P4.18 Drizzle Detection for Maritime Stratocumulus Clouds by Combined Use of TRMM Microwave Imager and Visible/Infrared Scanner

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1 P4.18 Drizzle Detection for Mritime Strtocumulus Clouds y Comined Use of TRMM Microwve Imger nd Visile/Infrred Scnner Hongfei Sho* nd Guosheng Liu Florid Stte University, Tllhssee, FL 6 1. INTRODUCTION* Determining the rditive effects of erosols is currently one of the most ctive res in climte reserch. Evidences demonstrte tht erosols cn ffect the rditive lnce of the Erth y influencing cloud properties. Aerosols ct s condenstion nuclei tht form clouds. As the numer of erosols increses, the wter in the cloud gets spred over mny more prticles. Lrge concentrtions of smll droplets mke these clouds more reflective, nd reduce the effectiveness of colescence t lter stge of cloud development through nrrowing the spectrum of droplet size, then prolong cloud lifetimes. This indirect effect - incresed numer concentrtion of cloud droplets nd prolonged cloud lifetime - re elieved to hve gret impct on glol climte. Precipittion is key component in determining the lifetime nd extent of clouds. It lso is key component in the tmospheric energy lnce through the redistriution of ltent het. Therefore understnding to wht extent tht drizzle is suppressed in the polluted cloud is essentil for us to ssess erosol indirect effect. Although drizzles hve een oserved y ircrft nd surfce-sed cloud rdrs, they cn hrdly e detected y stellite sensors, which cover much roder re nd much longer time period thn ircrft or surfce sed mesurements. As first step in ssessing erosol-induced effect on suppression of precipittion, in this study, we formulte drizzle detection index - Scle Re, sed on stellite microwve nd visile/infrred mesurements.. SCALE Re One of the key vriles tht determine the rditive properties of liquid wter clouds nd reflect the erosol indirect effect is the cloud effective rdius Re (Hnsen nd Trvis 1974), which is defined s the rtio of the third to the second moment of droplet size distriution n(r), i.e., Re = r n( r) dr r n( r) dr (1) * Corresponding uthor ddress: Hongfei Sho Florid Stte University, Dept. of Meteorology, Tllhssee, Florid 1; emil:sor@met.fsu.edu Presently, spce-orne pssive sensors re cple of deriving the effective rdius of clouds from two distinct methods. The first method mkes use of solr reflectnce mesurements t nonsoring visile nd soring nerinfrred frequencies to determine the cloud visile opticl depth (τ) nd the effective rdius of the cloud droplets [herefter referred to s ]. The second pproch uses liquid wter pth (LWP) from microwve nd cloud opticl depth from visile mesurements to infer effective rdius [herefter referred to s ] ccording to the reltionship (see Fig.1): LWP = τ Re () The min differences etween these two methods re: tends to e ised towrd n effective rdius somewhere ner cloud top while is mesurement of n verge droplet rdius over the whole cloud lyer. Becuse retrievl relies on sorption t the ner-infrred, photons t this frequencies do not penetrte clouds s deep s those t microwve nd visile frequencies. On the other hnd, is derived from LWP nd τ; oth of them re integrl quntities of the cloud. The difference etween nd is therefore le to reflect the verticl inhomogeneity of prticle size inside the cloud. For exmple, if >, it indictes tht the effective rdii increse with height; if <, profile tht effective rdii decrese with height could e inferred. Generlly, for wrm cloud, 1) t the cloud formtion stge cloud droplets grow y condenstion, effective rdius increses with height nd reches mximum ner the top; ) t precipittion formtion stge reltively lrge droplets (lrger thn micrometers in rdius) fll through the cloud nd grow y colescence, then effective rdius increse with the decrese of height nd rech mximum ner or elow the cloud se. Tht is, for non-precipitting clouds the rtio of to is less thn unity, while for the precipitting clouds the rtio exceeds unity. Therefore, we introduce scled Re s drizzle index [herefter referred to s Re(DI)] to discriminte whether cloud is precipitting or not: Re( MW ) Re( DI ) = Re( MW ) () Re( SR) Re(DI) consists of two terms: 1) the second term

