Japan Geoscience Union Meeting 2014

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International Session (Oral)

Symbol A (Atmospheric, Ocean, and Environmental Sciences) » A-CG Complex & General

[A-CG06_29AM1] Satellite Earth Environment Observation

Tue. Apr 29, 2014 9:00 AM - 10:45 AM 315 (3F)

Convener:*Riko Oki(Japan Aerospace Exploration Agency), Yoshiaki Honda(Chiba University, Center for Environmental), Kenlo Nishida Nasahara(Institute of Agricultural and Forest Engineering, University of Tsukuba), Takashi Nakajima(Tokai University Department of Network and Computer Engineering, School of Information and Design Engineering), Taikan Oki(Institute of Industrial Science, The University of Tokyo), Yokota Tatsuya(Center for Global Environmental Research, National Institute for Environmental Studies), Yukari N. Takayabu(Atmosphere and Ocean Research Institute(AORI), The University of Tokyo), Hiroshi Murakami(Earth Observation Research Center, Japan Aerospace Exploration Agency), Hajime Okamoto(Research Institute for Applied Mechanics,Kyushu University), Chair:Yukari Takayabu(Atmosphere and Ocean Research Institute, the University of Tokyo)

10:30 AM - 10:45 AM

[ACG06-13] Analysis of rain characteristics by using CloudSat and TRMM/PR

*Nobuhiro TAKAHASHI1 (1.National Institute of Information and Communications Technology)

Keywords:rain, drop size distribution, CloudSat, TRMM

Spaceborne cloud/precipitation radars are suitable for understanding the global climate (especially precipitation in this study) that means both the average figure of the Earth climate and the local climate in the global climate. In terms of precipitation climatology, major parameters are the precipitation amount and its diurnal/seasonal changes as well as the drop size information that is a kind of proxy of the precipitation processes such as warm/cold rain. The purpose of this study is to develop the climate map of precipitation by using CloudSat that equips W-band (94 GHz) radar and TRMM/PR that equips Ku-band (13.8 GHz) radar; rain amount is estimated by the TRMM/PR level 2 product (2A25) and the drop size information is obtained by combining the CloudSat and TRMM/PR. The basic idea of the analysis method is to compare the histograms of radar reflectivity factor (Z) at near-surface range bin at the overlapping Z range (weak to moderate rain echo). Because the both satellites have different orbit, only the statistical approach is available. Since the different Mie scattering effect appears for the different frequency and drop size, the Z value of rainfall is different between w- and Ku-band radar observations and it reflects the difference in the histograms of w- and Ku-band. Based on these characteristics, drop size information is estimated by comparing the histograms. In this study, median diameter (D0) is estimated. For the comparison of the estimation, D0 is estimated by TRMM/PR only.Climate data are created in 10 x 10 degrees in latitude and longitude boxes and each box consists of the unconditional and conditional rain rate (the former corresponds the rain amount) and D0 (median diameter) both from the CloudSat-TRMM/PR combined analysis and TRMM/PR-only analysis for every seasons (DJF, MAM, JJA, and SON), diurnal cycle (night time/day time orbit) and over land or ocean. The results show that the general characteristic of global maps of D0 through the year and local time is apparent land-ocean contrast; larger D0 appears over land and smaller D0 appears over ocean except for relatively small D0 over southeastern Asia to China. Also, relatively larger D0 appears in tropical area and mid latitude summer. Diurnal change of D0 can be seen by comparing the day/night time D0; D0 is larger in the night time over ocean while day time D0 is larger over land. Tropical Ocean shows smaller seasonal change, while larger changes are seen over mid-latitude area. Comparison of the two estimates of D0 between CloudSat-TRMM/PR combined estimation and TRMM/PR-only estimation.Since the Dual-frequency Precipitation Radar (DPR) onboard Global Precipitation Measurement (GPM) core satellite, which is launched in February 2014, can estimate the drop size distribution (DSD), the approach in this study can be useful of evaluation of the algorithm for DSD estimation.