Aerosols, Dust and High Spectral Resolution Remote Sensing

Transcription

1 Aerosols, Dust and Hgh Spectral Resoluton Remote Sensng Irna N. Sokolk Program n Atmospherc and Oceanc Scences (PAOS) Unversty of Colorado at Boulder rna.sokolk@colorado.edu

2 Goals and challenges MAIN GOALS: establsh a framework for the development of a new physcallybased treatment of mneral dust for IR hyperspectral remote sensng based on ths framework, analyze NAST-I arcraft spectra acqured over the East Chna Sea regon durng Sprng of 2001 to dentfy the spectral radatve sgnature of Asan dust MAIN CHALLENGES: a common look-up table approach used for aerosol retrevals from narrow-band sensors (e.g., MODIS) wll not work for hgh spectral resoluton observatons n the IR A need for new conceptual approaches

3 Effect of the dust mxture and loadng on brghtness temperature (US 1976 Standard Atmosphere, observaton at 100 km, averagng ν = 0.5 cm -1, dust n the lowest 2.5 km) LBLRTM+DISORT Clear sky (Sokolk, GRL, 2002) dust causes a negatve slope

4 YEAR 1 ACTIVITIES Development of new aerosol models: Developed and tested new hgh resoluton optcal models of Asan dust and several ndvdual aerosol speces. The models were ncorporated nto a new database called HROMAA (Hgh Resoluton Optcal Models of Atmospherc Aerosols) avalable onlne to the MURI Team: Forward modelng&senstvty studes: Lnked kcarta and DISORT that was modfed to handle the new aerosol models. The code was used to perform forward modelng to determne the senstvty of IR hghresoluton spectral radances to varous dust characterstcs (such as dust composton, vertcal dstrbuton, partcle szes, etc.). The man goal was to test robustness of a negatve slope approach for the detecton of dust from hgh spectral resoluton sensng. NAST-I data analyss: Receved NAST-I raw data from the Smth group and started to work on the analyss of spectra acqured over the Yellow Sea n sprng of Collected and analyzed varous data (meteorologcal, satellte, ldar network, etc.) avalable for ths tme perod over East Asa to support the analyss of NAST-I data. Examnaton of Asan dust outbreaks based on observatonal data and MM5 smulatons has been started.

5 Hgh Resoluton Optcal Models of Atmospherc Aerosols (HROMAA)

6 Hgh Resoluton Optcal Models of Atmospherc Aerosols (HROMAA) Optcal propertes of ndvdual aerosol speces: Normalzed extncton coeffcent K ext (per unt number concentraton; need N(Z) to get the profle of aerosol optcal depth); Sngle scatterng albedo ω 0 Asymmetry parameter g Optcal propertes of the external mxture of several aerosol speces: ω 0 = ω 0, N N K K ext, ext, mxture K ext = N K ext, g = g N N K K sc, sc,

7 Normalzed extncton coeffcent mx1(50s+50kao ) mx2(75s+20kao +5Hem) mx3(20s+75kao +5Hem) KextKaol2_05 KextSO2_

8 Effect of dust coatng Imagnary part of the effectve refractve ndex Refractve ndex of mneral aggregates-water mxtures (Curves 1-4 are for water volume fracton 10%, 50%, 90%, and 100%, respectvely) wavelength, um

9 Effect of dust partcle szes D eff = 1.72 µm D eff = 2.44 µm kcarta+disort, resoluton= cm -1

10 Effect of the vertcal profle of dust on brghtness temperature We performed a seres of modelng experments for several vertcal profles of dust The vertcal profles were reconstructed based on arcraft and ldar observatons In each experment, dust propertes remans the same but the poston of a dust layer vares

11

12 Effect of the vertcal profle of dust on brghtness temperature clear Dust layer P= mb Dust layer P= mb Dust layer P= mb kcarta+disort, resoluton=0.25 cm -1

13 Effect of the vertcal profle of dust on brghtness temperature Moderate dust loadng Effect of the vertcal profle of dust on brghtness temperature kcarta+disort, resoluton=0.25 cm -1

14 Effect of the vertcal profle of dust on brghtness temperature kcarta+disort, resoluton=0.25 cm -1-1

15 Sub-vsble crrus spectral sgnature

16 Dscrmnaton of dust from clouds: problems n MODIS cloud mask Black-cloud, whte clear

17 Effectve cloud partcle szes Red color denotes larger partcles (30 µm) ; Blue color denotes small partcles (< 10 µm). MODIS algorthm does not dscrmnate between cloud and dust partcles t treats a dust layer as a cloud wth smaller partcle szes

18 Contnue forward modelng studes: * How to handle dust scatterng: Summary and work for Year 2 Heney-Greensten vs. actual scatterng phase functons * Mult-layered vertcal dstrbuton * Varatons n the vertcal profles of T and atmospherc gases (H 2 O) Dust retrevals: * Test retreval algorthms usng NAST-I data Strategy: use forward modelng as a pror to constran the retrevals

19 Some ssues Dust causes addtonal heatng/coolng of a layer => affects T and H 2 O profles Potental problems: a radosonde clmatology of T and H 2 O profles n the dust laden condtons s lmted

20 2 th Internatonal Workshop on Mneral Dust September, 2003 Pars, France