crystal surface roughness and air bubble inclusions on cirrus cloud radiative properties from remote sensing perspective

NASA Astrophysics Data System (ADS)

Tang, Guanglin; Panetta, R. Lee; Yang, Ping; Kattawar, George W.; Zhai, Peng-Wang

2017-07-01

We study the combined effects of surface roughness and inhomogeneity on the optical scattering properties of ice crystals and explore the consequent implications to remote sensing of cirrus cloud properties. Specifically, surface roughness and inhomogeneity are added to the Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 (MC6) cirrus cloud particle habit model. Light scattering properties of the new habit model are simulated using a modified version of the Improved Geometric Optics Method (IGOM). Both inhomogeneity and surface roughness affect the single scattering properties significantly. In visible bands, inhomogeneity and surface roughness both tend to smooth the phase function and eliminate halos and the backscattering peak. The asymmetry parameter varies with the degree of surface roughness following a U shape - decreases and then increases - with a minimum at around 0.15, whereas it decreases monotonically with the air bubble volume fraction. Air bubble inclusions significantly increase phase matrix element -P12 for scattering angles between 20°-120°, whereas surface roughness has a much weaker effect, increasing -P12 slightly from 60°-120°. Radiative transfer simulations and cirrus cloud property retrievals are conducted by including both the factors. In terms of surface roughness and air bubble volume fraction, retrievals of cirrus cloud optical thickness or the asymmetry parameter using solar bands show similar patterns of variation. Polarimetric simulations using the MC6 cirrus cloud particle habit model are shown to be more consistent with observations when both surface roughness and inhomogeneity are simultaneously considered.

Daytime Cloud Property Retrievals Over the Arctic from Multispectral MODIS Data

NASA Technical Reports Server (NTRS)

Spangenberg, Douglas A.; Trepte, Qing; Minnis, Patrick; Uttal, Taneil

2004-01-01

Improving climate model predictions over Earth's polar regions requires a complete understanding of polar clouds properties. Passive satellite remote sensing techniques can be used to retrieve macro and microphysical properties of polar cloud systems. However, over the Arctic, there is minimal contrast between clouds and the background snow surface observed in satellite data, especially for visible wavelengths. This makes it difficult to identify clouds and retrieve their properties from space. Variable snow and ice cover, temperature inversions, and the predominance of mixed-phase clouds further complicate cloud property identification. For this study, the operational Clouds and the Earth s Radiant Energy System (CERES) cloud mask is first used to discriminate clouds from the background surface in Terra Moderate Resolution Imaging Spectroradiometer (MODIS) data. A solar-infrared infrared nearinfrared technique (SINT) first used by Platnick et al. (2001) is used here to retrieve cloud properties over snow and ice covered regions.

Study and Application on Cloud Covered Rate for Agroclimatical Distribution Using In Guangxi Based on Modis Data

NASA Astrophysics Data System (ADS)

Yang, Xin; Zhong, Shiquan; Sun, Han; Tan, Zongkun; Li, Zheng; Ding, Meihua

Based on analyzing of the physical characteristics of cloud and importance of cloud in agricultural production and national economy, cloud is a very important climatic resources such as temperature, precipitation and solar radiation. Cloud plays a very important role in agricultural climate division .This paper analyzes methods of cloud detection based on MODIS data in China and Abroad . The results suggest that Quanjun He method is suitable to detect cloud in Guangxi. State chart of cloud cover in Guangxi is imaged by using Quanjun He method .We find out the approach of calculating cloud covered rate by using the frequency spectrum analysis. At last, the Guangxi is obtained. Taking Rongxian County Guangxi as an example, this article analyze the preliminary application of cloud covered rate in distribution of Rong Shaddock pomelo . Analysis results indicate that cloud covered rate is closely related to quality of Rong Shaddock pomelo.

Orbiting Carbon Observatory-2 (OCO-2) Cloud Screening; Validation Against Collocated MODIS and Initial Comparison to CALIOP Data

NASA Technical Reports Server (NTRS)

Taylor, Thomas E.; O'Dell, Christopher W.; Frankenberg, Christian; Partain, Philip; Cronk, Heather W.; Savtchenko, Andrey; Nelson, Robert R.; Rosenthal, Emily J.; Chang, Albert; Crisp, David;

Radiative effects of global MODIS cloud regimes

PubMed Central

Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Kato, Seiji

2018-01-01

We update previously published MODIS global cloud regimes (CRs) using the latest MODIS cloud retrievals in the Collection 6 dataset. We implement a slightly different derivation method, investigate the composition of the regimes, and then proceed to examine several aspects of CR radiative appearance with the aid of various radiative flux datasets. Our results clearly show the CRs are radiatively distinct in terms of shortwave, longwave and their combined (total) cloud radiative effect. We show that we can clearly distinguish regimes based on whether they radiatively cool or warm the atmosphere, and thanks to radiative heating profiles to discern the vertical distribution of cooling and warming. Terra and Aqua comparisons provide information about the degree to which morning and afternoon occurrences of regimes affect the symmetry of CR radiative contribution. We examine how the radiative discrepancies among multiple irradiance datasets suffering from imperfect spatiotemporal matching depend on CR, and whether they are therefore related to the complexity of cloud structure, its interpretation by different observational systems, and its subsequent representation in radiative transfer calculations. PMID:29619289

Radiative effects of global MODIS cloud regimes.

PubMed

Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Kato, Seiji

2016-03-16

We update previously published MODIS global cloud regimes (CRs) using the latest MODIS cloud retrievals in the Collection 6 dataset. We implement a slightly different derivation method, investigate the composition of the regimes, and then proceed to examine several aspects of CR radiative appearance with the aid of various radiative flux datasets. Our results clearly show the CRs are radiatively distinct in terms of shortwave, longwave and their combined (total) cloud radiative effect. We show that we can clearly distinguish regimes based on whether they radiatively cool or warm the atmosphere, and thanks to radiative heating profiles to discern the vertical distribution of cooling and warming. Terra and Aqua comparisons provide information about the degree to which morning and afternoon occurrences of regimes affect the symmetry of CR radiative contribution. We examine how the radiative discrepancies among multiple irradiance datasets suffering from imperfect spatiotemporal matching depend on CR, and whether they are therefore related to the complexity of cloud structure, its interpretation by different observational systems, and its subsequent representation in radiative transfer calculations.

Radiative Effects of Global MODIS Cloud Regimes

NASA Technical Reports Server (NTRS)

Oraiopoulos, Lazaros; Cho, Nayeong; Lee, Dong Min; Kato, Seiji

2016-01-01

We update previously published MODIS global cloud regimes (CRs) using the latest MODIS cloud retrievals in the Collection 6 dataset. We implement a slightly different derivation method, investigate the composition of the regimes, and then proceed to examine several aspects of CR radiative appearance with the aid of various radiative flux datasets. Our results clearly show the CRs are radiatively distinct in terms of shortwave, longwave and their combined (total) cloud radiative effect. We show that we can clearly distinguish regimes based on whether they radiatively cool or warm the atmosphere, and thanks to radiative heating profiles to discern the vertical distribution of cooling and warming. Terra and Aqua comparisons provide information about the degree to which morning and afternoon occurrences of regimes affect the symmetry of CR radiative contribution. We examine how the radiative discrepancies among multiple irradiance datasets suffering from imperfect spatiotemporal matching depend on CR, and whether they are therefore related to the complexity of cloud structure, its interpretation by different observational systems, and its subsequent representation in radiative transfer calculations.

Smoke, Clouds, and Radiation-Brazil (SCAR-B) Experiment

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Hobbs, P. V.; Kirchoff, V. W. J. H.; Artaxo, P.; Remer, L. A.; Holben, B. N.; King, M. D.; Ward, D. E.; Prins, E. M.; Longo, K. M.;

CERES cloud property retrievals from imagers on TRMM, Terra, and Aqua

NASA Astrophysics Data System (ADS)

Minnis, Patrick; Young, David F.; Sun-Mack, Sunny; Heck, Patrick W.; Doelling, David R.; Trepte, Qing Z.

2004-02-01

The micro- and macrophysical properties of clouds play a crucial role in Earth"s radiation budget. The NASA Clouds and Earth"s Radiant Energy System (CERES) is providing simultaneous measurements of the radiation and cloud fields on a global basis to improve the understanding and modeling of the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. Cloud properties derived for CERES from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites are compared to ensure consistency between the products to ensure the reliability of the retrievals from multiple platforms at different times of day. Comparisons of cloud fraction, height, optical depth, phase, effective particle size, and ice and liquid water paths from the two satellites show excellent consistency. Initial calibration comparisons are also very favorable. Differences between the Aqua and Terra results are generally due to diurnally dependent changes in the clouds. Additional algorithm refinement is needed over the polar regions for Aqua and at night over those same areas for Terra. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data: Part III. Using Combined PCA to Compare Spatiotemporal Variability of MODIS, MISR and OMI Aerosol Optical Depth

NASA Technical Reports Server (NTRS)

Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

2014-01-01

Satellite measurements of global aerosol properties are very useful in constraining aerosol parameterization in climate models. The reliability of different data sets in representing global and regional aerosol variability becomes an essential question. In this study, we present the results of a comparison using combined principal component analysis (CPCA), applied to monthly mean, mapped (Level 3) aerosol optical depth (AOD) product from Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Ozone Monitoring Instrument (OMI). This technique effectively finds the common space-time variability in the multiple data sets by decomposing the combined AOD field. The results suggest that all of the sensors capture the globally important aerosol regimes, including dust, biomass burning, pollution, and mixed aerosol types. Nonetheless, differences are also noted. Specifically, compared with MISR and OMI, MODIS variability is significantly higher over South America, India, and the Sahel. MODIS deep blue AOD has a lower seasonal variability in North Africa, accompanied by a decreasing trend that is not found in either MISR or OMI AOD data. The narrow swath of MISR results in an underestimation of dust variability over the Taklamakan Desert. The MISR AOD data also exhibit overall lower variability in South America and the Sahel. OMI does not capture the Russian wild fire in 2010 nor the phase shift in biomass burning over East South America compared to Central South America, likely due to cloud contamination and the OMI row anomaly. OMI also indicates a much stronger (boreal) winter peak in South Africa compared with MODIS and MISR.

Direct Aerosol Radiative Forcing from Combined A-Train Observations - Preliminary Comparisons with AeroCom Models and Pathways to Observationally Based All-sky Estimates

NASA Astrophysics Data System (ADS)

Redemann, J.; Livingston, J. M.; Shinozuka, Y.; Kacenelenbogen, M. S.; Russell, P. B.; LeBlanc, S. E.; Vaughan, M.; Ferrare, R. A.; Hostetler, C. A.; Rogers, R. R.; Burton, S. P.; Torres, O.; Remer, L. A.; Stier, P.; Schutgens, N.

2014-12-01

We describe a technique for combining CALIOP aerosol backscatter, MODIS spectral AOD (aerosol optical depth), and OMI AAOD (absorption aerosol optical depth) retrievals for the purpose of estimating full spectral sets of aerosol radiative properties, and ultimately for calculating the 3-D distribution of direct aerosol radiative forcing. We present results using one year of data collected in 2007 and show comparisons of the aerosol radiative property estimates to collocated AERONET retrievals. Use of the recently released MODIS Collection 6 data for aerosol optical depths derived with the dark target and deep blue algorithms has extended the coverage of the multi-sensor estimates towards higher latitudes. Initial calculations of seasonal clear-sky aerosol radiative forcing based on our multi-sensor aerosol retrievals compare well with over-ocean and top of the atmosphere IPCC-2007 model-based results, and with more recent assessments in the "Climate Change Science Program Report: Atmospheric Aerosol Properties and Climate Impacts" (2009). For the first time, we present comparisons of our multi-sensor aerosol direct radiative forcing estimates to values derived from a subset of models that participated in the latest AeroCom initiative. We discuss the major challenges that exist in extending our clear-sky results to all-sky conditions. On the basis of comparisons to suborbital measurements, we present some of the limitations of the MODIS and CALIOP retrievals in the presence of adjacent or underlying clouds. Strategies for meeting these challenges are discussed.

Study of Aerosol - Cloud Interaction over Indo - Gangetic Basin During Normal Monsoon and Drought Years

NASA Astrophysics Data System (ADS)

Tiwari, S.; Ramachandran, S.

2017-12-01

Clouds are one of the major factors that influence the Earth's radiation budget and also change the precipitation pattern. Atmospheric aerosols play a crucial role in modifying the cloud properties acting as cloud condensation nuclei (CCN). It can change cloud droplet number concentration, cloud droplet size and hence cloud albedo. Therefore, the effects of aerosol on cloud parameters are one of the most important topics in climate change study. In the present study, we investigate the spatial variability of aerosol - cloud interactions during normal monsoon years and drought years over entire Indo - Gangetic Basin (IGB) which is one of the most polluted regions of the world. Based on aerosol loading and their major emission sources, we divided the entire IGB in to six major sub regions (R1: 66 - 71 E, 24 - 29 N; R2: 71 - 76 E, 29 - 34 N; R3: 76 - 81 E, 26 - 31 N; R4: 81 - 86 E, 23 - 28 N; R5: 86 - 91 E, 22 - 27 N and R6: 91 - 96 E, 23 - 28 N). With this objective, fifteen years (2001 - 2015), daily mean aerosol optical depth, cloud parameters and rainfall data obtained from MODerate resolution Imaging Spectroradiometer (MODIS) on board of Terra satellite and Tropical Rainfall Measuring Mission (TRMM) is analyzed over each sub regions of IGB for monsoon season (JJAS : June, July, August and September months). Preliminary results suggest that a slightly change in aerosol optical depth can affect the significant contribution of cloud fraction and other cloud properties which also show a large spatial heterogeneity. During drought years, higher cloud effective radius (i.e. CER > 20µm) decreases from western to eastern IGB suggesting the enhancement in cloud albedo. Relatively week correlation between cloud optical thickness and rainfall is found during drought years than the normal monsoon years over western IGB. The results from the present study will be helpful to reduce uncertainty in understanding of aerosol - cloud interaction over IGB. Further details will be presented during the conference.