2 of the right hnd of Eq.() is rinfll informtion term, ecuse is mesurement of n verge droplet rdius so tht it hve some sensitivity to droplets growth even though the precipittion occurs; ) the first term is modultion term which cn mplify rinfll informtion coming from, ecuse s discussed ove, when precipittion occurs the rtio will e greter thn 1. Therefore Re(DI) is expected to e cple of the drizzle detection. Using Eq.(), the Re(DI) cn e further expressed s: LWP( MW ) Re( DI ) = Re( MW ) (4-) LWP( SR) LWP ( MW ) or Re( DI ) = (4-) τ Re( SR) where LWP(MW) is liquid wter pth derived from microwve mesurement nd LWP(SR) is LWP inferred from τ nd with Eq.(). Now, we hve three different forms of effective rdius:, nd Re(DI). To etter understnd wht different ehviors nd different physicl menings they hve in cloud formtion nd precipittion stges, we used rditive trnsfer models [SBDART model (Ricchizzi et l., 1998) for visile/infrred, nd MWRT model (Liu, 1998) for microwve] to do the following simultions. In ech simultion, we ssume uniform profile of the cloud opticl depth τ ut linerly incresing (or decresing) profile of effective rdius. Fig. shows LWP(SR) vs. LWP(MW). Note tht the rtio of LWP(MW) to LWP(SR) equls to the rtio of to [ref. Eq.() nd Eq.(4)], we hve: 1) When Re is verticlly uniform (open circles in oth Figs. nd ), the rtio term LWP(MW)/LWP(SR)=1. When Re increses with height (Fig.), the rtio<1. When Re decreses with height (Fig.), the rtio>1. ) For the sme Re profile, the solute difference etween LWP(MW) nd LWP(SR) increses with τ (or LWP) in oth Figs. nd, ut the rtio for Re-incresing profiles (Fig.) doesn t chnge s much s tht for Re-decresing profiles (Fig.). ) For different Re profiles ut the sme LWP, in Fig. the rtio is lmost constnt no mtter in wht rte the Re increses with height, nd points closely locte long the fitting function Y=1.6X 1., ut in Fig. the points re sustntilly prt from ech other. The resons lie in: 1) When effective rdius vries linerly with the height, the verge effective rdius Re(vg) cn e otined y: Re( vg) Re( top) / if increses Re( vg) = (1 + α) Re( top) / if decreses Where, α = Re(tm)/Re(top), Re(top) nd Re(tm) re the effective rdius t the top nd ottom of cloud respectively. ) is proxy of effective rdius t level ner the cloud top. How fr wy this level from the cloud top depends on the cloud opticl depth; the smller the τ is, the deeper into the cloud. On the other hnd, is good pproximtion of Re(vg). Therefore, for Re-incresing profiles, the rtios re in the rnge of (.5,1) slightly depending on τ. For the Re-decresing profiles, the rtio > 1 nd the lger the α (or τ) is, the igger the rtio will e. LWP(SR) [kg m - ] LWP(SR) [kg m - ] Re(tm)=6µm τ=1,48,1 Re(top)= 6 Re(top)=1 Re(top)=14 Re(top)=18 LWP(SR)=1.6LWP(MW) LWP(MW) [kg m - ] Re(top)=4µm τ=1,48,1 Re(tm)=4 Re(tm)=48 Re(tm)=7 Re(tm)= LWP(MW) [kg m - ] Fig. Computed LWP(SR) vs. LWP(MW) with τ vrying from 1 to 48 with step of 1, () when Re linerly incresing with height, nd () when Re linerly decresing with height. Profiles of Re re given y the Re(top) nd Re(tm) which donte Res t the top nd the ottom of the cloud, respectively. Also shown the est fit for the Re-incresing cse (dsh line).

