4.データを解析する - ??照データとしてjra55 等の再解析データを用い 、cmip5 ... 段フレームに 出力ファイルの一覧が属性情報と共に表示され ます ...

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  • 37

    4.1 CMIP5 (1)

    5 CMIP5Web JRA55CMIP5 (2)

    http://apps.diasjp.net/modelvis/cmip5/

    (3)

    Web 1.3.3 (4) a) CMIP5 Data Viewer CMIP5

    Hide Unsupported Items 4.2

    4.2

    4.1

    http://apps.diasjp.net/modelvis/cmip5/http://db.cger.nies.go.jp/portal/analyses/index

  • 38

    CMIP5 61 CMIP5 20 historical GPCPGlobal Precipitation Climatology Project 10N-20N, 115E-130E1981 2005 25

    5 10 6 4.2 historicalmonpr

    1268 4.3 CMIP52 CMIP5 4.4

    4.3 4.4 CMIP5

    ScorrRMSE 2 4.5 4.6 RMSE Scorr

    4.5 4.6

    BNU-ESMCCSM4CESM1(CAM5)CNRM-CM5 4

  • 39

    DIAS APHRODITE

    4

    4.7

    CMIP5

    BNU-ESM,CCSM4,CESM1(CAM5), CNRM-CM5historical rcp85daypr4.7 Tools for CMIP5 Analysis Bias Correction (APHTODITE) 4.8

    15.5N-16N, 120E-121.5E198111 2000 12 31 2046 1 1 2065 12 31 20

    4

    b) Mann-Kendall

    CMIP5 Data Viewer rcp85montas

    4.9

    4.8

  • 40

    4.9

    Tools for CMIP5 Analysis Mann-Kendall Trend Analysis 4.1090S -90N, 0-360 2006 2100 95 1 12

    4.10

    Mann-Kendall Sen's slope 1% 5% 4.11 (a) 95 100 4.11 (b) 1%

    (a) Sen's slope (b) 1%

    4.11

  • 41

    c) CMIP5 4.12 URL

    http://apps.diasjp.net/modelvis/cmip5/ocean.html

    4.12 (MLD)

    CMIP5

    CMIP5 Data Viewer Show Supported Oceanic Items

    Only 4.13

    4.13

    4.13 rcp85monrhopoto

    4.14

    CMIP5 4.15

    http://apps.diasjp.net/modelvis/cmip5/ocean.html

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    4.14 4.15 CMIP5 10S-45N, 120E-145W2006 2025 20 2

    3 2 MLD 4.15

    (5)

    DIAS dias-office(at)editoria.u-tokyo.ac.jp 4.2 (1)

    ITWeb DIAS

    2 Web

    (2) 4.17

    4.16 2

  • 43

    (3) EDITORIA (4)

    4.16 Web Web SQL DIAS

    Web Web

    ( 4.17)

    4.17

    4.18

    4.19

    4.17

    4.18

  • 44

    4)

    (5)

    DIAS dias-office(at)editoria.u-tokyo.ac.jp

    4.3 PVES (1)

    3 3Web (2)

    4.20 4.21

    (3) dias-office(at)editoria.u-tokyo.ac.jp

    4.19

    4.20 4.21

  • 45

    (4) a) 3

    Aqua AIRS

    4.20 ()

    4.22 Web

    b)

    NCEP/NCAR 4.21 ()

    ()

    4.23Web 4.23

    (5)

    (6)

    DIAS dias-office(at)editoria.u-tokyo.ac.jp

    4.22

    4.23

  • 46

    4.4 (1)

    (CGER)

    (GED) GED

    DIAS GED (2)

    http://db.cger.nies.go.jp/portal/analyses/index

    4.24

    (3)

    (4)

    a) FFT () Thoning

    CO2()Thoning et al., 1989, J. Geophys. Res., 94(6):8549-8565 Web

    4.25 4.25 http://db.cger.nies.go.jp/portal/analyses/trend

    http://db.cger.nies.go.jp/portal/analyses/indexhttp://db.cger.nies.go.jp/portal/analyses/indexhttp://db.cger.nies.go.jp/portal/analyses/trendhttp://db.cger.nies.go.jp/portal/analyses/index

  • 47

    4.25

    b) ()

    ()

    CGER METEX (Meteorological Data Explorer) 1)

    2) METEX 3) ECMWF)NCEP)