Aerosol and cloud properties derived from hyperspectral transmitted light in the southeast Atlantic sampled during field campaign deployments in 2016 and 2017

NASA Astrophysics Data System (ADS)

LeBlanc, S. E.; Redemann, J.; Flynn, C. J.; Segal-Rosenhaimer, M.; Kacenelenbogen, M. S.; Shinozuka, Y.; Pistone, K.; Karol, Y.; Schmidt, S.; Cochrane, S.; Chen, H.; Meyer, K.; Ferrare, R. A.; Burton, S. P.; Hostetler, C. A.; Hair, J. W.

2017-12-01

We present aerosol and cloud properties collected from airborne remote-sensing measurements in the southeast Atlantic during the recent NASA ObseRvations of CLouds above Aerosols and their intEractionS (ORACLES) field campaign. During the biomass burning seasons of September 2016 and August 2017, we sampled aerosol layers which overlaid marine stratocumulus clouds off the southwestern coast of Africa. We sampled these aerosol layers and the underlying clouds from the NASA P3 airborne platform with the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR). Aerosol optical depth (AOD), along with trace gas content in the atmospheric column (water vapor, NO2, and O3), is obtained from the attenuation in the sun's direct beam, measured at the altitude of the airborne platform. Using hyperspectral transmitted light measurements from 4STAR, in conjunction with hyperspectral hemispheric irradiance measurements from the Solar Spectral Flux Radiometers (SSFR), we also obtained aerosol intensive properties (asymmetry parameter, single scattering albedo), aerosol size distributions, cloud optical depth (COD), cloud particle effective radius, and cloud thermodynamic phase. Aerosol intensive properties are retrieved from measurements of angularly resolved skylight and flight level spectral albedo using the inversion used with measurements from AERONET (Aerosol Robotic Network) that has been modified for airborne use. The cloud properties are obtained from 4STAR measurements of scattered light below clouds. We show a favorable initial comparison of the above-cloud AOD measured by 4STAR to this same product retrieved from measurements by the MODIS instrument on board the TERRA and AQUA satellites. The layer AOD observed above clouds will also be compared to integrated aerosol extinction profile measurements from the High Spectral Resolution Lidar-2 (HSRL-2).

Validation and Uncertainty Estimates for MODIS Collection 6 "Deep Blue" Aerosol Data

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Jeong, M.-J.

2013-01-01

The "Deep Blue" aerosol optical depth (AOD) retrieval algorithm was introduced in Collection 5 of the Moderate Resolution Imaging Spectroradiometer (MODIS) product suite, and complemented the existing "Dark Target" land and ocean algorithms by retrieving AOD over bright arid land surfaces, such as deserts. The forthcoming Collection 6 of MODIS products will include a "second generation" Deep Blue algorithm, expanding coverage to all cloud-free and snow-free land surfaces. The Deep Blue dataset will also provide an estimate of the absolute uncertainty on AOD at 550 nm for each retrieval. This study describes the validation of Deep Blue Collection 6 AOD at 550 nm (Tau(sub M)) from MODIS Aqua against Aerosol Robotic Network (AERONET) data from 60 sites to quantify these uncertainties. The highest quality (denoted quality assurance flag value 3) data are shown to have an absolute uncertainty of approximately (0.086+0.56Tau(sub M))/AMF, where AMF is the geometric air mass factor. For a typical AMF of 2.8, this is approximately 0.03+0.20Tau(sub M), comparable in quality to other satellite AOD datasets. Regional variability of retrieval performance and comparisons against Collection 5 results are also discussed.

Remote sensing of smoke, land, and clouds from the NASA ER-2 during SAFARI 2000

NASA Astrophysics Data System (ADS)

King, Michael D.; Platnick, Steven; Moeller, Christopher C.; Revercomb, Henry E.; Chu, D. Allen

2003-07-01

The NASA ER-2 aircraft was deployed to southern Africa between 13 August and 25 September 2000 as part of the Southern African Regional Science Initiative (SAFARI) 2000. This aircraft carried a sophisticated array of multispectral scanners, multiangle spectroradiometers, a monostatic lidar, a gas correlation radiometer, upward and downward spectral flux radiometers, and two metric mapping cameras. These observations were obtained over a 3200 × 2800 km region of savanna, woody savanna, open shrubland, and grassland ecosystems throughout southern Africa and were quite often coordinated with overflights by NASA's Terra and Landsat 7 satellites. The primary purpose of this high-altitude observing platform was to obtain independent observations of smoke, clouds, and land surfaces that could be used to check the validity of various remote sensing measurements derived by Earth-orbiting satellites. These include such things as the accuracy of the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask for distinguishing clouds and heavy aerosol from land and ocean surfaces and Terra analyses of cloud optical and microphysical properties, aerosol properties, leaf area index, vegetation index, fire occurrence, carbon monoxide, and surface radiation budget. In addition to coordination with Terra and Landsat 7 satellites, numerous flights were conducted over surface AERONET sites, flux towers in South Africa, Botswana, and Zambia, and in situ aircraft from the University of Washington, South Africa, and the United Kingdom. As a result of this experiment, the MODIS cloud mask was shown to distinguish clouds, cloud shadows, and fires over land ecosystems of southern Africa with a high degree of accuracy. In addition, data acquired from the ER-2 show the vertical distribution and stratification of aerosol layers over the subcontinent and make the first observations of a "blue spike" spectral emission signature associated with air heated by fire advecting over a cooler land surface.

Evaluation of Cloud and Aerosol Screening of Early Orbiting Carbon Observatory-2 (OCO-2) Observations with Collocated MODIS Cloud Mask

NASA Astrophysics Data System (ADS)

Nelson, R. R.; Taylor, T.; O'Dell, C.; Cronk, H. Q.; Partain, P.; Frankenberg, C.; Eldering, A.; Crisp, D.; Gunson, M. R.; Chang, A.; Fisher, B.; Osterman, G. B.; Pollock, H. R.; Savtchenko, A.; Rosenthal, E. J.

2015-12-01

Effective cloud and aerosol screening is critically important to the Orbiting Carbon Observatory-2 (OCO-2), which can accurately determine column averaged dry air mole fraction of carbon dioxide (XCO2) only when scenes are sufficiently clear of scattering material. It is crucial to avoid sampling biases, in order to maintain a globally unbiased XCO2 record for inversion modeling to determine sources and sinks of carbon dioxide. This work presents analysis from the current operational B7 data set, which is identifying as clear approximately 20% of the order one million daily soundings. Of those soundings that are passed to the L2 retrieval algorithm, we find that almost 80% are yielding XCO2 estimates that converge. Two primary preprocessor algorithms are used to cloud screen the OCO-2 soundings. The A-Band Preprocessor (ABP) uses measurements in the Oxygen-A band near 0.76 microns (mm) to determine scenes with large photon path length modifications due to scattering by aerosol and clouds. The Iterative Maximum A-Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) algorithm (IDP) computes ratios of retrieved CO2 (and H2O) in the 1.6mm (weak CO2) and 2.0mm (strong CO2) spectral bands to determine scenes with spectral differences, indicating contamination by scattering materials. We demonstrate that applying these two algorithms in tandem provides robust cloud screening of the OCO-2 data set. We compare the OCO-2 cloud screening results to collocated Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask data and show that agreement between the two sensors is approximately 85-90%. A detailed statistical analysis is performed on a winter and spring 16-day repeat cycle for the nadir-land, glint-land and glint-water viewing geometries. No strong seasonal, spatial or footprint dependencies are found, although the agreement tends to be worse at high solar zenith angles and for snow and ice covered surfaces.

Clear-sky remote sensing in the vicinity of clouds: what can be learned about aerosol changes?

NASA Astrophysics Data System (ADS)

Marshak, Alexander; Varnai, Tamas; Wen, Guoyong

2010-05-01

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.

A CERES-like Cloud Property Climatology Using AVHRR Data

NASA Astrophysics Data System (ADS)

Minnis, P.; Bedka, K. M.; Yost, C. R.; Trepte, Q.; Bedka, S. T.; Sun-Mack, S.; Doelling, D.

2015-12-01

Clouds affect the climate system by modulating the radiation budget and distributing precipitation. Variations in cloud patterns and properties are expected to accompany changes in climate. The NASA Clouds and the Earth's Radiant Energy System (CERES) Project developed an end-to-end analysis system to measure broadband radiances from a radiometer and retrieve cloud properties from collocated high-resolution MODerate-resolution Imaging Spectroradiometer (MODIS) data to generate a long-term climate data record of clouds and clear-sky properties and top-of-atmosphere radiation budget. The first MODIS was not launched until 2000, so the current CERES record is only 15 years long at this point. The core of the algorithms used to retrieve the cloud properties from MODIS is based on the spectral complement of the Advanced Very High Resolution Radiometer (AVHRR), which has been aboard a string of satellites since 1978. The CERES cloud algorithms were adapted for application to AVHRR data and have been used to produce an ongoing CERES-like cloud property and surface temperature product that includes an initial narrowband-based radiation budget. This presentation will summarize this new product, which covers nearly 37 years, and its comparability with cloud parameters from CERES, CALIPSO, and other satellites. Examples of some applications of this dataset are given and the potential for generating a long-term radiation budget CDR is also discussed.

NPOESS Preparatory Project Validation Program for Atmsophere Data Products from VIIRS

NASA Astrophysics Data System (ADS)

Starr, D.; Wong, E.

2009-12-01

The National Polar-orbiting Operational Environmental Satellite Suite (NPOESS) Program, in partnership with National Aeronautical Space Administration (NASA), will launch the NPOESS Preparatory Project (NPP), a risk reduction and data continuity mission, prior to the first operational NPOESS launch. The NPOESS Program, in partnership with Northrop Grumman Aerospace Systems (NGAS), will execute the NPP Validation program to ensure the data products comply with the requirements of the sponsoring agencies. Data from the NPP Visible/Infrared Imager/Radiometer Suite (VIIRS) will be used to produce Environmental Data Records (EDR's) for aerosol and clouds, specifically Aerosol Optical Thickness (AOT), Aerosol Particle Size Parameter (APSP), and Suspended Matter (SM); and Cloud Optical Thickness (COT), Cloud Effective Particle Size (CEPS), Cloud Top Temperature (CTT), Height (CTH) and Pressure (CTP), and Cloud Base Height (CBH). The Aerosol and Cloud EDR Validation Program is a multifaceted effort to characterize and validate these data products. The program involves systematic comparison to heritage data products, e.g., MODIS, and ground-based correlative data, such as AERONET and ARM data products, and potentially airborne field measurements. To the extent possible, the domain is global. The program leverages various investments that have and are continuing to be made by national funding agencies in such resources, as well as the operational user community and the broad Earth science user community. This presentation will provide an overview of the approaches, data and schedule for the validation of the NPP VIIRS Aerosol and Cloud environmental data products.

MODIS Collection 6 Data at the National Snow and Ice Data Center (NSIDC)

NASA Astrophysics Data System (ADS)

Fowler, D. K.; Steiker, A. E.; Johnston, T.; Haran, T. M.; Fowler, C.; Wyatt, P.

2015-12-01

For over 15 years, the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) has archived and distributed snow and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the NASA Earth Observing System (EOS) Aqua and Terra satellites. Collection 6 represents the next revision to NSIDC's MODIS archive, mainly affecting the snow-cover products. Collection 6 specifically addresses the needs of the MODIS science community by targeting the scenarios that have historically confounded snow detection and introduced errors into the snow-cover and fractional snow-cover maps even though MODIS snow-cover maps are typically 90 percent accurate or better under good observing conditions, Collection 6 uses revised algorithms to discriminate between snow and clouds, resolve uncertainties along the edges of snow-covered regions, and detect summer snow cover in mountains. Furthermore, Collection 6 applies modified and additional snow detection screens and new Quality Assessment protocols that enhance the overall accuracy of the snow maps compared with Collection 5. Collection 6 also introduces several new MODIS snow products, including a daily Climate Modelling Grid (CMG) cloud gap-filled (CGF) snow-cover map which generates cloud-free maps by using the most recent clear observations.. The MODIS Collection 6 sea ice extent and ice surface temperature algorithms and products are much the same as Collection 5; however, Collection 6 updates to algorithm inputs—in particular, the L1B calibrated radiances, land and water mask, and cloud mask products—have improved the sea ice outputs. The MODIS sea ice products are currently available at NSIDC, and the snow cover products are soon to follow in 2016 NSIDC offers a variety of methods for obtaining these data. Users can download data directly from an online archive or use the NASA Reverb Search & Order Tool to perform spatial, temporal, and parameter subsetting, reformatting, and re-projection of the data.

Wave Clouds over Ireland

NASA Image and Video Library

2017-12-08

Visualization Date 2003-12-18 Clouds ripple over Ireland and Scotland in a wave pattern, similar to the pattern of waves along a seashore. The similarity is not coincidental — the atmosphere behaves like a fluid, so when it encounters an obstacle, it must move around it. This movement forms a wave, and the wave movement can continue for long distances. In this case, the waves were caused by the air moving over and around the mountains of Scotland and Ireland. As the air crested a wave, it cooled, and clouds formed. Then, as the air sank into the trough, the air warmed, and clouds did not form. This pattern repeated itself, with clouds appearing at the peak of every wave. Other types of clouds are also visible in the scene. Along the northwestern and southwestern edges of this true-color image from December 17, 2003, are normal mid-altitude clouds with fairly uniform appearances. High altitude cirrus-clouds float over these, casting their shadows on the lower clouds. Open- and closed-cell clouds formed off the coast of northwestern France, and thin contrail clouds are visible just east of these. Contrail clouds form around the particles carried in airplane exhaust. Fog is also visible in the valleys east of the Cambrian Mountains, along the border between northern/central Wales and England. This is an Aqua MODIS image. Sensor Aqua/MODIS Credit Jacques Descloitres, MODIS Rapid Response Team, NASA/GSFC For more information go to: visibleearth.nasa.gov/view_rec.php?id=6146

First Complete Day from MODIS

NASA Technical Reports Server (NTRS)

2002-01-01

This spectacular, full-color image of the Earth is a composite of the first full day of data gathered by the Moderate-resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra spacecraft. MODIS collected the data for each wavelength of red, green, and blue light as Terra passed over the daylit side of the Earth on April 19, 2000. Terra is orbiting close enough to the Earth so that it cannot quite see the entire surface in a day, resulting in the narrow gaps around the equator. Although the sensor's visible channels were combined to form this true-color picture, MODIS collects data in a total of 36 wavelengths, ranging from visible to thermal infrared energy. Scientists use these data to measure regional and global-scale changes in marine and land-based plant life, sea and land surface temperatures, cloud properties, aerosols, fires, and land surface properties. Notice how cloudy the Earth is, and the large differences in brightness between clouds, deserts, oceans, and forests. The Antarctic, surrounded by clockwise swirls of cloud, is shrouded in darkness because the sun is north of the equator at this time of year. The tropical forests of Africa, Southeast Asia, and South America are shrouded by clouds. The bright Sahara and Arabian deserts stand out clearly. Green vegetation is apparent in the southeast United States, the Yucatan Peninsula, and Madagascar. Image by Mark Gray, MODIS Atmosphere Team, NASA GSFC

Sensitivity of Cirrus Bidirectional Reflectance at MODIS Bands to Vertical Inhomogeneity of Ice Crystal Habits and Size Distribution

NASA Technical Reports Server (NTRS)

Yang, P.; Gao, B.-C.; Baum, B. A.; Wiscombe, W.; Hu, Y.; Nasiri, S. L.; Soulen, P. F.; Heymsfield, A. J.; McFarquhar, G. M.; Miloshevich, L. M.

