Early Results from the MODIS Cloud Algorithms cloud detection optical, microphysical, and cloud top properties S. Platnick 5,2, S. A. Ackerman 1, M. D.

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Early Results from the MODIS Cloud Algorithms cloud detection optical, microphysical, and cloud top properties S. Platnick 5,2, S. A. Ackerman 1, M. D. King 2, W. P. Menzel 3,1, B. A. Baum 4,1, et al. 1 U. Wisconsin/CIMSS, 2 NASA GSFC, 3 NOAA NESDIS, 4 NASA LaRC, 5 UMBC/JCET

Outline MODIS - a quick introduction MODIS - a quick introduction MODIS cloud products MODIS cloud products Algorithm descriptions and example retrievals Algorithm descriptions and example retrievals Data status Data status MODIS (MODerate resolution Imaging Spectroradiomter)

Filter radiometer, 4 detector arrays, 36 spectral bands; 250 m, 500 m, 1 km spatial resolution Filter radiometer, 4 detector arrays, 36 spectral bands; 250 m, 500 m, 1 km spatial resolution Onboard calibration via Solar Diffuser/Stability Monitor, Spectral Radiometric Calibration Assembly instruments Onboard calibration via Solar Diffuser/Stability Monitor, Spectral Radiometric Calibration Assembly instruments First light on 24 February 2000 (Terra launch 18 Dec 1999) First light on 24 February 2000 (Terra launch 18 Dec 1999) Science teams organized into atmosphere, land, and ocean discipline groups Science teams organized into atmosphere, land, and ocean discipline groups MODIS instrument highlights

MODIS Atmosphere Global 19 April 2000 L1B True color RGB (0.65, 0.56, 0.47 µ m bands) example data granule coverage (5 min)

Pixel level products (Level 2) overview Pixel level products (Level 2) overview – Cloud mask for determining “ clear-sky ” – Cloud top properties – Cloud optical, microphysical properties (optical thickness, effective particle size, water path, thermodynamic phase, cirrus reflectance) Unique aspects Unique aspects – New algorithms from greater spectral coverage – Heritage algorithms at higher spatial resolution – Includes QA (processing and assessment info) MODIS cloud products, granule level

Gridded time-average products (Level 3) Gridded time-average products (Level 3) – Daily, 8 day, monthly composites containing all atmosphere products – 1˚ x 1˚ equal angle grid – mean, standard deviation, marginal and joint probability distributions joint probability distributions – quick look available on the web details at the MODIS atmosphere web page MODIS cloud products, global composites

Cloud mask (S. Ackerman, R. Frey, K. Strabala – U. Wisconsin/CIMSS) Bottom of the algorithmic “ food chain ”, input to all MODIS products. Bottom of the algorithmic “ food chain ”, input to all MODIS products. 1 km nadir spatial resolution day & night, (250 m day) 1 km nadir spatial resolution day & night, (250 m day) 17 spectral bands ( µm, incl µm) 17 spectral bands ( µm, incl µm) – 11 spectral tests (function of 5 ecosystems) – temporal consistency test over ocean, desert (nighttime) – spatial variability test over ocean 48 bits per pixel including individual test results and processing path; generation of clear sky maps 48 bits per pixel including individual test results and processing path; generation of clear sky maps Bits 1,2 give combined test results as: confident clear, probably clear, uncertain, obstructed/cloudy (clear sky conservative) Bits 1,2 give combined test results as: confident clear, probably clear, uncertain, obstructed/cloudy (clear sky conservative)

Cloud mask, cont. Spectral tests use fuzzy thresholds, examples include Spectral tests use fuzzy thresholds, examples include – low cloud tests: – low cloud tests: 3.9 µ m - 11 µ m BT – high cloud tests: – high cloud tests: 13.9 µ m (CO 2 ), 1.38 µ m (H 2 O), µ m BT 13.9 µ m (CO 2 ), 1.38 µ m (H 2 O), µ m BT – 1.6 µ m snow/ice test – 1.6 µ m snow/ice test – NIR/VIS reflectance test; IR tests (dependent on sfc emissivity, PW, aerosols); et al. – NIR/VIS reflectance test; IR tests (dependent on sfc emissivity, PW, aerosols); et al. Ackerman, S. A. et al. 1998: JGR, 103,

