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A New Global Data of Cloud Vertical Layers and Implications for Model Simulations

Zhanqing Li Department of Atmospheric and Oceanic Science & ESSIC University of Maryland Fu-Lung Chang National Institute of Aerospace (NIA). A New Global Data of Cloud Vertical Layers and Implications for Model Simulations. JCSDA Science Workshop, May 31-June 1, 2006, MD.

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A New Global Data of Cloud Vertical Layers and Implications for Model Simulations

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  1. Zhanqing Li Department of Atmospheric and Oceanic Science & ESSIC University of Maryland Fu-Lung Chang National Institute of Aerospace (NIA) A New Global Data of Cloud Vertical Layers and Implications for Model Simulations JCSDA Science Workshop, May 31-June 1, 2006, MD

  2. Do we have a sound global cloud data in terms of cloud vertical structure and cloud optical properties? • To what extent do cirrus clouds overlap with lower-level clouds on a global scale? • How much artifact and uncertainty exist in in current satellite and model simulation cloud products? Science Questions

  3. Satellite cloud properties •  Model validation (Zhang et al. 2005, JGR) Status of Model Simulation of Cloud-Layering

  4. Status of Satellite Remote Sensing of Cloud-layering • Both MODIS and ISCCP cloud retrieval algorithms are applied to April 2001 Terra/MODIS L1B radiance data.

  5. ISCCP and conventional methods: • Use a single IR-window • channel (11 m) • MODIS: • Use multi-spectral • IR sounding channels • (11-14.3 m) Determination Cloud Top Altitude from Satellite

  6. 11-m IR temperature • uppermost (CO2-slicing) cloud-top temperature • 0.65-m cloud VIS optical depth high cloud low cloud Principles of Our New Method high cloud low cloud

  7. Lookup-table radiances are generated based on an ice-over-water cloud radiative transfer calculations. Algorithm (Chang and Li 2005, JAS)

  8. High1- single-layer cirrus cloud (IR < 0.85); High2 - overlapped cirrus cloud (IR < 0.85); High3 - thick high cloud (IR  0.85); Low1- single-layer lower cloud; Low2 - overlapped lower cloud; *High2 and Low2 are retrieved simultaneously. Classification of Cloud Categories

  9. Validation is based on comparisons with the Active Remote Sensing Cloud Locations (ARSCL) data from DOE/ARM. • Overlapped cirrus clouds (open points) and low clouds (filled points) are validated during March-November 2001 by comparing the ARSCL and our cloud-top pressures (a) and cloud-top temperatures (b). Validation over the ARM SGP Site

  10. A Distinct Bimodal Distribution of High and Low Clouds

  11. Apr.-Nov. 2001 at SGP Apr.-Nov. 1999 at NAU A Distinct Bimodal Distribution of High and Low Clouds

  12. Cloud Top Pressure Cloud Top Temperature Cloud Optical Depth Zonal-mean Cloud Properties

  13. January 2001 April 2001 Our Low Cloud Amount July 2001 October 2001

  14. January 2001 April 2001 Mid Cloud Amount (Including 440-680 mb) July 2001 October 2001

  15. January 2001 April 2001 Total High Cloud Amount (High1/High2/High3) July 2001 October 2001

  16. January 2001 April 2001 Overlapped Cloud Amount July 2001 October 2001

  17. Our MODIS retrievals with overlapping MODIS data (Collection 4) Retrievals from the Visible-IR method H H H M M M Comparing High, Mid, and Low Cloud Amounts L L L H: < 440 mb, M: 440 mb-680 mb, L: > 680 mb

  18. Probability of Cloud Occurrence Layer Cloud Amount Ours MODIS Comparing Ours, MODIS and ISCCP Cloud Layer Structures ISCCP like

  19. Comparing Zonal-mean High/Mid/Low Cloud Amounts

  20. Comparing Cloud-Top/Cloud-Optical-Depth Joint Distributions • All MODIS, ISCCP, and our cloud retrieval algorithms are applied to April 2001 Terra/MODIS L1B radiance data.

  21. Evaluating Cloud Fields Generated by the NCEP Models • Implement and validate our retrieval algorithm • Get cloud data from the model for selected days & months • Retrieve cloud properties from MODIS satellite • Comparing cloud layers derived from satellite and models • Quantify major discrepancies • Study the causes for the discrepancies

  22. To date, most satellite and modeling cloud algorithms adopt a single-layer cloud assumption, which cannot deal with cloud overlap situation. • For cirrus overlapping low clouds, conventional IR method tends to detect them as single-layer mid-level clouds; while MODIS treats them as single-layer high-thick clouds. • Our results show relatively ~30% more low clouds than the MODIS operational product owing to cloud overlaps. • Our cloud layer structure shows a distinct bimodal high-and-low cloud distribution with minimum cloudiness near 500-600 hPa, • ISCCP does not show the distinct cloud layer structure. Yet, it has a lot less high and low clouds, but more mid-clouds. Conclusions

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