2000-01-01

A common assumption in satellite imager-based cirrus retrieval algorithms is that the radiative properties of a cirrus cloud may be represented by those associated with a specific ice crystal shape (or habit) and a single particle size distribution. However, observations of cirrus clouds have shown that the shapes and sizes of ice crystals may vary substantially with height within the clouds. In this study we investigate the sensitivity of the top-of-atmosphere bidirectional reflectances at two MODIS bands centered at 0.65 micron and 2.11 micron to the cirrus models assumed to be either a single homogeneous layer or three distinct but contiguous, layers. First, we define the single- and three-layer cirrus cloud models with respect to ice crystal habit and size distribution on the basis of in situ replicator data acquired during the First ISCCP Regional Experiment (FIRE-II), held in Kansas during the fall of 1991. Subsequently, fundamental light scattering and radiative transfer theory is employed to determine the single scattering and the bulk radiative properties of the cirrus cloud. Regarding the radiative transfer computations, we present a discrete form of the adding/doubling principle by introducing a direct transmission function, which is computationally straightforward and efficient an improvement over previous methods. For the 0.65 micron band, at which absorption by ice is negligible, there is little difference between the bidirectional reflectances calculated for the one- and three-layer cirrus models, suggesting that the vertical inhomogeneity effect is relatively unimportant. At the 2.11 micron band, the bidirectional reflectances computed for both optically thin (tau = 1) and thick (tau = 10) cirrus clouds show significant differences between the results for the one- and three-layer models. The reflectances computed for the three-layer cirrus model are substantially larger than those computed for the single-layer cirrus. Finally, we find that cloud reflectance is very sensitive to the optical properties of the small crystals that predominate in the top layer of the three-layer cirrus model. It is critical to define the most realistic geometric shape for the small "quasi-spherical" ice crystals in the top layer for obtaining reliable single-scattering parameters and bulk radiative properties of cirrus.

Accuracy Assessment of Aqua-MODIS Aerosol Optical Depth Over Coastal Regions: Importance of Quality Flag and Sea Surface Wind Speed

NASA Technical Reports Server (NTRS)

Anderson, J. C.; Wang, J.; Zeng, J.; Petrenko, M.; Leptoukh, G. G.; Ichoku, C.

2012-01-01

Coastal regions around the globe are a major source for anthropogenic aerosols in the atmosphere, but the underlying surface characteristics are not favorable for the Moderate Resolution Imaging Spectroradiometer (MODIS) algorithms designed for retrieval of aerosols over dark land or open-ocean surfaces. Using data collected from 62 coastal stations worldwide from the Aerosol Robotic Network (AERONET) from approximately 2002-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from MODIS aboard Aqua satellite. It is found that coastal AODs (at 550 nm) characterized respectively by the MODIS Dark Land (hereafter Land) surface algorithm, the Open-Ocean (hereafter Ocean) algorithm, and AERONET all exhibit a log-normal distribution. After filtering by quality flags, the MODIS AODs respectively retrieved from the Land and Ocean algorithms are highly correlated with AERONET (with R(sup 2) is approximately equal to 0.8), but only the Land algorithm AODs fall within the expected error envelope greater than 66% of the time. Furthermore, the MODIS AODs from the Land algorithm, Ocean algorithm, and combined Land and Ocean product show statistically significant discrepancies from their respective counterparts from AERONET in terms of mean, probability density function, and cumulative density function, which suggest a need for future improvement in retrieval algorithms. Without filtering with quality flag, the MODIS Land and Ocean AOD dataset can be degraded by 30-50% in terms of mean bias. Overall, the MODIS Ocean algorithm overestimates the AERONET coastal AOD by 0.021 for AOD less than 0.25 and underestimates it by 0.029 for AOD greater than 0.25. This dichotomy is shown to be related to the ocean surface wind speed and cloud contamination effects on the satellite aerosol retrieval. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) reveals that wind speeds over the global coastal region 25 (with a mean and median value of 2.94 meters per second and 2.66 meters per second, respectively) are often slower than 6 meters per second assumed in the MODIS Ocean algorithm. As a result of high correlation (R(sup 2) greater than 0.98) between the bias in binned MODIS AOD and the corresponding binned wind speed over the coastal sea surface, an empirical scheme for correcting the bias of AOD retrieved from the MODIS Ocean algorithm is formulated and is shown to be effective over the majority of the coastal AERONET stations, and hence can be used in future analysis of AOD trend and MODIS AOD data assimilation.

Microphysical properties and ice particle morphology of cirrus clouds inferred from combined CALIOP-IIR measurements

NASA Astrophysics Data System (ADS)

Saito, M.; Iwabuchi, H.; Yang, P.; Tang, G.; King, M. D.; Sekiguchi, M.

2016-12-01

Cirrus clouds cover about 25% of the globe. Knowledge about the optical and microphysical properties of these clouds [particularly, optical thickness (COT) and effective radius (CER)] is essential to radiative forcing assessment. Previous studies of those properties using satellite remote sensing techniques based on observations by passive and active sensors gave inconsistent retrievals. In particular, COTs from the Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) using the unconstrained method are affected by variable particle morphology, especially the fraction of horizontally oriented plate particles (HPLT), because the method assumes the lidar ratio to be constant, which should have different values for different ice particle shapes. More realistic ice particle morphology improves estimates of the optical and microphysical properties. In this study, we develop an optimal estimation-based algorithm to infer cirrus COT and CER in addition to morphological parameters (e.g., Fraction of HPLT) using the observations made by CALIOP and the Infrared Imaging Radiometer (IIR) on the CALIPSO platform. The assumed ice particle model is a mixture of a few habits with variable HPLT. Ice particle single-scattering properties are computed using state-of-the-art light-scattering computational capabilities. Rigorous estimation of uncertainties associated with surface properties, atmospheric gases and cloud heterogeneity is performed. The results based on the present method show that COTs are quite consistent with the MODIS and CALIOP counterparts, and CERs essentially agree with the IIR operational retrievals. The lidar ratio is calculated from the bulk optical properties based on the inferred parameters. The presentation will focus on latitudinal variations of particle morphology and the lidar ratio on a global scale.

Impact of Multiple Scattering on Longwave Radiative Transfer Involving Clouds

DOE PAGES

Kuo, Chia-Pang; Yang, Ping; Huang, Xianglei; ...

2017-12-13

General circulation models (GCMs) are extensively used to estimate the influence of clouds on the global energy budget and other aspects of climate. Because radiative transfer computations involved in GCMs are costly, it is typical to consider only absorption but not scattering by clouds in longwave (LW) spectral bands. In this study, the flux and heating rate biases due to neglecting the scattering of LW radiation by clouds are quantified by using advanced cloud optical property models, and satellite data from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, Clouds and the Earth's Radiant Energy System (CERES), and Moderatemore » Resolution Imaging Spectrometer (MODIS) merged products (CCCM). From the products, information about the atmosphere and clouds (microphysical and buck optical properties, and top and base heights) is used to simulate fluxes and heating rates. One-year global simulations for 2010 show that the LW scattering decreases top-of-atmosphere (TOA) upward flux and increases surface downward flux by 2.6 and 1.2 W/m 2, respectively, or approximately 10% and 5% of the TOA and surface LW cloud radiative effect, respectively. Regional TOA upward flux biases are as much as 5% of global averaged outgoing longwave radiation (OLR). LW scattering causes approximately 0.018 K/d cooling at the tropopause and about 0.028 K/d heating at the surface. Furthermore, over 40% of the total OLR bias for ice clouds is observed in 350–500 cm -1. Overall, the radiative effects associated with neglecting LW scattering are comparable to the counterpart due to doubling atmospheric CO 2 under clear-sky conditions.« less

Monte Carlo Bayesian Inference on a Statistical Model of Sub-Gridcolumn Moisture Variability using High-Resolution Cloud Observations

NASA Astrophysics Data System (ADS)

Norris, P. M.; da Silva, A. M., Jr.

2016-12-01

Norris and da Silva recently published a method to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation (CDA). The gridcolumn model includes assumed-PDF intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used are MODIS cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. The new approach not only significantly reduces mean and standard deviation biases with respect to the assimilated observables, but also improves the simulated rotational-Ramman scattering cloud optical centroid pressure against independent (non-assimilated) retrievals from the OMI instrument. One obvious difficulty for the method, and other CDA methods, is the lack of information content in passive cloud observables on cloud vertical structure, beyond cloud-top and thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard is helpful, better honoring inversion structures in the background state.

A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors

NASA Astrophysics Data System (ADS)

Sedano, Fernando; Kempeneers, Pieter; Strobl, Peter; Kucera, Jan; Vogt, Peter; Seebach, Lucia; San-Miguel-Ayanz, Jesús

2011-09-01

This study presents a novel cloud masking approach for high resolution remote sensing images in the context of land cover mapping. As an advantage to traditional methods, the approach does not rely on thermal bands and it is applicable to images from most high resolution earth observation remote sensing sensors. The methodology couples pixel-based seed identification and object-based region growing. The seed identification stage relies on pixel value comparison between high resolution images and cloud free composites at lower spatial resolution from almost simultaneously acquired dates. The methodology was tested taking SPOT4-HRVIR, SPOT5-HRG and IRS-LISS III as high resolution images and cloud free MODIS composites as reference images. The selected scenes included a wide range of cloud types and surface features. The resulting cloud masks were evaluated through visual comparison. They were also compared with ad-hoc independently generated cloud masks and with the automatic cloud cover assessment algorithm (ACCA). In general the results showed an agreement in detected clouds higher than 95% for clouds larger than 50 ha. The approach produced consistent results identifying and mapping clouds of different type and size over various land surfaces including natural vegetation, agriculture land, built-up areas, water bodies and snow.

Cloudy Earth

NASA Image and Video Library

2015-05-08

Decades of satellite observations and astronaut photographs show that clouds dominate space-based views of Earth. One study based on nearly a decade of satellite data estimated that about 67 percent of Earth’s surface is typically covered by clouds. This is especially the case over the oceans, where other research shows less than 10 percent of the sky is completely clear of clouds at any one time. Over land, 30 percent of skies are completely cloud free. Earth’s cloudy nature is unmistakable in this global cloud fraction map, based on data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite. While MODIS collects enough data to make a new global map of cloudiness every day, this version of the map shows an average of all of the satellite’s cloud observations between July 2002 and April 2015. Colors range from dark blue (no clouds) to light blue (some clouds) to white (frequent clouds).

Cloud and Aerosol Properties, Precipitable Water, and Profiles of Temperature and Water Vapor from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.; Menzel, W. Paul; Kaufman, Yoram J.; Tanre, Didier; Gao, Bo-Cai; Platnick, Steven; Ackerman, Steven A.; Remer, Lorraine A.; Pincus, Robert; Hubanks, Paul A.

2003-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) is an earth-viewing sensor that flies on the Earth Observing System (EOS) 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 pm with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to en- able 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. In this paper 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.

Evaluation and time series analysis of mountain snow from MODIS and VIIRS fractional snow cover products

NASA Astrophysics Data System (ADS)

Bormann, K.; Rittger, K.; Painter, T. H.

2016-12-01

The continuation of large-scale snow cover records into the future is crucial for monitoring the impacts of global pressures such as climate change and weather variability on the cryosphere. With daily MODIS records since 2000 from a now ageing MODIS constellation (Terra & Aqua) and daily VIIRS records since 2012 from the Suomi-NPP platform, the consistency of information between the two optical sensors must be understood. First, we evaluated snow cover maps derived from both MODIS and VIIRS retrievals with coincident cloud-free Landsat 8 OLI maps across a range of locations. We found that both MODIS and VIIRS snow cover maps show similar errors when evaluated with Landsat OLI retrievals. Preliminary results also show a general agreement in regional snowline between the two sensors that is maintained during the spring snowline retreat where the proportion of mixed pixels is increased. The agreement between sensors supports the future use of VIIRS snow cover maps to continue the long-term record beyond the lifetime of MODIS. Second, we use snowline elevation to quantify large scale snow cover variability and to monitor potential changes in the rain/snow transition zone where climate change pressures may be enhanced. Despite the large inter-annual variability that is often observed in snow metrics, we expect that over the 16-year time series we will see a rise in seasonal elevation of the snowline and consequently an increasing rain/snow transition boundary in mountain environments. These results form the basis for global snowline elevation monitoring using optical remote sensing data and highlight regional differences in snowline elevation dynamics. The long-term variability in observed snowline elevation provides a recent climatology of mountain snowpack across several regions that will likely to be of interest to those interested in climate change impacts in mountain environments. This work will also be of interest to existing users of MODSCAG and VIIRSCAG snow cover products and those working in remote sensing of the mountain snowpack.

