,*++ RSSJ Journal of The Remote Sensing Society of Japan Vol. -+ No. / (,*++) pp , - Abstract

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1 ,*++ RSSJ Journal of The Remote Sensing Society of Japan Vol. -+ No. / (,*++) pp MTST * * * +, - Development of a Precipitable Water Estimation Method Using MTST Measurement Shin KTSUK* Kei O YOSHI* and Wataru T KEUCHI* +, - bstract Japanese geostationary meteorological satellite, Multi-functional Transport Satellite (MTST), was launched in February,**/ and the algorithms for land surface temperature (LST) retrieval from MTST were developed for +, the monitoring of urban heat island and the other phenomenon. In order to improve the accuracy of LST retrieval from satellite remote sensing data, the information of atmospheric condition, especially atmospheric water vapor content, is absolutely imperative. In addition, since atmospheric water vapor is one of the dominant greenhouse gases and it influences the process of partitioning of incoming solar radiation into sensible and latent heats, the atmospheric water vapor content is one of the key parameters for the analysis of global environmental changes. However, the products of water vapor content are not o# ered except for radiosonde data and reanalysis products. Precipitable water (PW) is one of the physical quantities which represents the atmospheric water vapor content. This study aims to produce the hourly precipitable water maps using MTST data. set of precipitable water estimating equations were derived and demonstrated for mapping of hourly PW distribution in clear sky condition using MTST data and reanalysis products. These equations were derived by a multiple regression analysis between brightness temperature of MTST infrared channels and temperature at 1** hpa from reanalysis products, and PW derived from radiosonde data. The monthly root mean square errors ranged approximately from 0./ to ++./ mm. It was revealed that the PW estimating equations could estimate PW with relatively high accuracy from July to September, but it could not in January and February. Keywords : geostationary satellite, radiosonde data, reanalysis products, split-window 0 MTST + ++ MTST Multi-functional Transport Satellite GMS-/,**/ - MTST +,. MTST + MTST / +, 0,* ,*++. +*. / + * Yamanashi Institute of Environmental Sciences, //31 +, Kenmarubi, + * Kamiyoshida, Fujiyoshida, Yamanashi.*- **/, Japan.*- ***/ //31 +, * Japan erospace Exploration gency,, + +, Sengen, Tsukuba,, * Ibaraki -*/- 2/*/, Japan -*/ 2/*/, * Institute of Industrial Science, The University of Tokyo,.0+, - * +/-2/*/. 0 + Komaba, Meguro-ku, Tokyo +/-2/*/, Japan 481

2 MTST 1 + 0* 0* 2* +0* l 2 GOES Geostationary Operational Environmental Satellite VS VISSR Visible- Infrared Spin Scan Radiometer tomaspheric Sounder 3 ++ T T T t Spinning Enhanced Visible and Infrared Imager +, GMS-/ MTST MSG-SEVIRI Kleespies McMillin +- +, T t T + t T T T T t T + t T T t T + t T, - T + / K MSG-SEVIRI +/. W T MTST k a + n q n, +* mm TO,IR+ TO,IR, W 1 T T t T T t exp k a Wsec q. TO,IR+ T exp k aw secq +, TO,IR, T kk k aa a MTST 0, MSG-SEVIRI +* mm + + TO,IR+ T W ln k asecq T T +* mm 3 T IR+ IR, MSG-SEVIRI Meteosat Second Generation- IR+ IR, 1,,+ + GMS-/ MTST IR + +*./ ++./ mm MTST GMS-/ IR, ++./ +,./ mm + GMS-/ GMS-/ RMSE +* mm RMSE O S t t O l S l O,IR+ O,IR, O,IR+ ++ S ++ O,IR, +, S +, ++ +, O,IR+ O,IR, n ++ +, ++ +, n n n S O,IR, MTST MTST n n l 482

3 Vol. -+ No. /,*++ +* PWa a cos qa IR+ IR, a IR+ IR, cosq * +, - a ln IR+ T a ln IR+ T cos q. 1** / 1** a ln IR, T a ln IR, T cos q 0 1* 1** +, ** : ** UTC +, : ** UTC PW mm IR+ IR, MTST IR+ NO NCEP/NCR +/ +* mm IR, ++./ 1** hpa +,./ mm K T 1** +. ** : ** hpa K q rad UTC *0 : ** UTC +, : ** UTC +2 : ** UTC a a MTST,/. 1** +. 1** hpa,- MTST Fig., +*,,,**1 a a MTST IR+ IR+ IR+ MTST User s Guide http : //mscweb. IR+ -IR, - MODIS kishou.go.jp/support/index.htm MOD-/ IR,/. MTST HRIT +* a a Normalized Geostational Projection 1** hpa - Weather Web http : //weather.uwyo.edu/ + Fig. +,/ 1** hpa +0 Fig. + The geographical location of radiosonde stations for the analysis. Stars represent the radiosonde stations for deriving PW estimating equation, and circles represent those for validation of it. 483

4 MTST Fig., Flow chart of deriving PW estimating equation. 1** hpa,/. +, 1** hpa 1** hpa 1** hpa. 1** hpa *.,1 *. 0. K RMSE K 1** hpa RMSE -/. +. 1** hpa 1 mm RMSE 1** hpa Table, Table, 1** hpa +* mm,/. RMSE 1 mm. Chongq- ing DaNang Dibrugarh Hanoi 1** hpa 1** hpa MTST 1** hpa RMSE Table ,+,**1 RMSE Table - 1** hpa Fig. + * mm RMSE 3. 2-mm mm,/,**1,./ + MTST 1** hpa 1** hpa Fig. - Table + 1** hpa +. +* +, 1** hpa RMSE / 3 484