3 Figure shows the verticl loctions t which, nd Re(DI) correspond to the effective rdii. It lso shows how the rtio term vries profile y profile t τ=6. Height (km) Height (km) Rtio=.86 Rtio=.8 Rtio=.76 Re(DI) Effective Rdius (µm) Re(DI) Rtio=1.7 Rtio=1.7 Rtio= Effective Rdius (µm) Fig. Illustrtion of the verticl loctions t which, nd Re(DI) correspond to the effective rdii t τ=6. The Re profiles re sme s Fig. () for Re-incresing cse, () for Re-decresing cse. Also shown is the rtio for ech profile.. CASE STUDY VIRS nd TMI Dt from the Tropicl Rinfll Mesurement Mission (TRMM) stellite re used in this study. The reflectnces t.6 µm nd 1.61 µm VIRS chnnels re used to retrieve cloud opticl depth nd effective rdius t the solr wvelengths. A new microwve lgorithm is developed to derive cloud liquid wter pth LWP(MW) from 19 nd 7 GHz frequencies. Since TMI hs lrger footprints thn VIRS, the VIRS cloud retrievls re convolved with the TMI ntenn pttern function to produce new VIRS pixels with the sme footprint size of TMI s. Thus they re collocted with the ctul TMI pixels. To void em-filling error, only completely overcst pixels re selected. Additionlly, pixels with cloud top temperture colder thn 7 K re excluded in the nlysis to void ice scttering. Two cses were chosen for the cse study. In Fig.4, the VIRS chnnel 4 imge shows two clusters of strtiform cloud with uniform wrm cloud-top temperture (green color) over the By of Bengl t 9: UTC, 1 Ferury And the verticlly integrted rinrte from TRMM PR (Fig.5) shows tht the cse ws ssocited with moderte rin ut in the re of cse1 there ws no pprecile rinfll signl. It should e mentioned here tht the possiility of the light rinfll, i.e. drizzle, cnnot e excluded ecuse drizzle signl is lower thn the minimum detectle rdr reflectivity fctor 17dBZ. LWP(SR) (kg m - ) LWP(SR) (kg m - ) Re(DI) µm to 6 6 to 1 1 to 1 1 to to to to 6 LWP(SR)=1.6LWP(MW) Re(DI) (µm) 7 to to 5 5 to to to to 1 1 to to 5 LWP(SR)=1.6LWP(MW) 1. LWP(MW) (kg m - ) LWP(MW) (kg m - ) Fig.6 Shows the sctter digrm of LWPs retrieved from TMI nd VIRS mesurements with the clssified Re(DI). () for the drizzle cse, () for moderte rin cse. A fitting line s discussed in section, LWP(SR)=1.6LWP(MW) 1., is lso indicted