Recent Efforts to Improve the Near Real Time Forest Disturbance Monitoring Capabilities of the ForWarn System

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Hargrove, William; Gasser, Gerald

2013-01-01

This presentation discusses the development of anew method for computing NDVI temporal composites from near real time eMODIS data This research is being conducted to improve forest change products used in the ForWarn system for monitoring regional forest disturbances in the United States. ForWarn provides nation-wide NDVI-based forest disturbance detection products that are refreshed every 8 days. Current eMODIS and historical MOD13 24 day NDVI data are used to compute the disturbance detection products. The eMODIS 24 day NDVI data re-aggregated from 7 day NDVI products. The 24 day eMODIS NDVIs are generally cloud free, but do not necessarily use the freshest quality data. To shorten the disturbance detection time, a method has been developed that performs adaptive length/maximum value compositing of eMODIS NDVI, along with cloud and shadow "noise" mitigation. Tests indicate that this method can reduce detection rates by 8-16 days for known recent disturbance events, depending on the cloud frequencies and disturbance type. The noise mitigation in these tests, though imperfect, helped to improve quality of the resulting NDVI and forest change products.

Direct Radiative Effect of Aerosols Based on PARASOL and OMI Satellite Observations

NASA Technical Reports Server (NTRS)

Lacagnina, Carlo; Hasekamp, Otto P.; Torres, Omar

2017-01-01

Accurate portrayal of the aerosol characteristics is crucial to determine aerosol contribution to the Earth's radiation budget. We employ novel satellite retrievals to make a new measurement-based estimate of the shortwave direct radiative effect of aerosols (DREA), both over land and ocean. Global satellite measurements of aerosol optical depth, single-scattering albedo (SSA), and phase function from PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) are used in synergy with OMI (Ozone Monitoring Instrument) SSA. Aerosol information is combined with land-surface bidirectional reflectance distribution function and cloud characteristics from MODIS (Moderate Resolution Imaging Spectroradiometer) satellite products. Eventual gaps in observations are filled with the state-of-the-art global aerosol model ECHAM5-HAM2. It is found that our estimate of DREA is largely insensitive to model choice. Radiative transfer calculations show that DREA at top-of-atmosphere is -4.6 +/- 1.5 W/sq m for cloud-free and -2.1 +/- 0.7 W/sq m for all-sky conditions, during year 2006. These fluxes are consistent with, albeit generally less negative over ocean than, former assessments. Unlike previous studies, our estimate is constrained by retrievals of global coverage SSA, which may justify different DREA values. Remarkable consistency is found in comparison with DREA based on CERES (Clouds and the Earth's Radiant Energy System) and MODIS observations.

Biogeography, Cloud Base Heights and Cloud Immersion in Tropical Montane Cloud Forests

NASA Astrophysics Data System (ADS)

Welch, R. M.; Asefi, S.; Zeng, J.; Nair, U. S.; Lawton, R. O.; Ray, D. K.; Han, Q.; Manoharan, V. S.

2007-05-01

Tropical Montane Cloud Forests (TMCFs) are ecosystems characterized by frequent and prolonged immersion within orographic clouds. TMCFs often lie at the core of the biological hotspots, areas of high biodiversity, whose conservation is necessary to ensure the preservation of a significant amount of the plant and animal species in the world. TMCFs support islands of endemism dependent on cloud water interception that are extremely susceptible to environmental and climatic changes at regional or global scales. Due to the ecological and hydrological importance of TMCFs it is important to understand the biogeographical distribution of these ecosystems. The best current list of TMCFs is a global atlas compiled by the United Nations Environmental Program (UNEP). However, this list is incomplete, and it does not provide information on cloud immersion, which is the defining characteristic of TMCFs and sorely needed for ecological and hydrological studies. The present study utilizes MODIS satellite data both to determine orographic cloud base heights and then to quantify cloud immersion statistics over TMCFs. Results are validated from surface measurements over Northern Costa Rica for the month of March 2003. Cloud base heights are retrieved with approximately 80m accuracy, as determined at Monteverde, Costa Rica. Cloud immersion derived from MODIS data is also compared to an independent cloud immersion dataset created using a combination of GOES satellite data and RAMS model simulations. Comparison against known locations of cloud forests in Northern Costa Rica shows that the MODIS-derived cloud immersion maps successfully identify these cloud forest locations, including those not included in the UNEP data set. Results also will be shown for cloud immersion in Hawaii. The procedure appears to be ready for global mapping.

Single-footprint retrievals of temperature, water vapor and cloud properties from AIRS

NASA Astrophysics Data System (ADS)

Irion, Fredrick W.; Kahn, Brian H.; Schreier, Mathias M.; Fetzer, Eric J.; Fishbein, Evan; Fu, Dejian; Kalmus, Peter; Wilson, R. Chris; Wong, Sun; Yue, Qing

2018-02-01

Single-footprint Atmospheric Infrared Sounder spectra are used in an optimal estimation-based algorithm (AIRS-OE) for simultaneous retrieval of atmospheric temperature, water vapor, surface temperature, cloud-top temperature, effective cloud optical depth and effective cloud particle radius. In a departure from currently operational AIRS retrievals (AIRS V6), cloud scattering and absorption are in the radiative transfer forward model and AIRS single-footprint thermal infrared data are used directly rather than cloud-cleared spectra (which are calculated using nine adjacent AIRS infrared footprints). Coincident MODIS cloud data are used for cloud a priori data. Using single-footprint spectra improves the horizontal resolution of the AIRS retrieval from ˜ 45 to ˜ 13.5 km at nadir, but as microwave data are not used, the retrieval is not made at altitudes below thick clouds. An outline of the AIRS-OE retrieval procedure and information content analysis is presented. Initial comparisons of AIRS-OE to AIRS V6 results show increased horizontal detail in the water vapor and relative humidity fields in the free troposphere above the clouds. Initial comparisons of temperature, water vapor and relative humidity profiles with coincident radiosondes show good agreement. Future improvements to the retrieval algorithm, and to the forward model in particular, are discussed.

Impact of Assimilated and Interactive Aerosol on Tropical Cyclogenesis

NASA Technical Reports Server (NTRS)

Reale, O.; Lau, K. M.; daSilva, A.; Matsui, T.

2014-01-01

This article investigates the impact 3 of Saharan dust on the development of tropical cyclones in the Atlantic. A global data assimilation and forecast system, the NASA GEOS-5, is used to assimilate all satellite and conventional data sets used operationally for numerical weather prediction. In addition, this new GEOS-5 version includes assimilation of aerosol optical depth from the Moderate Resolution Imaging Spectroradiometer (MODIS). The analysis so obtained comprises atmospheric quantities and a realistic 3-d aerosol and cloud distribution, consistent with the meteorology and validated against Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat data. These improved analyses are used to initialize GEOS-5 forecasts, explicitly accounting for aerosol direct radiative effects and their impact on the atmospheric dynamics. Parallel simulations with/without aerosol radiative effects show that effects of dust on static stability increase with time, becoming highly significant after day 5 and producing an environment less favorable to tropical cyclogenesis.

Shortwave direct radiative effects of above cloud aerosols over global oceans derived from eight years of CALIOP and MODIS observations

NASA Astrophysics Data System (ADS)

Zhang, Z.; Meyer, K.; Yu, H.; Platnick, S.; Colarco, P.; Liu, Z.; Oreopoulos, L.

2015-09-01

In this paper, we studied the frequency of occurrence and shortwave direct radiative effects (DRE) of above-cloud aerosols (ACAs) over global oceans using eight years of collocated CALIOP and MODIS observations. Similar to previous work, we found high ACA occurrence in four regions: Southeast (SE) Atlantic region where ACAs are mostly light-absorbing aerosols, i.e., smoke and polluted dust according to CALIOP classification, originating from biomass burning over African Savanna; Tropical Northeast Atlantic and Arabian Sea where ACAs are predominantly windblown dust from the Sahara and Arabian desert, respectively; and Northwest Pacific where ACAs are mostly transported smoke and polluted dusts from Asian. From radiative transfer simulations based on CALIOP-MODIS observations and a set of the preselected aerosol optical models, we found the DREs of ACAs at the top of atmosphere (TOA) to be positive (i.e., warming) in the SE Atlantic and NW Pacific regions, but negative (i.e., cooling) in TNE Atlantic and Arabian Sea. The cancellation of positive and negative regional DREs results in a global ocean annual mean diurnally averaged cloudy-sky DRE of 0.015 W m-2 (range of -0.03 to 0.06 W m-2) at TOA. The DREs at surface and within atmosphere are -0.15 W m-2 (range of -0.09 to -0.21 W m-2), and 0.17 W m-2 (range of 0.11 to 0.24 W m-2), respectively. The regional and seasonal mean DREs are much stronger. For example, in the SE Atlantic region the JJA (July ~ August) seasonal mean cloudy-sky DRE is about 0.7 W m-2 (range of 0.2 to 1.2 W m-2) at TOA. The uncertainty in our DRE computations is mainly cause by the uncertainties in the aerosol optical properties, in particular aerosol absorption, and uncertainties in the CALIOP operational aerosol optical thickness retrieval. In situ and remotely sensed measurements of ACA from future field campaigns and satellite missions, and improved lidar retrieval algorithm, in particular vertical feature masking, would help reduce the uncertainty.

A new method for assessing surface solar irradiance: Heliosat-4

NASA Astrophysics Data System (ADS)

Qu, Z.; Oumbe, A.; Blanc, P.; Lefèvre, M.; Wald, L.; Schroedter-Homscheidt, M.; Gesell, G.

2012-04-01

Downwelling shortwave irradiance at surface (SSI) is more and more often assessed by means of satellite-derived estimates of optical properties of the atmosphere. Performances are judged satisfactory for the time being but there is an increasing need for the assessment of the direct and diffuse components of the SSI. MINES ParisTech and the German Aerospace Center (DLR) are currently developing the Heliosat-4 method to assess the SSI and its components in a more accurate way than current practices. This method is composed by two parts: a clear sky module based on the radiative transfer model libRadtran, and a cloud-ground module using two-stream and delta-Eddington approximations for clouds and a database of ground albedo. Advanced products derived from geostationary satellites and recent Earth Observation missions are the inputs of the Heliosat-4 method. Such products are: cloud optical depth, cloud phase, cloud type and cloud coverage from APOLLO of DLR, aerosol optical depth, aerosol type, water vapor in clear-sky, ozone from MACC products (FP7), and ground albedo from MODIS of NASA. In this communication, we briefly present Heliosat-4 and focus on its performances. The results of Heliosat-4 for the period 2004-2010 will be compared to the measurements made in five stations within the Baseline Surface Radiation Network. Extensive statistic analysis as well as case studies are performed in order to better understand Heliosat-4 and have an in-depth view of the performance of Heliosat-4, to understand its advantages comparing to existing methods and to identify its defaults for future improvements. The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under Grant Agreement no. 218793 (MACC project) and no. 283576 (MACC-II project).

Smoke over haze: Comparative analysis of satellite, surface radiometer, and airborne in situ measurements of aerosol optical properties and radiative forcing over the eastern United States

NASA Astrophysics Data System (ADS)

Vant-Hull, Brian; Li, Zhanqing; Taubman, Brett F.; Levy, Robert; Marufu, Lackson; Chang, Fu-Lung; Doddridge, Bruce G.; Dickerson, Russell R.

2005-05-01

In July 2002 Canadian forest fires produced a major smoke episode that blanketed the east coast of the United States. Properties of the smoke aerosol were measured in situ from aircraft, complementing operational Aerosol Robotic Network (AERONET), and Moderate Resolution Imaging Spectroradiometer (MODIS) remotely sensed aerosol retrievals. This study compares single scattering albedo and phase function derived from the in situ measurements and AERONET retrievals in order to evaluate their consistency for application to satellite retrievals of optical depth and radiative forcing. These optical properties were combined with MODIS reflectance observations to calculate optical depth. The use of AERONET optical properties yielded optical depths 2-16% lower than those directly measured by AERONET. The use of in situ-derived optical properties resulted in optical depths 22-43% higher than AERONET measurements. These higher optical depths are attributed primarily to the higher absorption measured in situ, which is roughly twice that retrieved by AERONET. The resulting satellite retrieved optical depths were in turn used to calculate integrated radiative forcing at both the surface and top of atmosphere. Comparisons to surface (Surface Radiation Budget Network (SURFRAD) and ISIS) and to satellite (Clouds and Earth Radiant Energy System CERES) broadband radiometer measurements demonstrate that the use of optical properties derived from the aircraft measurements provided a better broadband forcing estimate (21% error) than those derived from AERONET (33% error). Thus AERONET-derived optical properties produced better fits to optical depth measurements, while in situ properties resulted in better fits to forcing measurements. These apparent inconsistencies underline the significant challenges facing the aerosol community in achieving column closure between narrow and broadband measurements and calculations.

The Role of Aerosols in Cloud Growth, Suppression, and Precipitation: Yoram Kaufman and his Contributions

NASA Technical Reports Server (NTRS)

King, Michael D.

2006-01-01

Aerosol particles are produced in the earth's atmosphere through both natural as well as manmade processes, and contribute profoundly to the (i) formation and characteristics of clouds, (ii) lifetime of clouds, (iii) optical and microphysical properties of clouds, (iv) human health through effects on air quality and the size of particulates as well as vectors for transport of pathogens, (v) climate response and feedbacks, (vi) precipitation, and (vii) harmful algal blooms. Without aerosol particles in the Earth's atmosphere, there would be no fogs, no clouds, ,no mists, and probably no rain, as noted as far back as 1880 by Scottish physicist John Aitken. With the modern development of instrumentation, both groundbased, airborne, and satellite-based, much progress has been made in linkng phenomena and processes together, and putting regional air quality characteristics and hypothesized cloud response into closer scrutiny and linkages. In h s presentation I will summarize the wide ranging contributions that Yoram Kaufman has made in ground-based (AERONET), aircraft field campaigns (such as SCAR-B and TARFOX), and, especially, satellite remote sensing (Landsat, MODIS, POLDER) to shed new light on this broad ranging and interdisciplinary field of cloud-aerosol-precipitation interactions.

Applications for Near-Real Time Satellite Cloud and Radiation Products

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Palikonda, Rabindra; Chee, Thad L.; Bedka, Kristopher M.; Smith, W.; Ayers, Jeffrey K.; Benjamin, Stanley; Chang, F.-L.; Nguyen, Louis; Norris, Peter;

Reconstruction of MODIS total suspended matter time series maps by DINEOF and validation with autonomous platform data

NASA Astrophysics Data System (ADS)

Nechad, Bouchra; Alvera-Azcaràte, Aida; Ruddick, Kevin; Greenwood, Naomi

2011-08-01

In situ measurements of total suspended matter (TSM) over the period 2003-2006, collected with two autonomous platforms from the Centre for Environment, Fisheries and Aquatic Sciences (Cefas) measuring the optical backscatter (OBS) in the southern North Sea, are used to assess the accuracy of TSM time series extracted from satellite data. Since there are gaps in the remote sensing (RS) data, due mainly to cloud cover, the Data Interpolating Empirical Orthogonal Functions (DINEOF) is used to fill in the TSM time series and build a continuous daily "recoloured" dataset. The RS datasets consist of TSM maps derived from MODIS imagery using the bio-optical model of Nechad et al. (Rem Sens Environ 114: 854-866, 2010). In this study, the DINEOF time series are compared to the in situ OBS measured in moderately to very turbid waters respectively in West Gabbard and Warp Anchorage, in the southern North Sea. The discrepancies between instantaneous RS, DINEOF-filled RS data and Cefas data are analysed in terms of TSM algorithm uncertainties, space-time variability and DINEOF reconstruction uncertainty.

MODIS Observation of Aerosols over Southern Africa During SAFARI 2000: Data, Validation, and Estimation of Aerosol Radiative Forcing

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Kaufman, Yoram; Remer, Lorraine; Chu, D. Allen; Mattoo, Shana; Tanre, Didier; Levy, Robert; Li, Rong-Rong; Kleidman, Richard; Lau, William K. M. (Technical Monitor)

2001-01-01

Aerosol properties, including optical thickness and size parameters, are retrieved operationally from the MODIS sensor onboard the Terra satellite launched on 18 December 1999. The predominant aerosol type over the Southern African region is smoke, which is generated from biomass burning on land and transported over the southern Atlantic Ocean. The SAFARI-2000 period experienced smoke aerosol emissions from the regular biomass burning activities as well as from the prescribed burns administered on the auspices of the experiment. The MODIS Aerosol Science Team (MAST) formulates and implements strategies for the retrieval of aerosol products from MODIS, as well as for validating and analyzing them in order to estimate aerosol effects in the radiative forcing of climate as accurately as possible. These activities are carried out not only from a global perspective, but also with a focus on specific regions identified as having interesting characteristics, such as the biomass burning phenomenon in southern Africa and the associated smoke aerosol, particulate, and trace gas emissions. Indeed, the SAFARI-2000 aerosol measurements from the ground and from aircraft, along with MODIS, provide excellent data sources for a more intensive validation and a closer study of the aerosol characteristics over Southern Africa. The SAFARI-2000 ground-based measurements of aerosol optical thickness (AOT) from both the automatic Aerosol Robotic Network (AERONET) and handheld Sun photometers have been used to validate MODIS retrievals, based on a sophisticated spatio-temporal technique. The average global monthly distribution of aerosol from MODIS has been combined with other data to calculate the southern African aerosol daily averaged (24 hr) radiative forcing over the ocean for September 2000. It is estimated that on the average, for cloud free conditions over an area of 9 million square kin, this predominantly smoke aerosol exerts a forcing of -30 W/square m C lose to the terrestrial surface and -10 W/square m at the top of the atmosphere (TOA). While cooling the surface and Earth system, the difference of 20 W/square m is energy that heats the atmosphere.

Some Technical Aspects of a CALIOP and MODIS Data Analysis that Examines Near-Cloud Aerosol Properties as a Function of Cloud Fraction

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Yang, Weidong; Marshak, Alexander

2016-01-01

CALIOP shows stronger near-cloud changes in aerosol properties at higher cloud fractions. Cloud fraction variations explain a third of near-cloud changes in overall aerosol statistics. Cloud fraction and aerosol particle size distribution have a complex relationship.

Seasonal Surface Spectral Emissivity Derived from Terra MODIS Data

NASA Technical Reports Server (NTRS)

Sun-Mack, Sunny; Chen, Yan; Minnis, Patrick; Young, DavidF.; Smith, William J., Jr.

2004-01-01

The CERES (Clouds and the Earth's Radiant Energy System) Project is measuring broadband shortwave and longwave radiances and deriving cloud properties form various images to produce a combined global radiation and cloud property data set. In this paper, simultaneous data from Terra MODIS (Moderate Resolution Imaging Spectroradiometer) taken at 3.7, 8.5, 11.0, and 12.0 m are used to derive the skin temperature and the surface emissivities at the same wavelengths. The methodology uses separate measurements of clear sky temperature in each channel determined by scene classification during the daytime and at night. The relationships between the various channels at night are used during the day when solar reflectance affects the 3.7- m radiances. A set of simultaneous equations is then solved to derive the emissivities. Global monthly emissivity maps are derived from Terra MODIS data while numerical weather analyses provide soundings for correcting the observed radiances for atmospheric absorption. These maps are used by CERES and other cloud retrieval algorithms.

Multi-sensor quantification of aerosol-induced variability in warm clouds over eastern China

NASA Astrophysics Data System (ADS)

Wang, Fu; Guo, Jianping; Zhang, Jiahua; Huang, Jingfeng; Min, Min; Chen, Tianmeng; Liu, Huan; Deng, Minjun; Li, Xiaowen

2015-07-01

Aerosol-cloud (AC) interactions remain uncharacterized due to difficulties in obtaining accurate aerosol and cloud observations. In this study, we quantified the aerosol indirect effects (AIE) on warm clouds over Eastern China based on near-simultaneous retrievals from MODIS/AQUA, CALIOP/CALIPSO, and CPR/CLOUDSAT between June 2006 and December 2010. The seasonality of aerosols from ground-based PM10 (aerosol particles with diameter of 10 μm or less) significantly differed from that estimated using MODIS aerosol optical depth (AOD). This result was supported by the lower level frequency profile of aerosol occurrence from CALIOP, indicative of the significant role of CALIOP in the AC interaction. To focus on warm clouds, cloud layers with base (top) altitudes above 7 (10) km were excluded. The combination of CALIOP and CPR was applied to determine the exact position of warm clouds relative to aerosols out of the following six scenarios in terms of AC mixing states: 1) aerosol only (AO); 2) cloud only (CO); 3) single aerosol layer-single cloud layer (SASC); 4) single aerosol layer-double cloud layers (SADC); 5) double aerosol layers - single cloud layer (DASC); and 6) others. The cases with vertical distance between aerosol and cloud layer less (more) than 100 m (700 m) were marked mixed (separated), and the rest as uncertain. Results showed that only 8.95% (7.53%) belonged to the mixed (separated and uncertain) state among all of the collocated AC overlapping cases, including SASC, SADC, and DASC. Under mixed conditions, the cloud droplet effective radius (CDR) decreased with increasing AOD at moderate aerosol loading (AOD<0.4), and then became saturated at an AOD of around 0.5, followed by an increase in CDR with increasing AOD, known as boomerang shape. Under separated conditions, no apparent changes in CDR with AOD were observed. We categorized the AC dataset into summer- and winter-season subsets to determine how the boomerang shape varied with season. The response of CDR to AOD in summer exhibited similar but much more deepened boomerang shape, as compared with the all year round case. In contrast, CDR in winter did not follow the boomerang shape for its continued decreasing with increasing AOD, even after the saturation zone (AOD around 0.5) of a cloud droplet.

Generating Land Surface Reflectance for the New Generation of Geostationary Satellite Sensors with the MAIAC Algorithm

NASA Astrophysics Data System (ADS)

Wang, W.; Wang, Y.; Hashimoto, H.; Li, S.; Takenaka, H.; Higuchi, A.; Lyapustin, A.; Nemani, R. R.

2017-12-01

The latest generation of geostationary satellite sensors, including the GOES-16/ABI and the Himawari 8/AHI, provide exciting capability to monitor land surface at very high temporal resolutions (5-15 minute intervals) and with spatial and spectral characteristics that mimic the Earth Observing System flagship MODIS. However, geostationary data feature changing sun angles at constant view geometry, which is almost reciprocal to sun-synchronous observations. Such a challenge needs to be carefully addressed before one can exploit the full potential of the new sources of data. Here we take on this challenge with Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, recently developed for accurate and globally robust applications like the MODIS Collection 6 re-processing. MAIAC first grids the top-of-atmosphere measurements to a fixed grid so that the spectral and physical signatures of each grid cell are stacked ("remembered") over time and used to dramatically improve cloud/shadow/snow detection, which is by far the dominant error source in the remote sensing. It also exploits the changing sun-view geometry of the geostationary sensor to characterize surface BRDF with augmented angular resolution for accurate aerosol retrievals and atmospheric correction. The high temporal resolutions of the geostationary data indeed make the BRDF retrieval much simpler and more robust as compared with sun-synchronous sensors such as MODIS. As a prototype test for the geostationary-data processing pipeline on NASA Earth Exchange (GEONEX), we apply MAIAC to process 18 months of data from Himawari 8/AHI over Australia. We generate a suite of test results, including the input TOA reflectance and the output cloud mask, aerosol optical depth (AOD), and the atmospherically-corrected surface reflectance for a variety of geographic locations, terrain, and land cover types. Comparison with MODIS data indicates a general agreement between the retrieved surface reflectance products. Furthermore, the geostationary results satisfactorily capture the movement of clouds and variations in atmospheric dust/aerosol concentrations, suggesting that high quality land surface and vegetation datasets from the advanced geostationary sensors can help complement and improve the corresponding EOS products.

The impact of horizontal heterogeneities, cloud fraction, and cloud dynamics on warm cloud effective radii and liquid water path from CERES-like Aqua MODIS retrievals

NASA Astrophysics Data System (ADS)

Painemal, D.; Minnis, P.; Sun-Mack, S.

2013-05-01

The impact of horizontal heterogeneities, liquid water path (LWP from AMSR-E), and cloud fraction (CF) on MODIS cloud effective radius (re), retrieved from the 2.1 μm (re2.1) and 3.8 μm (re3.8) channels, is investigated for warm clouds over the southeast Pacific. Values of re retrieved using the CERES Edition 4 algorithms are averaged at the CERES footprint resolution (~ 20 km), while heterogeneities (Hσ) are calculated as the ratio between the standard deviation and mean 0.64 μm reflectance. The value of re2.1 strongly depends on CF, with magnitudes up to 5 μm larger than those for overcast scenes, whereas re3.8 remains insensitive to CF. For cloudy scenes, both re2.1 and re3.8 increase with Hσ for any given AMSR-E LWP, but re2.1 changes more than for re3.8. Additionally, re3.8 - re2.1 differences are positive (< 1 μm) for homogeneous scenes (Hσ < 0.2) and LWP > 50 g m-2, and negative (up to -4 μm) for larger Hσ. Thus, re3.8 - re2.1 differences are more likely to reflect biases associated with cloud heterogeneities rather than information about the cloud vertical structure. The consequences for MODIS LWP are also discussed.

CHIMAERA System for Cloud Retrievals v 6.0.85

NASA Technical Reports Server (NTRS)

Wind, Galina; Platnick, Steven; Meyer, Kerry; Amarasinghe, Nandana; Marchant, Benjamin; Arnold, Tom; King, Michael D.

2015-01-01

Organizers of the MODIS-VIIRS Science Team Meeting, held May 18-22, 2015 in Silver Spring, MD plan to post the presentations and posters to the NASA MODIS website: http:modis.gsfc.nasa.govsci_teammeetings201505index.php. The MODIS Science Team Meeting is held twice a year, so that the members of the science team may assemble and discuss data they have collected, ideas they have formed, and future issues that apply to the MODIS Mission.

Satellite Ocean Biology: Past, Present, Future

NASA Technical Reports Server (NTRS)

McClain, Charles R.

2012-01-01

Since 1978 when the first satellite ocean color proof-of-concept sensor, the Nimbus-7 Coastal Zone Color Scanner, was launched, much progress has been made in refining the basic measurement concept and expanding the research applications of global satellite time series of biological and optical properties such as chlorophyll-a concentrations. The seminar will review the fundamentals of satellite ocean color measurements (sensor design considerations, on-orbit calibration, atmospheric corrections, and bio-optical algorithms), scientific results from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate resolution Imaging Spectroradiometer (MODIS) missions, and the goals of future NASA missions such as PACE, the Aerosol, Cloud, Ecology (ACE), and Geostationary Coastal and Air Pollution Events (GeoCAPE) missions.

Global variability of cloud condensation nuclei concentrations

NASA Astrophysics Data System (ADS)

Makkonen, Risto; Krüger, Olaf

2017-04-01

Atmospheric aerosols can influence cloud optical and dynamical processes by acting as cloud condensation nuclei (CCN). Globally, these indirect aerosol effects are significant to the radiative budget as well as a source of high uncertainty in anthropogenic radiative forcing. While historically many global climate models have fixed CCN concentrations to a certain level, most state-of-the-art models calculate aerosol-cloud interactions with sophisticated methodologies based on interactively simulated aerosol size distributions. However, due to scarcity of atmospheric observations simulated global CCN concentrations remain poorly constrained. Here we assess global CCN variability with a climate model, and attribute potential trends during 2000-2010 to changes in emissions and meteorological fields. Here we have used ECHAM5.5-HAM2 with model M7 microphysical aerosol model. The model has been upgraded with a secondary organic aerosol (SOA) scheme including ELVOCs. Dust and sea salt emissions are calculated online, based on wind speed and hydrology. Each experiment is 11 years, analysed after a 6-month spin-up period. The MODIS CCN product (Terra platform) is used to evaluate model performance throughout 2000-2010. While optical remote observation of CCN column includes several deficiencies, the products serves as a proxy for changes during the simulation period. In our analysis we utilize the observed and simulated vertical column integrated CCN concentration, and limit our analysis only over marine regions. Simulated annual CCN column densities reach 2ṡ108 cm-2 near strong source regions in central Africa, Arabian Sea, Bay of Bengal and China sea. The spatial concentration gradient in CCN(0.2%) is steep, and column densities drop to <50% a few hundred kilometers away from the coasts. While the spatial distribution of CCN at 0.2% supersaturation is closer to that of MODIS proxy, as opposed to 1.0% supersaturation, the overall column integrated CCN are too low. Still, we can compare the relative response of CCN to emission and meteorological variability. Most evident pattern of high temporal correlation is found over North Atlantic ocean, extending throughout Europe and up to Gulf of Mexico. All of these regions show a generally decreasing trend throughout the decade in control simulations and MODIS CCN, and the simulations including the emission trends clearly improve the simulations with climatological emissions. In regions where the observed intra-annual cycle correlates well with sea-spray emissions, the long-term annual correlation usually remains poor. This could indicate that the model is unable to capture the natural variability in marine aerosol emissions.

Unveiling aerosol-cloud interactions - Part 1: Cloud contamination in satellite products enhances the aerosol indirect forcing estimate

NASA Astrophysics Data System (ADS)

Christensen, Matthew W.; Neubauer, David; Poulsen, Caroline A.; Thomas, Gareth E.; McGarragh, Gregory R.; Povey, Adam C.; Proud, Simon R.; Grainger, Roy G.

2017-11-01

Increased concentrations of aerosol can enhance the albedo of warm low-level cloud. Accurately quantifying this relationship from space is challenging due in part to contamination of aerosol statistics near clouds. Aerosol retrievals near clouds can be influenced by stray cloud particles in areas assumed to be cloud-free, particle swelling by humidification, shadows and enhanced scattering into the aerosol field from (3-D radiative transfer) clouds. To screen for this contamination we have developed a new cloud-aerosol pairing algorithm (CAPA) to link cloud observations to the nearest aerosol retrieval within the satellite image. The distance between each aerosol retrieval and nearest cloud is also computed in CAPA. Results from two independent satellite imagers, the Advanced Along-Track Scanning Radiometer (AATSR) and Moderate Resolution Imaging Spectroradiometer (MODIS), show a marked reduction in the strength of the intrinsic aerosol indirect radiative forcing when selecting aerosol pairs that are located farther away from the clouds (-0.28±0.26 W m-2) compared to those including pairs that are within 15 km of the nearest cloud (-0.49±0.18 W m-2). The larger aerosol optical depths in closer proximity to cloud artificially enhance the relationship between aerosol-loading, cloud albedo, and cloud fraction. These results suggest that previous satellite-based radiative forcing estimates represented in key climate reports may be exaggerated due to the inclusion of retrieval artefacts in the aerosol located near clouds.

A Sample of What We Have Learned from A-Train Cloud Measurements

NASA Technical Reports Server (NTRS)

Joiner, Joanna; Vasilkov, Alexander; Ziemke, Jerry; Chandra, Sushil; Spurr, Robert; Bhartia, P. K.; Krotkov, Nick; Sneep, Maarten; Menzel, Paul; Platnick, Steve;

The Plane-parallel Albedo Bias of Liquid Clouds from MODIS Observations

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Cahalan, Robert F.; Platnick, Steven

2007-01-01

In our most advanced modeling tools for climate change prediction, namely General Circulation Models (GCMs), the schemes used to calculate the budget of solar and thermal radiation commonly assume that clouds are horizontally homogeneous at scales as large as a few hundred kilometers. However, this assumption, used for convenience, computational speed, and lack of knowledge on cloud small scale variability, leads to erroneous estimates of the radiation budget. This paper provides a global picture of the solar radiation errors at scales of approximately 100 km due to warm (liquid phase) clouds only. To achieve this, we use cloud retrievals from the instrument MODIS on the Terra and Aqua satellites, along with atmospheric and surface information, as input into a GCM-style radiative transfer algorithm. Since the MODIS product contains information on cloud variability below 100 km we can run the radiation algorithm both for the variable and the (assumed) homogeneous clouds. The difference between these calculations for reflected or transmitted solar radiation constitutes the bias that GCMs would commit if they were able to perfectly predict the properties of warm clouds, but then assumed they were homogeneous for radiation calculations. We find that the global average of this bias is approx.2-3 times larger in terms of energy than the additional amount of thermal energy that would be trapped if we were to double carbon dioxide from current concentrations. We should therefore make a greater effort to predict horizontal cloud variability in GCMs and account for its effects in radiation calculations.

Investigating the influence of volcanic sulfate aerosol on cloud properties Along A-Train tracks

NASA Astrophysics Data System (ADS)

Mace, G. G.

2017-12-01

Marine boundary layer (MBL) clouds are central actors in the climate system given their extensive coverage on the Earth's surface, their 1-way influence on the radiative balance (cooling), and their intimate coupling between air motions, anthropogenic and natural aerosol sources, and processes within the upper ocean mixed layer. Knowledge of how MBL shallow cumulus clouds respond to changes in aerosol is central to understanding how MBL clouds modulate the climate system. A frequent approach to investigating how sulfate aerosol influences MBL clouds has been to examine sulfate plumes extending downstream of active island volcanoes. This approach is challenging due to modification of the air motions in the plumes downstream of islands and due to the tendency of most researchers to examine only level-2 retrievals ignoring the actual data collected by sensors such as MODIS. Past studies have concluded that sulfate aerosols have large effects consistent with the 1st aerosol indirect effect (AIE). We reason that if such effects are as large as suggested in level-2 retrievals then evidence should also be present in the raw MODIS reflectance data as well as other data sources. In this paper we will build on our recently published work where we tested that hypothesis from data collected near Mount Kilauea during a 3-year period. Separating data into aerosol optical depth (A) quartiles, we found little support for a large 1st AIE response. We did find an unambiguous increase in sub 1km-scale cloud fraction with A. This increase in sub 1 km cloud fraction was entirely consistent with increased reflectance with increasing A that is used, via the level 2 retrievals, to argue for a large AIE response of MBL clouds. While the 1-km pixels became unambiguously brighter, that brightening was due to increased sub 1 km cloud fraction and not necessarily due to changes in pixel-level cloud microphysics. We also found that MBL cloud top heights increase as do surface wind speeds as aerosol increases while the radar reflectivity from CloudSat does not change implying that increased aerosols may have caused invigoration of the MBL clouds with little effect on precipitation. We have since expanded upon this initial analysis by exmaining data near other volcanic islands. These expanded results support our initial findings.

The Global Influence of Cloud Optical Thickness on Terrestrial Carbon Uptake

NASA Astrophysics Data System (ADS)

Zhu, P.; Cheng, S. J.; Keppel-Aleks, G.; Butterfield, Z.; Steiner, A. L.

2016-12-01

Clouds play a critical role in regulating Earth's climate. One important way is by changing the type and intensity of solar radiation reaching the Earth's surface, which impacts plant photosynthesis. Specifically, the presence of clouds modifies photosynthesis rates by influencing the amount of diffuse radiation as well as the spectral distribution of solar radiation. Satellite-derived cloud optical thickness (COT) may provide the observational constraint necessary to assess the role of clouds on ecosystems and terrestrial carbon uptake across the globe. Previous studies using ground-based observations at individual sites suggest that below a COT of 7, there is a greater increase in light use efficiency than at higher COT values, providing evidence for higher carbon uptake rates than expected given the reduction in radiation by clouds. However, the strength of the COT-terrestrial carbon uptake correlation across the globe remains unknown. In this study, we investigate the influence of COT on terrestrial carbon uptake on a global scale, which may provide insights into cloud conditions favorable for plant photosynthesis and improve our estimates of the land carbon sink. Global satellite-derived MODIS data show that tropical and subtropical regions tend to have COT values around or below the threshold during growing seasons. We find weak correlations between COT and GPP with Fluxnet MTE global GPP data, which may be due to the uncertainty of upscaling GPP from individual site measurements. Analysis with solar-induced fluorescence (SIF) as a proxy for GPP is also evaluated. Overall, this work constructs a global picture of the role of COT on terrestrial carbon uptake, including its temporal and spatial variations.

TERRA/MODIS Data Products and Data Management at the GES-DAAC

NASA Astrophysics Data System (ADS)

Sharma, A. K.; Ahmad, S.; Eaton, P.; Koziana, J.; Leptoukh, G.; Ouzounov, D.; Savtchenko, A.; Serafino, G.; Sikder, M.; Zhou, B.

2001-05-01

Since February 2000, the Earth Sciences Distributed Active Archive Center (GES-DAAC) at the NASA/Goddard Space Flight Center has been successfully ingesting, processing, archiving, and distributing the Moderate Resolution Imaging Spectroradiometer (MODIS) data. MODIS is the key instrument aboard the Terra satellite, viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 channels in the visible and infrared spectral bands (0.4 to 14.4 microns). Higher resolution (250m, 500m, and 1km pixel) data are improving our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere and will play a vital role in the future development of validated, global, interactive Earth-system models. MODIS calibrated and uncalibrated radiances, and geolocation products were released to the public in April 2000, and a suite of oceans products and an entire suite of atmospheric products were released by early January 2001. The suite of ocean products is grouped into three categories Ocean Color, SST and Primary Productivity. The suite of atmospheric products includes Aerosol, Total Precipitable Water, Cloud Optical and Physical properties, Atmospheric Profiles and Cloud Mask. The MODIS Data Support Team (MDST) at the GES-DAAC has been providing support for enabling basic scientific research and assistance in accessing the scientific data and information to the Earth Science User Community. Support is also provided for data formats (HDF-EOS), information on visualization tools, documentation for data products, information on the scientific content of products and metadata. Visit the MDST website at http://daac.gsfc.nasa.gov/CAMPAIGN_DOCS/MODIS/index.html The task to process archive and distribute enormous volumes of MODIS data to users (more than 0.5 TB a day) has led to the development of an unique world wide web based GES DAAC Search and Order system http://acdisx.gsfc.nasa.gov/data/, data handling software and tools, as well as a FTP site that contains sample of browse images and MODIS data products. This paper is intended to inform the user community about the data system and services available at the GES-DAAC in support of these information-rich data products. MDST provides support to MODIS data users to access and process data and information for research, applications and educational purposes. This paper will present an overview of the MODIS data products released to public including the suite of atmosphere and oceans data products that can be ordered from the GES-DAAC. Different mechanisms for search and ordering the data, determining data product sizes, data distribution policy, User Assistance System (UAS), and data subscription services will be described.

Effect of Clouds on Apertures of Space-based Air Fluorescence Detectors

NASA Technical Reports Server (NTRS)

Sokolsky, P.; Krizmanic, J.

2003-01-01

Space-based ultra-high-energy cosmic ray detectors observe fluorescence light from extensive air showers produced by these particles in the troposphere. Clouds can scatter and absorb this light and produce systematic errors in energy determination and spectrum normalization. We study the possibility of using IR remote sensing data from MODIS and GOES satellites to delimit clear areas of the atmosphere. The efficiency for detecting ultra-high-energy cosmic rays whose showers do not intersect clouds is determined for real, night-time cloud scenes. We use the MODIS SST cloud mask product to define clear pixels for cloud scenes along the equator and use the OWL Monte Carlo to generate showers in the cloud scenes. We find the efficiency for cloud-free showers with closest approach of three pixels to a cloudy pixel is 6.5% exclusive of other factors. We conclude that defining a totally cloud-free aperture reduces the sensitivity of space-based fluorescence detectors to unacceptably small levels.

3D Cloud Tomography, Followed by Mean Optical and Microphysical Properties, with Multi-Angle/Multi-Pixel Data

NASA Astrophysics Data System (ADS)

Davis, A. B.; von Allmen, P. A.; Marshak, A.; Bal, G.

2010-12-01

The geometrical assumption in all operational cloud remote sensing algorithms is that clouds are plane-parallel slabs, which applies relatively well to the most uniform stratus layers. Its benefit is to justify using classic 1D radiative transfer (RT) theory, where angular details (solar, viewing, azimuthal) are fully accounted for and precise phase functions can be used, to generate the look-up tables used in the retrievals. Unsurprisingly, these algorithms catastrophically fail when applied to cumulus-type clouds, which are highly 3D. This is unfortunate for the cloud-process modeling community that may thrive on in situ airborne data, but would very much like to use satellite data for more than illustrations in their presentations and publications. So, how can we obtain quantitative information from space-based observations of finite aspect ratio clouds? Cloud base/top heights, vertically projected area, mean liquid water content (LWC), and volume-averaged droplet size would be a good start. Motivated by this science need, we present a new approach suitable for sparse cumulus fields where we turn the tables on the standard procedure in cloud remote sensing. We make no a priori assumption about cloud shape, save an approximately flat base, but use brutal approximations about the RT that is necessarily 3D. Indeed, the first order of business is to roughly determine the cloud's outer shape in one of two ways, which we will frame as competing initial guesses for the next phase of shape refinement and volume-averaged microphysical parameter estimation. Both steps use multi-pixel/multi-angle techniques amenable to MISR data, the latter adding a bi-spectral dimension using collocated MODIS data. One approach to rough cloud shape determination is to fit the multi-pixel/multi-angle data with a geometric primitive such as a scalene hemi-ellipsoid with 7 parameters (translation in 3D space, 3 semi-axes, 1 azimuthal orientation); for the radiometry, a simple radiosity-type model is used where the cloud surface "emits" either reflected (sunny-side) or transmitted (shady-side) light at different levels. As it turns out, the reflected/transmitted light ratio yields an approximate cloud optical thickness. Another approach is to invoke tomography techniques to define the volume occupied by the cloud using, as it were, cloud masks for each direction of observation. In the shape and opacity refinement phase, initial guesses along with solar and viewing geometry information are used to predict radiance in each pixel using a fast diffusion model for the 3D RT in MISR's non-absorbing red channel (275 m resolution). Refinement is constrained and stopped when optimal resolution is reached. Finally, multi-pixel/mono-angle MODIS data for the same cloud (at comparable 250 m resolution) reveals the desired droplet size information, hence the volume-averaged LWC. This is an ambitious remote sensing science project drawing on cross-disciplinary expertise gained in medical imaging using both X-ray and near-IR sources and detectors. It is high risk but with potentially high returns not only for the cloud modeling community but also aerosol and surface characterization in the presence of broken 3D clouds.

Pre-launch Performance Assessment of the VIIRS Ice Surface Temperature Algorithm

NASA Astrophysics Data System (ADS)

Ip, J.; Hauss, B.

