Clouds, Aerosols, and Atmospheric Composition from Satellites : Clouds, Aerosols, and Atmospheric Composition from Satellites Cloud optical, microphysical, and radiative properties
Terra, Aqua, ICESat
Aerosol optical and microphysical properties
Terra, Aqua, SeaWiFS
Atmospheric profiles
Terra, Aqua
Summary and resources
Data availability
Collection 5 reprocessing schedule Michael D. King
EOS Senior Project Scientist
NASA Goddard Space Flight Center
MODIS Cloud Mask (MOD35/MYD35)(S. A. Ackerman, W. P. Menzel, R. A. Frey, K. I. Strabala - U. Wisc.) : MODIS Cloud Mask (MOD35/MYD35)(S. A. Ackerman, W. P. Menzel, R. A. Frey, K. I. Strabala - U. Wisc.) MODIS cloud mask uses multispectral imagery to indicate whether the scene is clear, cloudy, or affected by shadows
Cloud mask is input to many atmosphere and land algorithms
Mask is generated at 250 m and 1 km resolutions
Mask uses 20 spectral bands ranging from 0.55-13.93 µm
11 different spectral tests are performed, with different tests being conducted over each of 5 different domains (land, ocean, coast, snow, and desert)
Temporal consistency test is run over the oceans
Spatial variability is run over the oceans
Algorithm based on radiance thresholds in the infrared, and reflectance and reflectance ratio thresholds in the visible and near-infrared
Cloud mask consists of 48 bits of information for each pixel, including results of individual tests and the processing path used
Bits 1 & 2 give combined results (confident clear, probably clear, probably cloudy, cloudy)
Terra/MODIS Cloud Mask (S. A. Ackerman, W. P. Menzel – NOAA/NESDIS, Univ. Wisconsin) : True Color Composite (0.65, 0.56, 0.47) Terra/MODIS Cloud Mask (S. A. Ackerman, W. P. Menzel – NOAA/NESDIS, Univ. Wisconsin) King et al. (2003) Cloud Mask June 4, 2001 Confident Clear Probably Clear Cloudy Probably Cloudy
Monthly Mean Cloud Fraction during Daytime(M. D. King, S. Platnick et al. – NASA GSFC) : Monthly Mean Cloud Fraction during Daytime(M. D. King, S. Platnick et al. – NASA GSFC) April 2003 (Collection 4)
Zonal Mean Cloud Fraction during Daytime(M. D. King, S. Platnick et al. – NASA GSFC) : Zonal Mean Cloud Fraction during Daytime(M. D. King, S. Platnick et al. – NASA GSFC) April 2004 (Collection 4) 1.0 Cloud Fraction (Daytime) 0.0 0.4 -90 0.9 0.8 0.6 0.5 0.2 -60 -30 0 30 60 90 Latitude 0.7 0.3 0.1 Terra Aqua Ocean Land
Time Series of Cloud Fraction during the Daytime(M. D. King, S. Platnick et al. – NASA GSFC) : Time Series of Cloud Fraction during the Daytime(M. D. King, S. Platnick et al. – NASA GSFC) 1.0 0.0 0.4 0.9 0.8 0.6 0.5 0.2 0.7 0.3 0.1 Cloud Fraction (Daytime) Jul02 Sep02 Nov02 Jan03 Mar03 May03 Jul03 Sep03 Nov03 Jan04 Mar04 May04 Jul04 Terra Aqua
Combined Elevation and Atmospheric Data : Combined Elevation and Atmospheric Data An ICESat first day track (2/20/03) across Antarctica Vertical exaggeration 50x, 1064 nm data only, RADARSAT mosaic image from CSA
GLAS Global Cloud Cover(J. D. Spinhirne et al. – NASA GSFC) : GLAS Global Cloud Cover(J. D. Spinhirne et al. – NASA GSFC) October 16-November 16, 2003 70% Global Cloud Cover
45% Single Layer Cloud Cover
25% Multiple Layer Cloud Cover 1.0 0.0 Cumulative Frequency 0.6 0.4 0.8 0.2 Number of Layers 0 1 2 3 4 5