Cloud mask, validation activities Mask consistent with radar/lidar cloud boundary measurements at Oklahoma ARM CART site and ER-2 observations during spring 2000 campaign (including correct snow identification). Mask consistent with radar/lidar cloud boundary measurements at Oklahoma ARM CART site and ER-2 observations during spring 2000 campaign (including correct snow identification). Improvements being made for sun glint, warm cloud in arid ecosystems, Antarctica, nighttime low cloud over land, nighttime snow/ice surfaces Improvements being made for sun glint, warm cloud in arid ecosystems, Antarctica, nighttime low cloud over land, nighttime snow/ice surfaces Regional/global validation is ongoing. Gobal clear sky composite images being used to identify problem regions. Regional/global validation is ongoing. Gobal clear sky composite images being used to identify problem regions.

aa MODIS cloud mask example (confident clear is green, probably clear is blue, uncertain is red, cloud is white) 1.6 µm image0.86 µm image11 µm image3.9 µm imagecloud mask Snow test (impacts choice of tests/thresholds) VIS test (over non-snow covered areas) BT test for low clouds BT test (primarily for high cloud) 13.9 µm high cloud test (sensitive in cold regions)

MODIS 5-8 September 2000 Band 31 (11.0 µm) Daytime Clear sky Brightness Temperature

MODIS 5-8 September 2000 Band 1, 4, 3 (R/G/B) Daytime Clear sky Reflectance Composite

Cloud top properties (P. Menzel, R. Frey, K. Strabala, L. Gumley, et al. – NOAA NESDIS, U. Wisc./CIMSS) Cloud top pressure, temperature, effective emissivity Cloud top pressure, temperature, effective emissivity Retrieved for every 5x5 box of 1 km FOV ’ s, when at least 5 FOV ’ s are cloudy, day & night Retrieved for every 5x5 box of 1 km FOV ’ s, when at least 5 FOV ’ s are cloudy, day & night CO 2 Slicing technique (5 bands, µ m) CO 2 Slicing technique (5 bands, µ m) – ratio of cloud forcing in 2 nearby bands – retrieve p c ; T c from temperature profile – most accurate for high and mid-level clouds Previously applied to HIRS (NOAA POES, 20 km). MODIS 1st satellite sensor capable of CO 2 slicing at high spatial resolution. Previously applied to HIRS (NOAA POES, 20 km). MODIS 1st satellite sensor capable of CO 2 slicing at high spatial resolution.

Activities proceeding via early ER-2 effort (March 2000 with lidar and HIS IR interferometer), and NOAA HIRS intercomparisons Activities proceeding via early ER-2 effort (March 2000 with lidar and HIS IR interferometer), and NOAA HIRS intercomparisons Cloud top pressure compares well with HIRS and aircraft validation,better than 50 mb. Cloud top pressure compares well with HIRS and aircraft validation,better than 50 mb. Cloud top properties, validation activities Frey, R. A. et al, 1999: JGR, 104,

CO 2 slicing Technique: Technique: - ratio of cloud forcing at two near-by wavelengths - effective emissivity includes cloud fraction in 5x5 box - actual cloud emissivity assumed same for each band - radiance gradient used when clear sky not available The more absorbing bands are more sensitive to high clouds, weighting functions The more absorbing bands are more sensitive to high clouds, weighting functions Frey, R. A. et al, 1999: A comparison of cloud top heights computed from airborne lidar and MAS radiance data. J. Geophys. Res., 104,

Cloud Mask – MODIS 12 March 2000, 1730 UTC snow clear=green cloud=white uncertain=red MODIS band µm Cloud Mask ARM CART site

Cloud Top Pressure – MODIS 12 March 2000, 1730 UTC MODIS band µ m Cloud top pressure mb=purple mb=blue mb=red ARM CART site

Comparison of ER2 lidar (nadir view), HIRS (3 hrs later), RAOB, & MODIS Cloud Properties over ARM CART site, Oklahoma lidar effective emissivity vs. HIRS CTP vs. HIRS

Cloud top PressureCloud top Temperature Cloud Fraction Cloud Effective Emissivity MODIS 5-8 September 2000

IR thermodynamic phase algorithm (B. Baum, S. Ackerman, K. Strabala – NASA LaRC, U.W. CIMSS) Tri-spectral method, 5 km resolution Tri-spectral method, 5 km resolution NIR, MWIR reflectance technique being developed NIR, MWIR reflectance technique being developed ice cloud April 1996 Success water cloud Jan 1993 TOGA/ COARE Strabala, Menzel, and Ackerman, 1994, JAM, 2, Baum et al, 2000, JGR, 105,

Ice Water Mixed Phase Uncertain MODIS cloud thermodynamic phase - IR algorithm Clouds over Southern India 19 April 2000 VIS IR window cloud phase

