Lecture on outline of JMA s interactive tool for analysis of climate system

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Transcription:

Lecture on outline of JMA s interactive tool for analysis of climate system November 4, 2008 Ushida Shingo Climate Prediction Division of JMA

Introduction To announce advanced information about climate events that occurred in Japan to people, JMA has established a panel composed by researchers at Univ. and Lab. To proceed to a discussion smoothly at the conference, we should share the climatology data with researcher. And it is effective that we and researchers use a common tool for analysis of climate system. So JMA developed new software named Interactive Tool for Analysis of Climate System (ITACS). あいたくす I entrust love. 我托愛나는사랑을맡긴다

The Account Panel for Extreme Climate Event J M A Climatology Data Operational Monitoring Sharing Data and Knowledge,Using the Common Tool (ITACS) Extreme Climate Event Special Knowledge Univ. and Lab. Conference at JMA or Teleconference by Researchers and JMA s officers Cause and Outlook of the Event

The Account Panel for Extreme Climate Event Dr. Masahide Kimoto The Chairman of the panel (Center for Climate System Research, University of Tokyo) An article about heavy rain and heat wave in this summer

An Outline of ITACS JMA s officers JMA Committee of the panel ITACS JCDAS,SST etc. DATA operationally analyzed Satellite DATA DATA BANK (JRA-25 etc.)

What can we do by ITACS? Drawing chart On a web browser, we set parameters for the chart. We don t need any programming. We can make not only ordinary plane chart, but also vertical cross section, time cross section, time series and animation. Statistical analysis We set parameters for the statistical analysis in the same way as drawing chart. We can test various techniques of statistical analyses. We can see the result with statistically confidence on the chart.

Mercator, contour and vector (OLR and 850hPa wind) Example of Chart Polar Stereographic, shade and vector ( 200hPa zonal wind anomaly and wind vector) vertical cross section, contour and shade ( zonal mean zonal wind and air temperature)

Example of statistical analysis. SUBTRACT (Z500 minus zonal mean Z500 ) CORRELATION COEFFICIENT (between Z500 and OLR around INDIA in August.) SIGNIFICANCE TEST (SST composite of El nino years in January. In the shaded areas the differences between the composite patterns of EL Nina and La Nino are statistically significant with a 95% confidence level based on t-test.)

DATA JRA-JCDAS atmospheric global analysis obtained by Japanese 25-year Reanalysis (JRA-25) project and JMA Climate Data Assimilation System (JCDAS) which is using same data assimilation system as that of JRA-25. (from 1979 to present, daily/pentad/monthly, 2.5deg x 2.5deg) SST sea surface temperature (SST) and sea ice concentration obtained by operational analysis of JMA. ( from 1891 to present, daily/pentad/monthly,1deg x 1deg) MOVE-G1, MOVE-G2 *being registered now oceanic temperature, salinity, current velocity, and so on obtained by the operational ocean data assimilation system in JMA. (from 1958 to present, pentad/monthly, 2.5deg x 2.5deg ) ODAS ocean analysis data obtained by the assimilation system which has been operated until March, 2008 in JMA (from 1986 to March, 2008, pentad/monthly, 2.5deg x 2.5deg ) SAT outgoing long wave radiation (OLR) analysis from CDC/NOAA. (from 1979 to present, daily/pentad/monthly, 2.5deg x 2.5deg) CLIMAT monthly world climate data at surface stations received from CLIMAT message (from 1951 to present. monthly, stations) INDEX NINO-1, NINO-2, NINO-3, NINO-4, and NINO-WEST

DATA USER INPUT We can input any index that we calculate beforehand and use those data for statistical analysis. Example Making correlation coefficient between 850hPa geopotential height and precipitation ratio at Tokyo. Using data 850hPa geopotential height has already been registered in ITACS. We must make dataset of precipitation ratio at Tokyo on the following format. # Tokyo precipitation in 1982-2008. #undef=-9999 1982,8,1,89 1982,9,1,70 1982,10,1,340 1982,11,1,185 1982,12,1,168 1983,1,1,189 1983,2,1,-9999 1983,3,1,-201

Setting Parameters data1: Parameters for drawing chart data2: Parameter about another data to overlay or for statistical analysis Graphic options: Options about color, projection, contour,and so on.

1Dataset JRA-JCDAS SAT SST MOVE-G ODAS CLIMAT USERINPUT INDEX 2Element Velocity potential Pressure vertical velocity Stream function Surface pressure to MSL Air temperature Zonal wind Meridional wind Zonal wind divergence Meridional wind divergence Calc Zonal component of wave activity flux Calc Meridional component of wave activity flux Geopotential height Vector radio button SD:(Standard Deviation) 3Data Type HIST NORM ANOM ANOM_SD 4Area select area or input latitude and longitude 7Show Period RANGE (used usually) YEARS (select several years to take the average) INDEX (to show the chart under the condition of an index) 6Average period MONTH PENTAD DAY DAILY Direct input Year average (for interannual variations of monthly data) Year average pentad (for interannual variation of petad data) Year average day (for interannual variation of daily data) 5Level Select vertical level. To show vertical cross section chart, input bottom level in upper raw and top level in lower raw.

8Analysis Method DATA1_DATA2: To overlay data2 with data1(to show data1 and data2 on the same chart) SUBTRACT: To show data1 minus data2 COMPOSITE:To make composite chart of data1 under the condition set on data2 9lag Set when analysis method is REGRESSION_COEFFICIENT or CORRELATION_COEFFICIENT. For example, to show regression coefficient between data1 in August and data2 in July, lag is -1 month. 10significance To set confidence level based on t-test SIGNIFICANCE_TEST:To show areas where the difference between the composite patterns of data1 and data2 is statistically significant. REGRESSION_COEFFICIENT:To show regression coefficient (data1 is dependent variable, data2 is explanatory variable.) CORRELATION_COEFFICIENT:To show correlation coefficient (data1 is dependent variable, data2 is explanatory variable.)

Now, let s use ITACS. 1 2 1 Open the C: ITACS folder (Start => My Computer => Hard disk drives => C: => ITACS) 2 Open the memo.txt (Double-click the file). You can find URL (http://***) for ITACS.

3 4 3Boot up Internet Explorer, and input the URL written in memo.txt, and push Enter key. 4You are asked USER NAME and PASSWORD, input those as written in memo.txt, and click OK.

5 6 7 5 Set parameters in data1 and Graphic Option as above. 6 After setting parameters, click Submit. ITACS draw the chart according to those parameters. 7 Click animation