Properties of Tropical Ice Clouds: Analyses Based on Terra/Aqua Measurements

1. Properties of Tropical Ice Clouds: Analyses Based on Terra/Aqua Measurements P. Yang, G. Hong, K. Meyer, G. North, A. Dessler Texas A&M University B.-C. Gao Naval Research Laboratory B. Baum NASA Langley Research Center Baltimore, MD January 05, 2006

2. Goals of the Investigation This is a work in progress We are attempting to establish links with the numerical modelling community to make use of the global satellite cloud products In this talk, I will focus on the following points: • Geographical distributions and seasonal variations of ice clouds • Relationship between cirrus clouds and deep convections • PDFs and CDFs of cloud properties • Comparison of the ice cloud properties derived from MODIS measurements and those from ECMWF simulations

3. Data • MOD08/MYD08 ice cloud properties (, De, , Tb) over the tropics from MODIS measurements (King et al., 2003; Platnick et al., 2003) • Data from 3 years: 9/2002 - 8/2005 Note: Poster of ice cloud properties based on the MODIS 0.66- and 1.375-m bands, following Gao et al. (2002) and Dessler and Yang (2003).

4. Ice Cloud Classification • In the literature, it is common to use the term “Cirrus Clouds” as a synonym of “Cirroform clouds” or “ice clouds” (e.g., Liou 1986, Fu et al. 1992…) • WMO: Cirrus, Cirrocumulus, and Cirrostratus based on visual appearance during daytime • Classification based on visible optical thickness: subvisual cirrus,  < 0.03 (Sassen et al., 1998) thin cirrus, 0.03 <  < 0.3 thick cirrus, 0.3 <  • Cirroform clouds based on ISCCP: Cirrus,  < 3.6 Cirrostratus, 3.6<  < 23.0

5. ISCCP Cloud Classification Cirrus • < 3.6 and Cloud top < 440 mb Cirrostratus 3.6<  < 23.0 and Cloud top < 440 mb Deep convection 23.0 <  and Cloud top < 440 mb We will use the ISCCP classification system for our analyses because modelers are familiar with it. Rossow and Schiffer, 1999, Advances in understanding clouds from ISCCP.Bull. Amer. Meteor. Soc., 80, 2261–2287.

6. BTD[8.5-11 m] for deep convective case from CRYSTAL-FACE case study Below: CPL (Cloud Physics lidar) and CRS (Cloud Radar System) data with MODIS BTD color-coding Note: CPL data consistently places cirrus heights above CRS MAS BTD[8.5-11] Thick Cirrus Thick cirrus Thin cirrus Thin cirrus Deep convection

7. Geographical Distribution of Ice/Cirrus Cloud Fraction Terra Aqua

8. Geographical Distribution of Cloud Fraction Terra Aqua

9. Geographical Distribution of Ice/Cirrus Cloud Fraction Terra Aqua

10. Cirrus and Deep Convection, over Ocean

11. Cirrus and Deep Convection, over Land

12. Ice Cloud: 30N to 30S; 3 years

13. Cloud Fraction

14. Cloud Optical Thickness

15. Cloud Effective Radius

16. Seasonal Variations of Ice Clouds

17. Ice Cloud from ECMWF Cloud phase and ice cloud top • Using Model-to-Satellite method (Morcrelle, 1991) to mitigate comparing properties incorrectly Cloud optical thickness • Directly derived from ECMWF Cirrus, cirrostrauts, deep convection • Classification based on cloud top and optical thickness (in terms of the ISCCP definition)

18. IWC, LWC profiles Atmospheric profile ECMWF Outputs IWC: Ice particle scattering database (Yang et al., 2005) LWC: Mie code Clear sky gaseous abs. MODTRAN (Berk et al, 1989) Mixed-phase Cloud (Yang et al, 2003; Lee et al, 2005) DISORT (Stamnes et al., 1988) BT at channels (m) 8.5, 11.0, 12.0, 13.34 13.64, 13.94, 14.24 Cloud Phase and Top from ECMWF

19. Comparison of Ice Clouds Derived from ECMWF and MODIS IWC, LWC from ECMWF BTs at 8.5, 11.0, and 12.0 m derived from ECMWF BTs at 11.0, 13.34, 13.64, 13.94, and 14.24 m derived from ECMWF Ice De=60 m Water De=20 m Cloud phase (Baum et al, 2000) Cloud top CO2 slicing technique (e.g., Wylie et al, 1986) Cloud optical thickness from data base (Yang et al, 2005) ISCCP Classification Ice cloud (cirrus, cirrostratus, deep convection) ISCCP Classification MODIS level-3 1°1° daily ice cloud products (http://modis.gsfc.nana.gov)

20. Preliminary Comparison June 2003, MODIS vs ECMWF

21. Ice Cloud Fraction MODIS — Southern Africa MODIS — West Pacific ECMWF — Southern Africa ECMWF — West Pacific

22. Ice Cloud Optical Thickness MODIS — Southern Africa MODIS — West Pacific ECMWF — Southern Africa ECMWF — West Pacific

23. Ice Cloud Effective Emissivity MODIS — Southern Africa MODIS — West Pacific ECMWF — Southern Africa ECMWF — West Pacific ECMWF — Southern Africa ECMWF — West Pacific

24. Ice Cloud Top Temperature MODIS — Southern Africa MODIS — West Pacific ECMWF — Southern Africa ECMWF — Southern Africa ECMWF — West Pacific ECMWF — West Pacific

25. Summary Reported on work in progress to put regional/global cloud properties in terms that a modeler may find useful. In working with global cloud properties, we - investigated the relationship between cirrus clouds and deep convections - want to find a way to provide PDFs to global modelling community - also want to build links to data assimilation community - compared MODIS measurements and ECMWF simulations (this work is --still ongoing).