MODIS 5-8 September 2000 IR retrieval - percent liquid water

MODIS 5-8 September 2000 IR retrieval - percent ice water

MODIS IR phase retrieval vs. Cloud Top Temperature frequency of ice phase & T c < 253 K statistics from 5 Sept day and night, 60 º N-60 º S, water surface only frequency (%)

MODIS IR phase retrieval vs. Cloud Top Temperature frequency of ice phase & 253< T c < 273 K statistics from 5 Sept day and night, 60 º N-60 º S, water surface only

frequency (%) MODIS IR phase retrieval vs. Cloud Top Temperature frequency of ice phase & T c > 273 K statistics from 5 Sept day and night, 60 º N-60 º S, water surface only

Cloud optical, microphysical properties (M. D. King, S. Platnick, M. Gray, E. Moody, J. Li, S.-C. Tsay, et al. – NASA GSFC, UMBC) Optical thickness, particle size (effective radius), water path Optical thickness, particle size (effective radius), water path 1 km spatial resolution, daytime only, liquid water and ice clouds 1 km spatial resolution, daytime only, liquid water and ice clouds Land, ocean, snow/sea ice surfaces Land, ocean, snow/sea ice surfaces Solar reflectance technique, VIS through MWIR (0.65, 0.86, 1.2, 1.6, 2.1, 3.7 µ m) Solar reflectance technique, VIS through MWIR (0.65, 0.86, 1.2, 1.6, 2.1, 3.7 µ m) MODIS 1 st satellite sensor with all useful SWIR, MWIR bands

Cloud optical, microphysical properties, cont. Required input: Required input: – cloud mask (tuned for cloudy not clear using individual cloud mask tests) – cloud top temperature for 3.7 µ m retrieval – cloud top pressure for atmospheric correction (being implemented) – cloud phase (currently derived from individual cloud mask tests, not IR or solar tests) – surface albedo (currently assigned from IGBP ecosystem map & NISE snow/ice data set) Early validation effort as part of SAFARI 2000 Early validation effort as part of SAFARI 2000

MODIS SAFARI granule RGB composite 13 September 2000, 0925 UTC Namibia Etosha Pan Angola marine stratocumulus ER-2 ground track Namibia Angola Botswana South Africa Zambia

(>99%) (>95%) (>66%)

Data summary Atmosphere L2 products processed on P.I. system at GSFC (except cloud mask) Atmosphere L2 products processed on P.I. system at GSFC (except cloud mask) Cloud products archived at GSFC DAAC Cloud products archived at GSFC DAAC – series starts at 8/20/00 for L2, 10/31/00 for L3(1d) – series starts at 8/20/00 for L2, 10/31/00 for L3(1d) Current archived products are “ beta ” release Current archived products are “ beta ” release – early data product, useful for familiarity with data formats/parameters, minimal validation, temporary – early data product, useful for familiarity with data formats/parameters, minimal validation, temporary Consistent processing time series (instrument bias settings, L1B algorithm) underway Consistent processing time series (instrument bias settings, L1B algorithm) underway Order through EOS Data Gateway Order through EOS Data Gateway - details at - details at

Data summary, cont. Data file info Data file info –“ MOD35 ” cloud mask ~ 48 MB/granule daytime –“ MOD06 ” cloud product ~ 65 MB/granule daytime, 16 MB nighttime, 12 GB/day - L3 atmospheres ~ MB/day - L1B ~ 340 MB/granule, 70 GB/day L2 production system limits L2 production system limits – currently running at approximately “ 1x ”, not sufficient for reprocessing needs – currently running at approximately “ 1x ”, not sufficient for reprocessing needs

minimum maximum standard deviation mean L3 optical thickness (liquid water) statistics, 10/2/00, from atmo web page

Algorithms summary MODIS provides an unprecedented opportunity for cloud and other atmospheric studies MODIS provides an unprecedented opportunity for cloud and other atmospheric studies – 36 spectral channels, high spatial resolution Comprehensive set of cloud algorithms Comprehensive set of cloud algorithms Archive of pixel level retrievals, global statistics Archive of pixel level retrievals, global statistics Product intercomparison for small number of selected day(s) proven useful Product intercomparison for small number of selected day(s) proven useful Validation activities ongoing (gnd. based, in situ, aircraft, satellite intercomparisons, etc.); detailed plans on atmosphere web site Validation activities ongoing (gnd. based, in situ, aircraft, satellite intercomparisons, etc.); detailed plans on atmosphere web site