MODIS Cloud Product (MOD06/MYD06) (M. D. King, S. Platnick, W. P. Menzel, B. C. Gao – GSFC, NOAA, NRL) : MODIS Cloud Product (MOD06/MYD06) (M. D. King, S. Platnick, W. P. Menzel, B. C. Gao – GSFC, NOAA, NRL) Cloud physical, radiative, and microphysical properties
Cloud top pressure, temperature, and effective emissivity
CO2 slicing for middle and high clouds (pc < 700 hPa)
11 µm brightness temperature for low clouds
Cloud optical thickness, thermodynamic phase, and effective radius
Cloud phase determined from cloud mask tests, bispectral threshold (8.5 & 11 µm), and shortwave infrared tests (1.6 and 2.1 µm)
Surface reflectance from MODIS ecosystem and albedo products
Solar reflectance technique using visible through midwave infrared bands
Effective radius determined separately using 1.6, 2.1 (baseline), and 3.7 µm bands
Effective radius and optical thickness computed using alternative 1.6 and 2.1 µm algorithm for ocean and snow/sea ice surfaces (new in collection 5)
Thin cirrus reflectance in the visible
Uses 1.38 µm band to determine thin cirrus and then estimates cirrus reflectance at visible bands
Terra/MODIS Cloud Thermodynamic Phase (M. D. King, S. Platnick, J. Riédi et al. – NASA GSFC, U. Lille) : True Color Composite (0.65, 0.56, 0.47) Terra/MODIS Cloud Thermodynamic Phase (M. D. King, S. Platnick, J. Riédi et al. – NASA GSFC, U. Lille) Ice Clouds Liquid Clear Sky Ice Uncertain Thermodynamic Phase Water Clouds Collection 5 March 22, 2001
Terra/MODIS Cloud Top Pressure and Temperature (W. P. Menzel – NOAA/NESDIS, Univ. Wisconsin) : 600 800 100 200 300 1000 400 Terra/MODIS Cloud Top Pressure and Temperature (W. P. Menzel – NOAA/NESDIS, Univ. Wisconsin) Cloud Top Pressure (hPa) Cloud Top Temperature (K) Collection 5 Cloud Top Pressure (hPa) Cloud Top Temperature (K) 250 275 150 175 200 300 225
Spatially Complete Spectral Albedo Maps(E. G. Moody, M. D. King, S. Platnick, C. B. Schaaf, F. Gao – GSFC, BU) : Spatially Complete Spectral Albedo Maps(E. G. Moody, M. D. King, S. Platnick, C. B. Schaaf, F. Gao – GSFC, BU) Moody et al. (2005) Moody et al. (2005)
Snow Albedo by Forest EcosystemsNorthern Hemisphere Multiyear Average (2000-2004) : Snow Albedo by Forest EcosystemsNorthern Hemisphere Multiyear Average (2000-2004)
Snow Albedo for Sparse Vegetation EcosystemsNorthern Hemisphere Multiyear Average (2000-2004) : Snow Albedo for Sparse Vegetation EcosystemsNorthern Hemisphere Multiyear Average (2000-2004)
Spatially Complete White-Sky AlbedoJanuary 1-16, 2002 : Spatially Complete White-Sky AlbedoJanuary 1-16, 2002 0.6 0.8 0.0 0.2 Surface Albedo (0.86 µm) 0.4 Snow-free Snow-covered
Cloud Optical Thickness and Effective Radius (M. D. King, S. Platnick – NASA GSFC) : Cloud Optical Thickness and Effective Radius (M. D. King, S. Platnick – NASA GSFC) Ice Clouds 100 100 1 1 10 10 30 Cloud Optical Thickness Cloud Effective Radius (µm) Ice Clouds 60 6 2 16 33 51 15 9 23 Water Clouds Water Clouds Collection 5 24 42
Cloud Optical Thickness and Effective Radius Uncertainty : Cloud Optical Thickness and Effective Radius Uncertainty Cloud Optical Thickness Uncertainty (%) Cloud Effective Radius Uncertainty (µm) 1 100 Uncertainty (%) Collection 5 March 22, 2001 10
Monthly Mean Cloud Effective Radius(M. D. King, S. Platnick et al. – NASA GSFC) : Monthly Mean Cloud Effective Radius(M. D. King, S. Platnick et al. – NASA GSFC) April 2003 (Collection 4)
QA Mean