5 Vol. -+ No. /,*++ (a) Precipitable water (b) Temperature at 1** hpa Fig. - Scatter plots between radiosode data and reanalysis data ; a Precipitable water b Temperature at 1** hpa. Table + Bias and RMSE of PW and temperature at 1** Table, Bias and RMSE of PW at each radiosonde hpa, respectively. N represents the number of station. N represents the number of samples. samples. -, MTST 1** hpa 1** hpa +,** * +, / 3 -+.,+ a a b Fig.. a,**1 485

6 MTST Table - Bias and RMSE of PW estimated using PW estimating equation and temperature at 1** hpa from either radiosonde or reanalysis. N represents the number of samples. Table. The coe$ cients of monthly PW estimating equations and the bias and RMSE of PW estimated using them. N represents the number of samples. Table. a a RMSE -- MTST Fig.. + : + -,,**1 Table - Table. + ** : ** UTC +, : ** UTC Fig. + RMSE *1. mm.+. mm Fig. +,+ Table. RMSE Table. RMSE 0./ a a +*./ mm Fig. + RMSE Table /

7 Vol. -+ No. /,*++ (a) Using annual estimating equation (b) Using monthly estimating equations Fig.. Scatter plots between radiosonde PW and PW estimated form MTST data ; a MTST PW was estimated using the equation derived from annual data, b MTST PW was estimated using the monthly equations. RMSE 1mm - Lapoag Medan Table / Bias and RMSE of PW estimated using monthly UjangPandang++ PW estimating equations. N represents the number RMSE Table of samples. / 1 3 RMSE 3 mm, +, RMSE ++ mm +1 MTST + +/ ** : ** UTC */ : ** UTC 1 1** hpa 1** hpa +2 Chester 1** hpa +. 3,* hpa..+ GMS-/ -. MTST -, + MTST MTST Fig. /,**

8 MTST Fig. / Hourly precipitable water maps in ugust +/,,**1. White area represents the cloud-contaminated area. RMSE 0./ mm +*./ mm 1 3 RMSE 3mm : +, RMSE ++ mm MTST : MTST +,.3. pp.,/+,/3,*+*., :MTST /* pp ,*++. RMSE+* mm - :WWW MTST MTST.0 0 pp..,.2,**1.. :.,,**1. / D.J. :,**,. 488

9 Vol. -+ No. /,*++ 0. Dai : Recent climatology, variability, and trends in global surface temperatures, Journal of pplied Meteorology,,3, surface humidity, Journal of Climate, +3, pp. -/23-0*0,,**0. pp. 2/+ 20,, +33*. 1 : +. D. Chester, W.D. Robinson and L.W. Uccellini : Optimized pp retrievals of precipitable water from the VS Split 2 : +2 Window, Journal of Climate and pplied Meteorology,,0, pp., pp. +*/3 +*00, +321.,**/. +/ E. Kalnay, M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, 3.R. Guillory G. J. Jedlovec and H.E. Fuelberg : tech- L. Gandin, M. Iredell, S. Saha, G. White, J. Wollen, Y. Zhu, nique for deriving column-integrated water content using. Leetmaa, R. Reynolds, M. Chelliah, W. Ebisuzaki, W. VS split-window data, Journal of pplied Meteorology, -,, Higgins, J. Janowiak, K.C. Mo, C. Ropelewski, J. Wang, R. pp. +,,0 +,.+, Jenne and D. Joseph : The NCEP/NCR.*-year reanalysis +* C.M. Hyden and G.S. Wade : Derived product imagery project, Bull. mer. Meteor. Soc., 11, pp..-1.1*,,**1. from GOES- 2, Journal of pplied Meteorology, -/, pp. +/- +0 Y.S. Choi and C.H. Ho : Validation of cloud property re- +0,, trieval from MTST-+ R imagery using MODIS observa- ++ J.F. Dostalek and T.J. Schemit : Total precipitable water tions, International Journal of Remote Sensing, -* (,,), pp. measurements from GEOS Sounder derived product image- /3-/ /3/2,,**3. ry, Weather and Forecasting, +0, pp. /1--/21,,**+. +1 K.E. Trenberth, F. Fasullo and L. Smith : Trends and vari- +, M. Schroedter-Homscheidt,. Drews and S. Heise : Total ability in column-integrated atmospheric water vapor, Climate water vapor column retrieval from MSG-SEVIRI split window Dynamics,,., pp /2,,**/. measurements exploiting the daily cycle of land surface +2 D. Chester and L.W. Uccellini : Low-level water vapor fields temperatures, Remote Sensing of Environment, ++,, pp.,.3 from the VISSR tmospheric Sounder (VS) Split Window,/2,,**2. channels, Journal of Climate and pplied Meteorology,,,, +- J.T. Kleespies and L.M. McMillin : Retrieval of precipitable pp. 1,/ 1.-, water from observations in the Split Window over varying,**1 +, +333,**.,**2 +,*+*.,*+*,**1-,**3 IT JIC +3 +3,*+*-,*+, JSPS th The -* sian conference on Remote Sensing Best Paper ward akatsyies.pref.yamanashi.jp GU wataruiis.u-tokyo.ac.jp,**,,**1,**2,*++.,**.,**/ ohyoshi.keijaxa.jp 489