2008-12-01

The VIIRS Ice Surface Temperature (IST) environmental data product provides the surface temperature of sea-ice at VIIRS moderate resolution (750m) during both day and night. To predict the IST, the retrieval algorithm utilizes a split-window approach with Long-wave Infrared (LWIR) channels at 10.76 μm (M15) and 12.01 μm (M16) to correct for atmospheric water vapor. The split-window approach using these LWIR channels is AVHRR and MODIS heritage, where the MODIS formulation has a slightly modified functional form. The algorithm relies on the VIIRS Cloud Mask IP for identifying cloudy and ocean pixels, the VIIRS Ice Concentration IP for identifying ice pixels, and the VIIRS Aerosol Optical Thickness (AOT) IP for excluding pixels with AOT greater than 1.0. In this paper, we will report the pre-launch performance assessment of the IST retrieval. We have taken two separate approaches to perform this assessment, one based on global synthetic data and the other based on proxy data from Terra MODIS. Results of the split- window algorithm have been assessed by comparison either to synthetic "truth" or results of the MODIS retrieval. We will also show that the results of the assessment with proxy data are consistent with those obtained using the global synthetic data.

Analysis of relations between aerosol optical depth and cloud parameters over land and offshore area of Eastern China and America

NASA Astrophysics Data System (ADS)

Chen, Yi-Lun; Fu, Yun-Fei; Yang, Yuan-Jian; Zhang, Ao-Qi

2014-11-01

As we know, China is the largest developing country and the United State (US) is one of the most developed countries of the world. Due to significant differences of the developmental levels between China and the US, different pollutants emissions may be performed. It is found that aerosol optical depth (AOD) over China is much higher than that over America. Since China and the US locate in westerly wind belts, it is feasible to examine the relationship between different AOD and cloud parameters over land and offshore area of the two countries. In this paper, cloud effective radius (CER), liquid water path (LWP) and AOD derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and circulations supplied by NCEP/NCAR reanalysis data from 2000 to 2013 are employed to explore the relationships between AOD and CER under different LWP levels. Results indicate that there is a clear negative relationship between AOD and CER in different LWP levels over the offshore area contrary to the insignificant relationship over land or the open sea. It suggests that aerosol indirect effects are more obvious over the offshore area.

Overview of CERES Cloud Properties Derived From VIRS AND MODIS DATA

NASA Technical Reports Server (NTRS)

Minis, Patrick; Geier, Erika; Wielicki, Bruce A.; Sun-Mack, Sunny; Chen, Yan; Trepte, Qing Z.; Dong, Xiquan; Doelling, David R.; Ayers, J. Kirk; Khaiyer, Mandana M.

2006-01-01

Simultaneous measurement of radiation and cloud fields on a global basis is recognized as a key component in understanding and modeling the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project (Wielicki et al., 1998) began addressing this issue in 1998 with its first broadband shortwave and longwave scanner on the Tropical Rainfall Measuring Mission (TRMM). This was followed by the launch of two CERES scanners each on Terra and Aqua during late 1999 and early 2002, respectively. When combined, these satellites should provide the most comprehensive global characterization of clouds and radiation to date. Unfortunately, the TRMM scanner failed during late 1998. The Terra and Aqua scanners continue to operate, however, providing measurements at a minimum of 4 local times each day. CERES was designed to scan in tandem with high resolution imagers so that the cloud conditions could be evaluated for every CERES measurement. The cloud properties are essential for converting CERES radiances shortwave albedo and longwave fluxes needed to define the radiation budget (ERB). They are also needed to unravel the impact of clouds on the ERB. The 5-channel, 2-km Visible Infrared Scanner (VIRS) on the TRMM and the 36-channel 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua are analyzed to define the cloud properties for each CERES footprint. To minimize inter-satellite differences and aid the development of useful climate-scale measurements, it was necessary to ensure that each satellite imager is calibrated in a fashion consistent with its counterpart on the other CERES satellites (Minnis et al., 2006) and that the algorithms are as similar as possible for all of the imagers. Thus, a set of cloud detection and retrieval algorithms were developed that could be applied to all three imagers utilizing as few channels as possible while producing stable and accurate cloud properties. This paper discusses the algorithms and results of applying those techniques to more than 5 years of Terra MODIS, 3 years of Aqua MODIS, and 4 years of TRMM VIRS data.

Characterizing Response Versus Scan-Angle for MODIS Reflective Solar Bands Using Deep Convective Clouds

NASA Technical Reports Server (NTRS)

Bhatt, Rajendra; Doelling, David R.; Angal, Amit; Xiong, Xiaoxiong; Scarino, Benjamin; Gopalan, Arun; Haney, Conor; Wu, Aisheng

2017-01-01

MODIS consists of a cross-track, two-sided scan mirror, whose reflectance is not uniform but is a function of angle of incidence (AOI). This feature, known as response versusscan-angle (RVS), was characterized for all reflective solar bands of both MODIS instruments prior to launch. The RVS characteristic has changed on orbit, which must be tracked precisely over time to ensure the quality of MODIS products. The MODIS characterization support team utilizes the onboard calibrators and the earth view responses from multiple pseudo invariant desert sites to track the RVS changes at different AOIs. The drawback of using deserts is the assumption that these sites are radiometrically stable during the monitoring period. In addition, the 16-day orbit repeat cycle of MODIS allows for only a limited set of AOIs over a given desert. We propose a novel and robust approach of characterizing the MODIS RVS using tropical deep convective clouds (DCC). The method tracks the monthly DCC response at specified sets of AOIs to compute the temporal RVS changes. Initial results have shown that the Aqua-MODIS collection 6 band 1 level 1B radiances show considerable residual RVS dependencies, with long-term drifts up to 2.3 at certain AOIs.

Characterizing response versus scan-angle for MODIS reflective solar bands using deep convective clouds

NASA Astrophysics Data System (ADS)

Bhatt, Rajendra; Doelling, David R.; Angal, Amit; Xiong, Xiaoxiong; Scarino, Benjamin; Gopalan, Arun; Haney, Conor; Wu, Aisheng

2017-01-01

MODIS consists of a cross-track, two-sided scan mirror, whose reflectance is not uniform but is a function of angle of incidence (AOI). This feature, known as response versus scan-angle (RVS), was characterized for all reflective solar bands of both MODIS instruments prior to launch. The RVS characteristic has changed on orbit, which must be tracked precisely over time to ensure the quality of MODIS products. The MODIS characterization support team utilizes the onboard calibrators and the earth view responses from multiple pseudoinvariant desert sites to track the RVS changes at different AOIs. The drawback of using deserts is the assumption that these sites are radiometrically stable during the monitoring period. In addition, the 16-day orbit repeat cycle of MODIS allows for only a limited set of AOIs over a given desert. We propose a novel and robust approach of characterizing the MODIS RVS using tropical deep convective clouds (DCC). The method tracks the monthly DCC response at specified sets of AOIs to compute the temporal RVS changes. Initial results have shown that the Aqua-MODIS collection 6 band 1 level 1B radiances show considerable residual RVS dependencies, with long-term drifts up to 2.3% at certain AOIs.

Evaluation of AIRS cloud properties using MPACE data

NASA Astrophysics Data System (ADS)

Wu, Xuebao; Li, Jun; Menzel, W. Paul; Huang, Allen; Baggett, Kevin; Revercomb, Henry

2005-12-01

Retrieval of cloud properties from the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite has been investigated. The cloud products from the collocated MODerate resolution Imaging Spectroradiometer (MODIS) data are used to characterize the AIRS sub-pixel cloud information such as cloud phase, cloud coverage, and cloud layer information. A Minimum Residual (MR) approach is used to retrieve cloud microphysical properties once the cloud top pressure (CTP) and effective cloud amount (ECA) are determined from AIRS CO2 absorption channels between 720 and 790 cm-1. The cloud microphysical properties can be retrieved by minimizing the differences between the observations and the calculations using AIRS longwave window channels between 790 and 1130 cm-1. AIRS is used to derive cloud properties during the Mixed Phase Arctic Cloud Experiment (MPACE) field campaign. Comparison with measurements obtained from lidar data is made for a test day, showing that AIRS cloud property retrievals agree with in situ lidar observations. Due to the large solar zenith angle, the MODIS operational retrieval approach is not able to provide cloud microphysics north of Barrow, Alaska; however, AIRS provides cloud microphysical properties with its high spectral resolution IR measurements.

Mapping the Distribution of Cloud Forests Using MODIS Imagery

NASA Astrophysics Data System (ADS)

Douglas, M. W.; Mejia, J.; Murillo, J.; Orozco, R.

2007-05-01

Tropical cloud forests - those forests that are frequently immersed in clouds or otherwise very humid, are extremely difficult to map from the ground, and are not easily distinguished in satellite imagery from other forest types, but they have a very different flora and fauna than lowland rainforest. Cloud forests, although found in many parts of the tropics, have a very restricted vertical extent and thus are also restricted horizontally. As a result, they are subject to both human disturbance (coffee growing for example) and the effects of possible climate change. Motivated by a desire to seek meteorological explanations for the distribution of cloud forests, we have begun to map cloudiness using MODIS Terra and Aqua visible imagery. This imagery, at ~1030 LT and 1330 LT, is an approximation for mid-day cloudiness. In tropical regions the amount of mid-day cloudiness strongly controls the shortwave radiation and thus the potential for evaporation (and aridity). We have mapped cloudiness using a simple algorithm that distinguishes between the cloud-free background brightness and the generally more reflective clouds to separate clouds from the underlying background. A major advantage of MODIS imagery over many other sources of satellite imagery is its high spatial resolution (~250m). This, coupled with precisely navigated images, means that detailed maps of cloudiness can be produced. The cloudiness maps can then be related to the underlying topography to further refine the location of the cloud forests. An advantage of this technique is that we are mapping the potential cloud forest, based on cloudiness, rather than the actual cloud forest, which are commonly based on forest estimates from satellite and digital elevation data. We do not derive precipitation, only estimates of daytime cloudiness. Although only a few years of MODIS imagery has been used in our studies, we will show that this is sufficient to describe the climatology of cloudiness with acceptable accuracy for its intended purposes. Even periods as short as one month are sufficient for depicting the location of most cloud forest environments. However, we are proceeding to distinguish different characteristics of cloud forests, depending on the overall frequency of cloudiness, the seasonality of cloudiness, and the interannual variability of cloudiness. These results should be useful to those seeking to describe relationships between the physical characteristics of the cloud forests and their biological environment.

Neural network cloud top pressure and height for MODIS

NASA Astrophysics Data System (ADS)

Håkansson, Nina; Adok, Claudia; Thoss, Anke; Scheirer, Ronald; Hörnquist, Sara

2018-06-01

Cloud top height retrieval from imager instruments is important for nowcasting and for satellite climate data records. A neural network approach for cloud top height retrieval from the imager instrument MODIS (Moderate Resolution Imaging Spectroradiometer) is presented. The neural networks are trained using cloud top layer pressure data from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) dataset. Results are compared with two operational reference algorithms for cloud top height: the MODIS Collection 6 Level 2 height product and the cloud top temperature and height algorithm in the 2014 version of the NWC SAF (EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting) PPS (Polar Platform System). All three techniques are evaluated using both CALIOP and CPR (Cloud Profiling Radar for CloudSat (CLOUD SATellite)) height. Instruments like AVHRR (Advanced Very High Resolution Radiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) contain fewer channels useful for cloud top height retrievals than MODIS, therefore several different neural networks are investigated to test how infrared channel selection influences retrieval performance. Also a network with only channels available for the AVHRR1 instrument is trained and evaluated. To examine the contribution of different variables, networks with fewer variables are trained. It is shown that variables containing imager information for neighboring pixels are very important. The error distributions of the involved cloud top height algorithms are found to be non-Gaussian. Different descriptive statistic measures are presented and it is exemplified that bias and SD (standard deviation) can be misleading for non-Gaussian distributions. The median and mode are found to better describe the tendency of the error distributions and IQR (interquartile range) and MAE (mean absolute error) are found to give the most useful information of the spread of the errors. For all descriptive statistics presented MAE, IQR, RMSE (root mean square error), SD, mode, median, bias and percentage of absolute errors above 0.25, 0.5, 1 and 2 km the neural network perform better than the reference algorithms both validated with CALIOP and CPR (CloudSat). The neural networks using the brightness temperatures at 11 and 12 µm show at least 32 % (or 623 m) lower MAE compared to the two operational reference algorithms when validating with CALIOP height. Validation with CPR (CloudSat) height gives at least 25 % (or 430 m) reduction of MAE.

Global distributions of cloud properties for CERES

NASA Astrophysics Data System (ADS)

Sun-Mack, S.; Minnis, P.; Heck, P.; Young, D.

2003-04-01

The microphysical and macrophysical properties of clouds play a crucial role in the earth's radiation budget. Simultaneous measurement of the radiation and cloud fields on a global basis has long been recognized as a key component in understanding and modeling the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. With the implementation of the NASA Clouds and Earth's Radiant Energy System (CERES) in 1998, this need is being met. Broadband shortwave and longwave radiance measurements taken by the CERES scanners at resolutions between 10 and 20 km on the Tropical Rainfall Measuring Mission (TRMM), Terra, and Aqua satellites are matched to simultaneous retrievals of cloud height, phase, particle size, water path, and optical depth from the TRMM Visible Infrared Scanner and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. The combined cloud-radiation product has already been used for developing new, highly accurate anisotropic directional models for converting broadband radiances to flux. They also provide a consistent measure of cloud properties at different times of day over the globe since January 1998. These data will be valuable for determining the indirect effects of aerosols and for linking cloud water to cloud radiation. This paper provides an overview of the CERES cloud products from the three satellites including the retrieval methodology, validation, and global distributions. Availability and access to the datasets will also be discussed.

