A new method of CDOM absorption in China east coastal waters

Transcription

1 new method of COM bsorption in Chin est costl wters XINGGUNG ZHNG, YONGSHENG XU* Institute of Ocenology Chinese cdemy of Sciences 7 Nnhi od, Qingdo, Shndong, CHIN E-mil: yongsheng.xu@qdio.c.cn bstrct: - he Chin est costl region contins some turbid costl wters. For turbid wter, stndrd MOIS dt processing(e.g. tmospheric correction) often produces significnt errors in the derived ocen color products due to significnt ocen wter-leving rdince contributions t the two NI bnds(748 nd 869nm). In this pper, we propose novel lgorithm to estimte COM in costl wters from the remote sensing dt. he terrestril originted COM is observed nd distributed in the river runoff nd long the cost of the Chin min lnd. Since 007, the short expeditions using fishing bots hve been conducted in the Qingdo By nd the Ximen By in Chin. hrough these expeditions, wters re smpled to determine chlorophyll- concentrtions, nutrients, COM, s well s the C profiling of temperture, slinity, nd photo-syntheticlly vilble irrdince. he correltion, single regression nd multiple regression nlysis were pplied to build new lgorithm to estimte COM from the trditionl COM, the in-situ COM, the remote sensing visible reflectnce, nd the yleigh-corrected rdince t the top of the tmosphere. Key-Words: - Colored dissolved orgnic mtter bsorption; yleigh-corrected rdince; urbid wter; Correltion nlysis; Single regression; Multiple regression 1 Introduction Colored dissolved orgnic mtter (COM), opertionlly defined using the bsorption coefficient of the mteril tht psses through 0.μm filter, is strong bsorber of ultrviolet rdition [1] nd the precursor of mny photochemicl rection []. uring the lst two decdes, number of reserchers hve developed lgorithms to relte remotely sensed properties to in situ bsorption by COM or to the concentrtion of dissolved orgnic crbon (OC). In 006 [3-4], severl semi-nlyticl lgorithms hd been proposed to derive inherent opticl properties (IOP) from the remote sensing reflectnce spectrum. In 010 [5], the normlized wter-leving rdinces t eight wve bnds within the UV nd visible spectrl domins were used to find the reltionship between the UV, violet, or blue/green wve bnd rtios of the normlized wter-leving rdinces nd surfce totl chlorophyll concentrtion nd CM bsorption. From the bove, we cn esily find the following phenomen: (1) ll the empiricl reltionships hevily depend on in situ rdiometric mesurements. ctully, these methods re not the direct wy. First, it is not esy to get the in situ rdiometric dt of our interested re ISBN:

2 on time; Second, indirect method will mke the whole system complex nd led to big system noise. () Most lgorithms re subject to tmospheric correction, especilly, in costl wter re. Methods.1 pproch In 1983 [6] nd 199 [7], Gordon nd iken used the wvelength rtio pproch to predict chlorophyll concentrtion in surfce wters, nd imges of globl ocen chlorophyll concentrtions re now produced routinely. MOIS does not hve UV detectors; tmospheric interference mkes direct stellite mesurements of UV upwelling rdince from the ocen extremely difficult. But, it seems resonble to pply the visible rdince rtio method to the UV, since the components of sewter which bsorb UV rdition lso bsorb visible rdition. o retrieve the ocen opticl nd biologicl properties from stellite mesurements, the rdince tht re contributed from tmosphere nd the ocen surfce must be ccurtely removed. his is known s tmospheric correction [8]. ypiclly, the top of the tmosphere (O) rdince t cn be linerly prtitioned into vrious physicl contributions [9]: Where stellite, = t W + t F + t( λ) t G (1) is the totl rdince received t the is the diffuse trnsmittnce, trnsmittnce, G is sun glint, nd, nd re respectively the tmospheric yleigh, erosol nd mixed yleigh-erosol scttering terms. We cn simplify (1) to the following simple one by ignoring the whitecp nd sun glint terms: = t + + () W Where is erosol (including yleigh-erosol interctions) scttering term. s we ll know, for the turbid ocen wters, we cn esily get yleigh scttering term from yleigh lookup tble, but the stndrd tmospheric correction lgorithm leds to n over-estimtion of erosol (including yleigh-erosol interctions) scttering term nd n under-estimtion of the derived wter-leving rdince in the visible. In some costl wter regions, negtive rdince will be found in the short visible bnds. im t two phenomen of previous works in the first prt, this pper dopts the following strtegies: (1) We substitute yleigh-corrected rdince for wter-leving rdince to void the tmospheric correcting filure in costl wter re. he yleigh-corrected rdince cn be written s: = (3) () We use direct method to get the reltionship between stellite remote sensing dt nd COM bsorption coefficient just using the wvelength rtio of MOIS yleigh-corrected rdince nd in situ COM dt. W is wter-leving rdince, F is the. In Situ COM t rdince reflected by fom, t is the bem Four cruises were undertken in Qingdo by nd Ximen by in September 007 nd Februry 009. ISBN:

3 t ech sttion, wter ws collected from the surfce (0m depth) nd 10m depth. Wter smples were filtered to remove prticles, including bcteri. ll wter smples of four cruises were filtered through 0.0µm nucler pore filter on return to the lb. Spectrl bsorption ws mesured in Cry 100/300 UV-VIS spectrophotometer, blnked ginst distilled wter. Spectrl bsorption, COM (dimensionless) ws mesured from 00nm to 800nm in 007 nd from 50nm to 800nm in 009. he COM vlues were converted to bsorption coefficient, COM (m -1 ), ccording to the reltion: COM COM ( λ ) =.303 (4) l Where l is the pth length of the spectrophotometer cell (m) nd l=0.1m. 3 esults 3.1 Find the Suitble tios for COM SeS processing softwre is used here to get yleigh-corrected rdinces t 9 ocen color bnds of MOIS nd we cn get 36 rtios 9 9! 9 8 ( C 9 = P = = = 36 ) using the 9!! (9 )! 1 Fig. 1. he reltionship between In-situ COM nd the yleigh-corrected rdince rtio From Figure 1, we cn get the first pek nd the second pek, the big one is smll one is nd the. In Figure 1, the rtio which hs big correltion coefficient will contin more COM informtion. We cn get better COM estimtion by using these rtios with high correltion coefficients. his pper provides two proposls in 3. nd 3.3 using single regression nd multiple regression. 3. Proposl I: Using One tio to Estimte COM We choose the biggest pek rtio to estimte COM bsorption coefficient. yleigh-corrected rdinces. In situ COM bsorption coefficient t ech of 33, 338 nd 380nm is plotted ginst these 36 rtios of visible yleigh-corrected rdince in Figure 1 s following: Fig.. iner egression of one rtio method ISBN:

4 Using single regression method, we cn get the equtions of the best fit regression lines to the costl wter dt s following: COM COM COM (33) = (338) = (380) = ; ; ; = (5) = = Using eqution (5), we cn get the comprisons of mtch-up dt of COM t ech of 33, 338 nd 380nm derived from MOIS stellite imgery nd mesured in-situ s following: COM COM COM (33) = (338) = (380) = (6) Using eqution (6), we cn get the comprisons of mtch-up dt of COM t ech of 33, 338 nd 380nm derived from MOIS stellite imgery nd mesured in-situ s following: Fig. 4. Comprisons of COM derived from two rtios method nd mesured in-situ Fig. 3. Comprisons of COM derived from one rtio method nd mesured in-situ We cn lso get the stndrd devition between COM derived from MOIS nd In-situ COM: S(33)=0.93 S(338)= S(380)= Proposl II: Using wo tios to Estimte COM Using multiple regression method, we cn get the equtions of the best fit regression lines to the costl wter dt s following: We cn lso get the stndrd devition between COM derived from MOIS nd In-situ COM: S(33)= S(338)=0.143 S(380)= Conclusion direct method reported here my be used to estimte COM bsorption coefficients from remotely sensed visible yleigh-corrected rdince rtio. From the stndrd devition between COM derived from MOIS nd In-situ COM, we cn find tht two rtios method is much better thn one rtio method. But, the computtionl complexity of one rtio method bsed on single regression is much lower thn two rtio method bsed on multiple ISBN:

5 regression. So, one rtio method is better if we focus on rel-time COM estimtion in smll costl wter re nd two rtios method will be good if we wnt to get the ccurte COM prediction within lrge costl wter re. cknowledgements We would like to thnk Stte Key bortory of Ocen emote Sensing of Ocen University of Chin nd Stte Key bortory of Mrine Environmentl Science of Ximen University for help with the cquisition of in situ COM dt. he reserch project for sustinble development of economic nd socil structure dependent on the environment of the estern cost of si in Jpn provided funding for this reserch. lso, the uthor would like to thnk the nonymous reviewers for their vluble comments tht helped to improve the pper. his work is supported by the Ntionl Nturl Science Foundtion of Chin (No ), the Ntionl Bsic eserch Progrm of Chin (973 Progrm) (No. 013CB9560), the 100-lent Project of Chinese cdemy of Sciences (CS), Chin (No. Y ), nd the Specil Funds of CS (No. X ). eferences: [1] Bricud,.,. Morel, nd. Prieur, bsorption by dissolved orgnic mtter of the se (yellow substnce) in the UV nd visible domins, imnol. Ocenogr., 6, 43 55, [] Hu, C., F. E. Muller-Krger, G.. Vrgo, M. B. Neely, nd E. Johns (004), inkges between costl runoff nd the Florid Keys ecosystem: study of drk plume event, Geophys. es. ett., 31, 15307, doi:10.109/004g0038. [3] ee, Z. P, (Ed.) (006), emote sensing of inherent opticl properties: Fundmentls, tests of lgorithms, nd pplictions, ep, 5, 16 pp., Int. Ocen-Color Coord. Group, rtmouth, N.S., Cnd. [4] ee, Z. P., nd C. M. Hu (006), Globl distribution of Cse-1 wters: n nlysis from SeWiFS mesurements, emote Sens. Environ., 101, [5] edetti, M., B. Chrrière,. Bricud, J. Pr, P. imbult, nd. Sempéré (010), istribution of normlized wter-leving rdinces t UV nd visible wve bnds in reltion with chlorophyll nd colored detritl mtter content in the southest Pcific, J. Geophys. es., 115, C0010, doi:10.109/009jc00589, 010. [6] Gordon, H..,. K. Clrk, J. W. Brown, O. B. Brown,. H. Evns, nd W. W. Broenkow, Phytoplnkton pigment concentrtions in the Middle tlntic Bight: Comprison of ship determintions nd CZCS estimtes, pplied Optics,, 0-36, [7] iken, J., G. F. Moore, nd P. M. Hollign, emote sensing of ocenic biology in reltion to globl climte chnge, J. Phycol., 8, , 199. [8] Gordon, H.. (1997), tmospheric correction of ocen color imgery in the Erth Observing System er, J. Geophys. es., 10, 17,081-17,106, [9] Hooker, S. B., nd McClin, C.. (000), he clibrtion nd vlidtion of SeWiFS dt, Progress in Ocenogrphy, 45, , 000. ISBN: