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.

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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

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 Goals of the Investigation

 MOD08/MYD08 ice cloud properties ( , D e, , T b ) over the tropics from MODIS measurements (King et al., 2003; Platnick et al., 2003)  Data from 3 years: 9/ /2005 Note: Poster of ice cloud properties based on the MODIS and  m bands, following Gao et al. (2002) and Dessler and Yang (2003). Data

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 Ice Cloud Classification

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– 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 ISCCP Cloud Classification

MAS BTD[8.5-11] Deep convection Thick cirrus Thin cirrus Thick Cirrus 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 BTD[  m] for deep convective case from CRYSTAL- FACE case study BTD[  m] for deep convective case from CRYSTAL- FACE case study

Terra Aqua Geographical Distribution of Ice/Cirrus Cloud Fraction

Terra Aqua Geographical Distribution of Cloud Fraction

Terra Aqua Geographical Distribution of Ice/Cirrus Cloud Fraction

Cirrus and Deep Convection, over Ocean

Cirrus and Deep Convection, over Land

Ice Cloud: 30N to 30S; 3 years

Cloud Fraction

Cloud Optical Thickness

Cloud Effective Radius

Seasonal Variations of Ice Clouds

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)

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

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

Preliminary Comparison June 2003, MODIS vs ECMWF

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

Ice Cloud Optical Thickness MODIS — Southern AfricaMODIS — West Pacific ECMWF — Southern AfricaECMWF — West Pacific

Ice Cloud Effective Emissivity MODIS — Southern AfricaMODIS — West Pacific ECMWF — Southern AfricaECMWF — West Pacific ECMWF — Southern AfricaECMWF — West Pacific

Ice Cloud Top Temperature MODIS — Southern AfricaMODIS — West Pacific ECMWF — Southern AfricaECMWF — West PacificECMWF — Southern AfricaECMWF — West Pacific

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). Summary