Recent Progress on Deep Blue Aerosol Algorithm as Applied TO MODIS, SEA WIFS, and VIIRS, and Their Intercomparisons with Ground Based and Other Satellite Measurements

NASA Technical Reports Server (NTRS)

Hsu, N. Christina; Bettenhausen, Corey; Sawyer, Andrew; Tsay, Si-Chee

2012-01-01

The impact of natural and anthropogenic sources of aerosols has gained increasing attention from scientific communities in recent years. Indeed, tropospheric aerosols not only perturb radiative energy balance by interacting with solar and terrestrial radiation, but also by changing cloud properties and lifetime. Furthermore, these anthropogenic and natural air particles, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across oceans and continents resulting in important biogeochemical impacts on the ecosystem. With the launch of SeaWiFS in 1997, Terra/MODIS in 1999, and Aqua/MODIS in 2002, high quality comprehensive aerosol climatology is becoming feasible for the first time. As a result of these unprecedented data records, studies of the radiative and biogeochemical effects due to tropospheric aerosols are now possible. In this talk, we will demonstrate how this newly available SeaWiFS/MODIS aerosol climatology can provide an important piece of puzzles in reducing the uncertainty of estimated climatic forcing due to aerosols. We will start with the global distribution of aerosol loading and their variabilities over both land and ocean on short- and long-term temporal scales observed over the last decade. The recent progress made in Deep Blue aerosol algorithm on improving accuracy of these Sea WiFS / MODIS aerosol products in particular over land will be discussed. The impacts on quantifying physical and optical processes of aerosols over source regions of adding the Deep Blue products of aerosol properties over bright-reflecting surfaces into Sea WiFS / MODIS as well as VIIRS data suite will also be addressed. We will also show the intercomparison results of SeaWiFS/MODIS retrieved aerosol optical thickness with data from ground based AERONET sunphotometers over land and ocean as well as with other satellite measurements. The trends observed in global aerosol loadings of both natural and anthropogenic sources based upon more than a decade of combined MODIS/SeaWiFS data (1997-2011) will be discussed. We will also address the importance of various key issues such as differences in spatial-temporal sampling rates and observation time between different satellite measurements could potentially impact these intercomparisons results, especially for using the monthly mean data, and thus on estimates of long-term aerosol trends.

MISR Aerosol Product Attributes and Statistical Comparisons with MODIS

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.; Nelson, David L.; Garay, Michael J.; Levy, Robert C.; Bull, Michael A.; Diner, David J.; Martonchik, John V.; Paradise, Susan R.; Hansen, Earl G.; Remer, Lorraine A.

2009-01-01

In this paper, Multi-angle Imaging SpectroRadiometer (MISR) aerosol product attributes are described, including geometry and algorithm performance flags. Actual retrieval coverage is mapped and explained in detail using representative global monthly data. Statistical comparisons are made with coincident aerosol optical depth (AOD) and Angstrom exponent (ANG) retrieval results from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The relationship between these results and the ones previously obtained for MISR and MODIS individually, based on comparisons with coincident ground-truth observations, is established. For the data examined, MISR and MODIS each obtain successful aerosol retrievals about 15% of the time, and coincident MISR-MODIS aerosol retrievals are obtained for about 6%-7% of the total overlap region. Cloud avoidance, glint and oblique-Sun exclusions, and other algorithm physical limitations account for these results. For both MISR and MODIS, successful retrievals are obtained for over 75% of locations where attempts are made. Where coincident AOD retrievals are obtained over ocean, the MISR-MODIS correlation coefficient is about 0.9; over land, the correlation coefficient is about 0.7. Differences are traced to specific known algorithm issues or conditions. Over-ocean ANG comparisons yield a correlation of 0.67, showing consistency in distinguishing aerosol air masses dominated by coarse-mode versus fine-mode particles. Sampling considerations imply that care must be taken when assessing monthly global aerosol direct radiative forcing and AOD trends with these products, but they can be used directly for many other applications, such as regional AOD gradient and aerosol air mass type mapping and aerosol transport model validation. Users are urged to take seriously the published product data-quality statements.

Estimation of time-series properties of gourd observed solar irradiance data using cloud properties derived from satellite observations

NASA Astrophysics Data System (ADS)

Watanabe, T.; Nohara, D.

2017-12-01

The shorter temporal scale variation in the downward solar irradiance at the ground level (DSI) is not understood well because researches in the shorter-scale variation in the DSI is based on the ground observation and ground observation stations are located coarsely. Use of dataset derived from satellite observation will overcome such defect. DSI data and MODIS cloud properties product are analyzed simultaneously. Three metrics: mean, standard deviation and sample entropy, are used to evaluate time-series properties of the DSI. Three metrics are computed from two-hours time-series centered at the observation time of MODIS over the ground observation stations. We apply the regression methods to design prediction models of each three metrics from cloud properties. The validation of the model accuracy show that mean and standard deviation are predicted with a higher degree of accuracy and that the accuracy of prediction of sample entropy, which represents the complexity of time-series, is not high. One of causes of lower prediction skill of sample entropy is the resolution of the MODIS cloud properties. Higher sample entropy is corresponding to the rapid fluctuation, which is caused by the small and unordered cloud. It seems that such clouds isn't retrieved well.

Enhancing a Simple MODIS Cloud Mask Algorithm for the Landsat Data Continuity Mission

NASA Technical Reports Server (NTRS)

Wilson, Michael J.; Oreopoulos, Lazarous

2011-01-01

The presence of clouds in images acquired by the Landsat series of satellites is usually an undesirable, but generally unavoidable fact. With the emphasis of the program being on land imaging, the suspended liquid/ice particles of which clouds are made of fully or partially obscure the desired observational target. Knowing the amount and location of clouds in a Landsat scene is therefore valuable information for scene selection, for making clear-sky composites from multiple scenes, and for scheduling future acquisitions. The two instruments in the upcoming Landsat Data Continuity Mission (LDCM) will include new channels that will enhance our ability to detect high clouds which are often also thin in the sense that a large fraction of solar radiation can pass through them. This work studies the potential impact of these new channels on enhancing LDCM's cloud detection capabilities compared to previous Landsat missions. We revisit a previously published scheme for cloud detection and add new tests to capture more of the thin clouds that are harder to detect with the more limited arsenal channels. Since there are no Landsat data yet that include the new LDCM channels, we resort to data from another instrument, MODIS, which has these bands, as well as the other bands of LDCM, to test the capabilities of our new algorithm. By comparing our revised scheme's performance against the performance of the official MODIS cloud detection scheme, we conclude that the new scheme performs better than the earlier scheme which was not very good at thin cloud detection.

Interpretation of multi-wavelength-retrieved cloud droplet effective radii in terms of cloud vertical inhomogeneity based on water cloud simulations using a spectral-bin microphysics cloud model

NASA Astrophysics Data System (ADS)

Matsui, T. N.; Suzuki, K.; Nakajima, T. Y.; Matsumae, Y.

2011-12-01

Clouds play an import role in energy balance and climate changes of the Earth. IPCC AR4, however, pointed out that cloud feedback is still the large source of uncertainty in climate estimates. In the recent decade, the new satellites with the active instruments (e.g. Cloudsat) represented a new epoch in earth observations. The active remote sensing is powerful for illustrating the vertical structures of clouds, but the passive remote sensing from satellite images also contribute to better understating of cloud system. For instance, Nakajima et al. (2010a) and Suzuki et al. (2010) illustrated transition of cloud growth, from cloud droplet to drizzle to rain, using the combine analysis of the cloud droplet size retrieved from passive images (MODIS) and the reflectivity profiles from Cloudsat. Furthermore, EarthCARE that is a new satellite launched years later is composed of not only the active but also passive instruments for the combined analysis. On the other hands, the methods to retrieve the advanced information of cloud properties are also required because many imagers have been operated and are now planned (e.g. GCOM-C/SGLI), and have the advantages such as wide observation width and more observation channels. Cloud droplet effective radius (CDR) and cloud optical thickness (COT) can be retrieved using a non-water-absorbing band (e.g. 0.86μm) and a water-absorbing band (1.6, 2.1, 3.7μm) of imagers under the assumptions such as the log-normal droplet size distribution and the plane-parallel cloud structure. However, the differences between three retrieved CDRs using 1.6, 2.1 or 3.7μm (R16, R21 and R37) are found in the satellite observations. Several studies pointed out that vertical/horizontal inhomogeneity of cloud structure, difference of penetration depth of water-absorbing bands, multi-modal droplet distribution and/or 3-D radiative transfer effect cause the CDR differences. In other words, the advanced information of clouds may lie hidden in the differences. Nakajima et al. (2010b) investigated the impact of the differences sensitivities to particle size and the penetration depth in an attempt to explain the CDR differences found in by using a simple two-layer cloud model with the bi-modal size distribution functions. Their results showed the sensitivity differences between 1.6, 2.1 and 3.7μm bands to droplet sizes and their vertical stratification. In this study, we further investigate the impact of the vertical inhomogeneity structure including the drizzle by using a spectral-bin microphysics cloud model. We apply the 1-D radiative transfer computation to the numerical cloud fields generated by the cloud model, and retrieve the CDRs from the reflectances thus simulated at each band. We then compare the statistics of these retrieved CDRs with the CDRs obtained from MODIS observations and derive the sensitivity functions of the retrieved CDRs to the particle size and the optical depth from the sets of the droplet distribution functions predicted by the model and the retrieved CDRs. This study is an attempt to interpret the CDR differences in terms of the cloud vertical structure and the cloud particle growth processes.

Scale Dependence of Cirrus Horizontal Heterogeneity Effects on TOA Measurements. Part I; MODIS Brightness Temperatures in the Thermal Infrared

NASA Technical Reports Server (NTRS)

Fauchez, Thomas; Platnick, Steven; Meyer, Kerry; Cornet, Celine; Szczap, Frederic; Varnai, Tamas

2017-01-01

This paper presents a study on the impact of cirrus cloud heterogeneities on MODIS simulated thermal infrared (TIR) brightness temperatures (BTs) at the top of the atmosphere (TOA) as a function of spatial resolution from 50 meters to 10 kilometers. A realistic 3-D (three-dimensional) cirrus field is generated by the 3DCLOUD model (average optical thickness of 1.4, cloudtop and base altitudes at 10 and 12 kilometers, respectively, consisting of aggregate column crystals of D (sub eff) equals 20 microns), and 3-D thermal infrared radiative transfer (RT) is simulated with the 3DMCPOL (3-D Monte Carlo Polarized) code. According to previous studies, differences between 3-D BT computed from a heterogenous pixel and 1-D (one-dimensional) RT computed from a homogeneous pixel are considered dependent at nadir on two effects: (i) the optical thickness horizontal heterogeneity leading to the plane-parallel homogeneous bias (PPHB); and the (ii) horizontal radiative transport (HRT) leading to the independent pixel approximation error (IPAE). A single but realistic cirrus case is simulated and, as expected, the PPHB mainly impacts the low-spatial resolution results (above approximately 250 meters), with averaged values of up to 5-7 K (thousand), while the IPAE mainly impacts the high-spatial resolution results (below approximately 250 meters) with average values of up to 1-2 K (thousand). A sensitivity study has been performed in order to extend these results to various cirrus optical thicknesses and heterogeneities by sampling the cirrus in several ranges of parameters. For four optical thickness classes and four optical heterogeneity classes, we have found that, for nadir observations, the spatial resolution at which the combination of PPHB and HRT effects is the smallest, falls between 100 and 250 meters. These spatial resolutions thus appear to be the best choice to retrieve cirrus optical properties with the smallest cloud heterogeneity-related total bias in the thermal infrared. For off-nadir observations, the average total effect is increased and the minimum is shifted to coarser spatial resolutions.

Real time retrieval of volcanic cloud particles and SO2 by satellite using an improved simplified approach

NASA Astrophysics Data System (ADS)

Pugnaghi, Sergio; Guerrieri, Lorenzo; Corradini, Stefano; Merucci, Luca

2016-07-01

Volcanic plume removal (VPR) is a procedure developed to retrieve the ash optical depth, effective radius and mass, and sulfur dioxide mass contained in a volcanic cloud from the thermal radiance at 8.7, 11, and 12 µm. It is based on an estimation of a virtual image representing what the sensor would have seen in a multispectral thermal image if the volcanic cloud were not present. Ash and sulfur dioxide were retrieved by the first version of the VPR using a very simple atmospheric model that ignored the layer above the volcanic cloud. This new version takes into account the layer of atmosphere above the cloud as well as thermal radiance scattering along the line of sight of the sensor. In addition to improved results, the new version also offers an easier and faster preliminary preparation and includes other types of volcanic particles (andesite, obsidian, pumice, ice crystals, and water droplets). As in the previous version, a set of parameters regarding the volcanic area, particle types, and sensor is required to run the procedure. However, in the new version, only the mean plume temperature is required as input data. In this work, a set of parameters to compute the volcanic cloud transmittance in the three quoted bands, for all the aforementioned particles, for both Mt. Etna (Italy) and Eyjafjallajökull (Iceland) volcanoes, and for the Terra and Aqua MODIS instruments is presented. Three types of tests are carried out to verify the results of the improved VPR. The first uses all the radiative transfer simulations performed to estimate the above mentioned parameters. The second one makes use of two synthetic images, one for Mt. Etna and one for Eyjafjallajökull volcanoes. The third one compares VPR and Look-Up Table (LUT) retrievals analyzing the true image of Eyjafjallajökull volcano acquired by MODIS aboard the Aqua satellite on 11 May 2010 at 14:05 GMT.

Assessing the accuracy of MISR and MISR-simulated cloud top heights using CloudSat- and CALIPSO-retrieved hydrometeor profiles

NASA Astrophysics Data System (ADS)

Hillman, Benjamin R.; Marchand, Roger T.; Ackerman, Thomas P.; Mace, Gerald G.; Benson, Sally

2017-03-01

Satellite retrievals of cloud properties are often used in the evaluation of global climate models, and in recent years satellite instrument simulators have been used to account for known retrieval biases in order to make more consistent comparisons between models and retrievals. Many of these simulators have seen little critical evaluation. Here we evaluate the Multiangle Imaging Spectroradiometer (MISR) simulator by using visible extinction profiles retrieved from a combination of CloudSat, CALIPSO, MODIS, and AMSR-E observations as inputs to the MISR simulator and comparing cloud top height statistics from the MISR simulator with those retrieved by MISR. Overall, we find that the occurrence of middle- and high-altitude topped clouds agrees well between MISR retrievals and the MISR-simulated output, with distributions of middle- and high-topped cloud cover typically agreeing to better than 5% in both zonal and regional averages. However, there are significant differences in the occurrence of low-topped clouds between MISR retrievals and MISR-simulated output that are due to differences in the detection of low-level clouds between MISR and the combined retrievals used to drive the MISR simulator, rather than due to errors in the MISR simulator cloud top height adjustment. This difference highlights the importance of sensor resolution and boundary layer cloud spatial structure in determining low-altitude cloud cover. The MISR-simulated and MISR-retrieved cloud optical depth also show systematic differences, which are also likely due in part to cloud spatial structure.

Evaluation of Passive Multilayer Cloud Detection Using Preliminary CloudSat and CALIPSO Cloud Profiles

NASA Astrophysics Data System (ADS)

Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.

2006-12-01

During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water clouds in overlapped conditions.