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Overview from ROSES 2009 Terra/Aqua NRA: 20 funded investigations

Algorithm Refinement (proposal element 2.4) •  5 funded teams:

-  Aerosol dark target: L. Remer, R. Levy -  Aerosol deep blue: C. Hsu, R. Hansell, J. Huang, S-C. Tsay -  Cloud-top, mask, profiles: S. Ackerman, P. Menzel, R. Frey, E.

Borbas, B. Baum -  Cloud optical properties: S. Platnick, M. D. King, R. Pincus -  Ice cloud models: B. Baum, P. Yang, A. Heymsfield

•  1 previous team not funded (cirrus reflectance, NIR water vapor)

New Algorithm Capability/Products (2.3) •  Cirrus retrievals w/1.38 !m band: K. Meyer, S. Platnick

NRT Capability (2.5) •  Direct broadcast/IMAPP: A. Huang •  Polar winds (MODIS & AIRS): D. Santek

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•  Day 1: Collection 6 –  Status of “Testing” system, schedule, etc. –  L2 Algorithm Plans/Status –  L3 and ATML2 Plan/Status –  Ancillary:

! New BU gap-filled land and snow/ice spectral albedo !  Ice cloud models for retrievals and data analysis

•  Day 2: Science Data Analysis Presentations –  Science Talks (9)

•  Posters –  24 Posters

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•  C5 L1B, cloud mask, profile products

•  C51 Atmosphere L2, L3 products –  Aqua C51 reprocessing completed early 2010 –  Terra C51 reprocessing completed late 2010

•  Terra Deep Blue algorithm requires L1B polarization corrections (available only through 2007)

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MODIS Data for IPCC CMIP5 (Coupled Model Intercomparison Project)

•  Previous IPCC assessments have not made good use of observational data for model assessment.

•  Program for Climate Model Diagnosis and Intercomparison (PCMDI) at LLNL has reached out to make NASA products more effectively accessible for routine climate model evaluation.

•  Two workshops were held (LLNL, Oct. 2010; GSFC, Nov 2010). •  Identified a small number (~12-14) of observational data sets that can be

“directly” compared to model output. •  For MODIS: Cloud Fraction (MOD35)

-  Monthly Terra cloud fraction data record from early 2000–Dec 2009 -  netCDF Climate Forecast (CF) compliant naming conventions and

metadata plus file structures that can be ingested into existing delivery infrastructure (Earth System Grid (ESG)).

-  Currently working with Gary Fu (MODAPS) and many others (including JPL) trying to achieve CF compliance. Tedious/iterative!

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MODIS Data for CFMIP5 (Cloud Feedback Model Intercomparison Project)

•  MODIS Cloud Simulator was developed for COSP (CFMIP Observational Simulation Package)

–  Simulates core MODIS cloud products AND generates L3-like statistics for comparison with MOD08/MYD08.

•  Subsetted monthly L3 files corresponding to simulator output and converted to netCDF

–  Full records (all years) for 35 data sets, Terra and Aqua C5.1 individually, and Terra+ Aqua combined (consistent w/other L3 temporal aggregations). Daytime only (most commensurate w/ simulator).

–  ~0.5 GB/year (per Terra, Aqua, or combined data set) –  Includes netCDF metadata convention (CF compliant) –  Documentation file provided –  Archived at: ftp://ladsweb.nascom.nasa.gov/NetCDF/L3_Monthly/.

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C6 Approach

•  Algorithm development required a test system (not a production system) –  minimize delivery overhead, provide a baseline set of fixed input

data files, fast turn-around of several months including L3 files. Provide on-line tracking of testing and visualization support (B. Ridgway)

•  Science Test Systems for Land / Atmosphere –  Run Atmosphere codes at 30x with online product archive

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June 2011 L1B calibration assessments June-Sept 2011 L2 delivery and testing cycle continues July-Sept 2011 C6 L1B & Cloud Mask reprocessing Sept 2011 FileSpec for L2 products finalized Oct-Nov 2011 L3 delivery and testing Nov-Dec 2011 Final PGE science testing Jan 2012 C6 reprocessing ready to start ? Apr 2012 C6 reprocessing complete

Instrument

•  Band 1, 2, 3 RVS trends.

–  MCST “Approach 2” promising •  Band 8 polarization

–  “Differences between MCST and OBPG calibration methods for C6 are small in terms of DB retrieved parameters.” R. Hansell, C. Hsu

•  Characterization support more necessary than ever to ensure climate quality data records!

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•  Retrieval Issues

–  Spectral effective radius discrepancies [Zhang]

–  3D radiative transfer and role of drizzle [Zhang, Di Girolamo] •  Science Questions

–  Processes: drizzle frequency, cloud processes/evolution [Yuter] –  GCMs have difficulty in forming these clouds [Naud] –  Aerosol retrievals close to clouds [Marshak, Varnai, et al.]

•  Field work

–  A balanced campaign portfolio needs to include these cloud types

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•  Retrieval Issues

Ice Cloud Radiative Models

–  Tuesday workshop held at Goddard with CALIPSO and MODIS team members.

–  Radiative Transfer: Improved scattering calculations [Ping Yang], habits and size distributions [Baum, A. Heymsfeld]

–  IR closure: match TOA window radiance, consistency with IR thin cirrus retrievals (IR not sensitive to habit/roughness) [Heidinger, Yang, Jacques Pelon (CALIPSO IIR)]

–  POLDER direction information [van Diedenhoven, Zhang]

Improved thin cirrus capability –  Quantitative use of 1.38 !m band w/uncertainties [Meyer]

•  Science Questions –  Sensitivity of deep convection to dynamic/thermodynamic history and

aerosols [Wilcox]

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MODIS C5

Gen. mixture Mod. rough

Gen. habit mixture Severely rough

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•  CO and aerosol retrievals, local radiative forcing: David Edwards •  Absorbing aerosol impacts on atmospheric heating and accelerated

snowpack melting in Himalayas/Tibetan Plateau: W. Lau, Kyu-Myong, Ritesh, Hsu, Yasunari

•  The dispersal and evolution of volcanic plumes: Vincent Realmuto

•  Aerosol transport and climatic impacts: Hongbin Yu