California / California Current RegimeMonthly Joint Histogram Counts of Liquid Water Clouds over Ocean : California / California Current RegimeMonthly Joint Histogram Counts of Liquid Water Clouds over Ocean 32°-40°N, 117°-125°W
June 2003 Terra/MODIS (AM Overpass) Aqua/MODIS (PM Overpass) Cloud Optical Thickness 10 50 40 30 20 15 8 6 4 2 0 Cloud Effective Radius (µm) Cloud Effective Radius (µm) 2 4 6 8 10 12.5 15 17.5 25 20 30 2 4 6 8 10 12.5 15 17.5 25 20 30 10 50 40 30 20 15 8 6 4 2 0
MODIS Aerosol Product (MOD04/MYD04)(Y. J. Kaufman, L. A. Remer, D. Tanré - NASA GSFC, Univ. Lille) : MODIS Aerosol Product (MOD04/MYD04)(Y. J. Kaufman, L. A. Remer, D. Tanré - NASA GSFC, Univ. Lille) Seven MODIS bands are utilized to derive aerosol properties
0.47, 0.55, 0.65, 0.86, 1.24, 1.64, and 2.13 µm
Ocean
reflectance contrast between cloud-free atmosphere and ocean reflectance (dark)
aerosol optical thickness (0.55-2.13 µm)
size distribution characteristics (fraction of aerosol optical thickness in the fine particle mode; effective radius)
Land
dense dark vegetation and semi-arid regions determined where aerosol is most transparent (2.13 µm)
contrast between Earth-atmosphere reflectance and that for dense dark vegetation surface (0.47 and 0.66 µm)
aerosol optical thickness (0.47 and 0.66 µm)
fraction of aerosol optical thickness in the fine particle mode
Terra/MODIS Aerosol Optical Thickness (Y. J. Kaufman, L. A. Remer, D. Tanré - NASA GSFC, Univ. Lille) : Terra/MODIS Aerosol Optical Thickness (Y. J. Kaufman, L. A. Remer, D. Tanré - NASA GSFC, Univ. Lille) King et al. (2003) 0.4 0.8 0.0 0.2 0.6 1.0 True Color Composite (0.65, 0.56, 0.47) Aerosol Optical Thickness ta (0.56 µm) May 4, 2001 sunglint
MODIS Monthly Mean Aerosol Optical Thickness(Y. J. Kaufman, D. Tanré, L. A. Remer – NASA GSFC, Univ. of Lille) : MODIS Monthly Mean Aerosol Optical Thickness(Y. J. Kaufman, D. Tanré, L. A. Remer – NASA GSFC, Univ. of Lille) Terra
September 2000 Fine Mode
Industrial pollution
China, India, US, Europe
Smoke from biomass burning
Brazil and Bolivia
southern Africa (DRC, Angola, Zambia)
Australia, Borneo
Coarse Mode
Desert dust
Sahara, Arabian Sea
Sea salt
Southern ocean
Deep Blue Algorithm for SeaWiFS & MODIS(N. C. Hsu, S. C. Tsay, M. D. King, and J. R. Herman – NASA GSFC) : Utilize solar reflectance at l = 412, 490, and 670 nm to retrieve aerosol optical thickness (ta) and single scattering albedo (?o)
Less sensitive to aerosol height, compared to UV methods
Works well on retrieving aerosol properties over various types of surfaces, including very bright desert Deep Blue Algorithm for SeaWiFS & MODIS(N. C. Hsu, S. C. Tsay, M. D. King, and J. R. Herman – NASA GSFC) Hsu et al. (2004)
Aerosol Optical Thickness of Dust plumes in Africa (N. C. Hsu, S. C. Tsay, M. D. King, and J. R. Herman – NASA GSFC) : Aerosol Optical Thickness of Dust plumes in Africa (N. C. Hsu, S. C. Tsay, M. D. King, and J. R. Herman – NASA GSFC) Hsu et al. (2004) SeaWiFS Cloud Cloud
MODIS Deep Blue Algorithm over the Middle East(N. C. Hsu , S. C. Tsay, M. D. King – NASA GSFC) : MODIS Deep Blue Algorithm over the Middle East(N. C. Hsu , S. C. Tsay, M. D. King – NASA GSFC) August 7, 2005 Aerosol Optical Thickness Persian Gulf True Color Composite (0.65, 0.56, 0.47) Aerosol Optical Thickness 1.5 2.0 0.5 2.5 1.0 0.0 Iraq Saudi Arabia Iran Syria