4 Figure 6 shows the sctter digrm of LWPs retrieved from TMI nd VIRS mesurements with the clssified Re(DI). A fitting line s discussed in section, LWP(SR)=1.6LWP(MW) 1., is lso indicted in the figures. The results re summrized s follows: 1) Below LWP(MW)=.kgm -, which is usully the criticl vlue for strtocumulus to precipitte, points sctter long the fitting line. Aove LWP(MW)=.kgm - points devite from the fitting line nd end to higher LWP(MW). These ehviors re consistent well with the model simultions given in the Fig.. In the Fig.6 the LWP(SR) leveled off round LWP(SR)=.8kgm -, the similr chrcter eing indicted y the model simultion t Re(top)=4µm (Fig.). ) When Re(DI)>1µm nerly ll the points re t the right side of the fitting line nd t Re(DI)=1µm points sctter round the fitting line. It suggests tht Re(DI)=1µm is threshold for precipittion. Becuse for the most clouds the rtio of to is ~.8 (Msung, 1) [lso shown in Fig.], this threshold is consistent with the threshold of ~ 15µm, which is often cited s the precipittion threshold in previous studies (Rosenfeld, ). ) Since Re(DI) keeps incresing s the points end to higher LWP(MW), Re(DI) my hve cpility to estimte rinrte, in prticulr the rinrte of drizzles, whose signl is too wek to e detected y TRMM PR. Fig.7 shows the Re(DI), nd s function of verticlly integrted rinrte within TMI pixel. Also shown the correltion coefficient etween rin rte nd these effective rdii. 5 Correltion coefficient Re(DI):.64 :.58 :.4 From Fig.7, it shows: 1) When rinrte >, the Re(DI) increses with rinrte in greter pce thn the other two Res due to the mplifiction fctor /. As result, its correltion with rinrte is greter thn the other two. ) At the rinrte =, points re congested nd overlpped. It indictes tht while the precipittion informtion is mplified in Re(DI) with the scle proportionl to the rinrte ut the precipittion threshold is not. 4. SUMMARY AND CONCLUSIONS In this pper, we introduced scled effective rdius s drizzle index. Bsed on model simultions nd nlysis of TRMM stellite dt, we demonstrted tht this index is cple to infer oth cloud microstructure nd precipittion over lrge re. The conclusions cn e summrized s follows: 1) While is n estimtion of the effective rdius somewhere ner the cloud top nd is verge effective rdius over the whole cloud lyer, Re(DI) represents the effective rdius t the lower portion of the cloud lyer. ) For non-precipitting clouds with LWP <. kg m -, the rtio of to rnges from.85 to 1 nd is insensitive to the rte t which Re increses with the height. For precipitting clouds, the rtio of to is greter thn 1 nd is positively correlted with rinrte. ) Modulted y the rtio of to, the scled Re, Re(DI), hs greter sensitivity to precipittion. References Effective Rdius (µm) Hnsen, J.E., nd L.D. Trvis Light scttering in plnetry tmospheres. Spce Sci. Rev. 16, Ricchizzi, P, S. Yng, C. Gutier, nd D. Sowle, 1998: SBDART: A reserch nd teching softwre tool for plne-prllel rditive trnsfer in the Erth s tmosphere, Bull. Amer. Meteor. Soc., 79, Liu, G., 1998: A fst nd ccurte model for microwve rdince clcultions. J. Meteor. Soc. Jpn, 76, Verticl Integrl Rin Rte in TMI Pixel (mmh -1 ) Msung, H., T. Y. Nkjim, T. Nkjim, M. Kchi, R. Oki, nd S. Kurod, 1: Physicl Properties of Mritime Low Clouds s Retrieved y Comined Use of TRMM Microwve Imger nd Visile/Infrred Scnner. I. Algorithm, J. Geophys. Res., (Pper I) Fig.7 Re(DI), nd s function of verticl rin rte for the cse. Also shown correltion coefficient etween the rin rte nd Res (in legend). Rosenfeld, D., : Suppression of rin nd snow y urn nd industril ir pollution, Science, 87,

TRMM VIR 1B1 DATA TRMM TMI 1B11 DATA 1st method LWP = τ Re nd method τ LWP(MW) Re( MW ) LWP ( MW ) Re( DI ) = Re( MW ) = Re( SR) τ Re( SR) Figure 1 The scheme to compute the, nd Re(DI) nd their

5 TRMM VIR 1B1 DATA TRMM TMI 1B11 DATA 1st method LWP = τ Re nd method τ LWP(MW) Re( MW ) LWP ( MW ) Re( DI ) = Re( MW ) = Re( SR) τ Re( SR) Figure 1 The scheme to compute the, nd Re(DI) nd their reltionship T (K) of VIRS Ch.4 [Fe ] Cse 1 Cse --- Along-trck Direction --> Figure 4 TRMM VIRS chnnel 4 Imge t 9: UTC on 1 Ferury 1999, showing two clusters of strtiform cloud with uniform wrm cloud-top temperture (green color) over the By of Bengl. The two prllel dsh lines delimit the km PR swth. The swth is oriented northwest to southest. the integrl of rin rte from rin top to rin ottom (mmh -1 ) to 1 1 to to to 5 5 to 1 1 to to 5 5 to Along-trck Direction --> Figure 5 Sptil distriution of verticlly integrted rinrte long the PR swth. Sme time s in Fig.4

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