    GPV METEX

    GED 1993 10

    ( 4.26(a)) CO2 (4.26(b)) METEX HPhttp://db.cger.nies.go.jp/metex/index.jp.html GED http://db.cger.nies.go.jp/portal/analyses/trajectory

    http://db.cger.nies.go.jp/metex/index.jp.htmlhttp://db.cger.nies.go.jp/portal/analyses/trajectory

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    (a) (b) 4.26 a 10(b) CO2

    c) CGER

    FLEXCPP (Zeng, et al., 2013)

    FLEXCPP FLEXPARTFLEXible PARTicle dispersion model

    (OpenMP)NVIDIA GPU 20

    GED 10000 10 11 2006

    4.27 10000 10

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    Zeng, J., et al., 2013, Lagrangian Modeling of the Atmosphere. Geophysical Monograph 200. Eds. J. Lin, D. Brunner, C. Gerbig, A. Stohl, A. Luhar, and P. Webley., p.163-172. doi:10.1029/2012GM001245.

    FLEXCPP HP: http://db.cger.nies.go.jp/metex/flexcpp.html GED http://db.cger.nies.go.jp/portal/analyses/footprint

    (5) cgerdb_admin(at)nies.go.jp

    4.5 (1)

    JAMSTECWeb3

    (2)

    4.28 http://apps.diasjp.net/modelvis/ocean/ (3)

    Web 1.3.3

    (4) a) Time-series 4.29

    NINO.3

    4.28

    4.29

    http://db.cger.nies.go.jp/metex/flexcpp.htmlhttp://db.cger.nies.go.jp/portal/analyses/footprinthttp://apps.diasjp.net/modelvis/ocean/

  • 50

    4.29 Oceanic Element: Temperature (t)Level / Layer: 5.00mAnalysis Area: NINO.3MembersView Time-series of Ensemble Prediction NINO.3 4.30X 9 3 99 33 b000 Display Option Display previous prediction result

    View Time-series of Ensemble Prediction 4.31 3 4

    b) 4.30 57

    2-D plot Variable: Temperature (t)Level/Layer: 5.00m57 Time Range Forecast:

    57

    4.32

    http://www.godac.jamstec.go.jp/catalog/data/doc_catalog/media/JAM_RandD18_11.pdf (5) : DIAS dias-office(at)editoria.u-tokyo.ac.jp : :: snishika(at)jamstec.go.jp

    4.30

    4.31

    4.32

    http://www.godac.jamstec.go.jp/catalog/data/doc_catalog/media/JAM_RandD18_11.pdf

  • 51

    4.6 OPeNDAP EDITORIA 4.7 CentOS 6 DIAS CentOS 6 EDITORIA

    Intel C Intel Fortran PHP MySQL

    GrADS ImageMagic NCLNCAR Command Language R The GMT System Octave (matlab )

    PLplot () Matplotlib (Python )

    NetCDF HDFHierarchical Data Format HDF-5 Grib_api (ECMWF GRIB )

    Python Ruby

    git mercurial

  • 52

    4.8 GeoNLP - (1)

    GeoNLP GeoNLP

    GeoNLP

    GeoNLPGeoNLP

    GeoNLP GeoNLP

    GeoNLP (2)

    http://dias.ex.nii.ac.jp/geonlp/ DIAS 4.33GeoNLP https://geonlp.ex.nii.ac.jp/

    4.33 (3)

    GeoNLP GeoNLP API

    4.33

    http://dias.ex.nii.ac.jp/geonlp/https://geonlp.ex.nii.ac.jp/

  • 53

    (4) GeoNLP

    4.34

    GeoNLP

    GeoNLP

    (5)

    GeoNLPBSDGeoNLP

    GeoNLP

    GeoNLP

    (6) kitamoto(at)nii.ac.jp

    4.34

  • 54

    4.9 SYNCREEL - (1)

    SYNCREEL

    SYNCREEL 1

    1

    SYNCREEL 7

    (2) http://dias.ex.nii.ac.jp/syncreel/

    4.35

    Syncreel 100

    http://dias.ex.nii.ac.jp/syncreel/

  • 55

    (3) SYNCREEL SYNCREEL

    DIAS (4) SYNCREEL Adobe Flash Player

    Flash Player SYNCREEL

    URLSYNCREEL

    SYNCREEL

    SYNCREEL API API API

    SQL

    (5)

    SYNCREEL

    (6)

    kitamoto(at)nii.ac.jp 4.11

    DIAS

    Hadoop

    5.3 QOL

    DIAS dias(at)db.ss.is.nagoya-u.ac.jp

    The GMT System

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