MODIS Atmospheric Profiles Product (MOD07/MYD07) (W. P. Menzel, J. Li, S. W. Seemann - Univ. Wisconsin) : MODIS Atmospheric Profiles Product (MOD07/MYD07) (W. P. Menzel, J. Li, S. W. Seemann - Univ. Wisconsin) Uses 12 spectral bands ranging from 4.47-14.24 µm
Statistical retrievals of atmospheric temperature, moisture layers, total precipitable water, total ozone content, and stability indices
Clear sky retrievals are done over land and ocean for both day and night
20% of the radiances measured within a 5 x 5 field of view area (approximately 5 km) are cloud-free
Radiative transfer computations are performed over the MODIS bandpass characteristics where the model has 101 pressure-level vertical coordinates
atmospheric profile information is saved at only 20 levels
total precipitable water is computed by integrating over the retrieved profiles with 101 levels
Aqua/MODIS Precipitable Water (MOD05/MYD05)(S. W. Seemann, J. Li, W. P. Menzel – Univ. Wisconsin, NOAA) : September 4, 2002 Aqua/MODIS Precipitable Water (MOD05/MYD05)(S. W. Seemann, J. Li, W. P. Menzel – Univ. Wisconsin, NOAA) Precipitable Water (cm) 0.8 2.6 4.4 3.2 2.0 1.4 3.8 King et al. (2003)
Aqua/MODIS Profiles of Atmospheric Temperature and Water Vapor Mixing Ratio : September 4, 2002 Aqua/MODIS Profiles of Atmospheric Temperature and Water Vapor Mixing Ratio Temperature (K) cloud 250 270 255 260 265 Pressure (hPa) 950 800 500 700 900 600 550 650 750 850 Mixing Ratio (g/km) cloud 0 16 4 8 12 Pressure (hPa) 950 800 500 700 900 600 550 650 750 850 37.5 38 38.5 39 39.5 Latitude (°N) Temperature Mixing Ratio
MODIS Precipitable Water Product (MOD05/MYD05)(B. C. Gao, W. P. Menzel, S. W. Seemann - NRL, Univ. Wisconsin) : MODIS Precipitable Water Product (MOD05/MYD05)(B. C. Gao, W. P. Menzel, S. W. Seemann - NRL, Univ. Wisconsin) Near-infrared water vapor
Uses 5 spectral bands located in and around the 0.94 µm water vapor band
Retrievals of PW over land and over the ocean with sunglint during the daytime
Accuracy of about 7% as compared to ground-based microwave radiometers
Thermal infrared water vapor
Uses 12 spectral bands ranging from 4.47-14.24 µm
Algorithm consists of a statistical regression that simultaneously retrieves atmospheric profiles of temperature, water vapor, and ozone
For dry atmospheres, MODIS overestimates the total PW, whereas for moist atmospheres MODIS underestimates PW
rms bias between MODIS and ground-based microwave radiometers is 4.7 mm
Monthly Mean Precipitable Water(S. W. Seemann, J. Li, W. P. Menzel – Univ. Wisconsin, NOAA) : Monthly Mean Precipitable Water(S. W. Seemann, J. Li, W. P. Menzel – Univ. Wisconsin, NOAA) January & July 2004 (Collection 4)
Summary and Resources : Summary and Resources Terra and Aqua
MODIS atmosphere products (descriptions, level-1b and level-3 browse imagery, documentation, contact information, tools for working with and ordering data…)
modis-atmos.gsfc.nasa.gov
MODIS multiple data ordering page (ordering interface for level-1b, geolocation, and atmosphere data)
MODIS online visualization and analysis system
MODIS surface albedo, ecosystem, and NDVI filled-in global data sets
Image Production for Web site
228 MB of images produced every day
Collection 4 reprocessing complete for Terra and Aqua
Terra and Aqua forward stream near real-time
Collection 5 enhancements and reprocessing to begin for Terra
Atmosphere – September 12, 2005 (reprocessing)
Land ~ January 1, 2006 (and atmosphere forward processing)