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WFM 6311: Climate Change Risk Management

Akm Saiful Islam. WFM 6311: Climate Change Risk Management. Lecture-7:Extereme Climate Indicators using RClimIndex. Institute of Water and Flood Management (IWFM) Bangladesh University of Engineering and Technology (BUET). February, 2013. RClimDex. To download and install R How to run R

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WFM 6311: Climate Change Risk Management

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  1. Akm Saiful Islam WFM 6311: Climate Change Risk Management Lecture-7:Extereme Climate Indicators using RClimIndex Institute of Water and Flood Management (IWFM) Bangladesh University of Engineering and Technology (BUET) February, 2013

  2. RClimDex To download and install R How to run R How to use RClimDex Input Data Format

  3. To download and install R: Go to: www.r-project.org Click “CRAN” in the left panel of the screen Select your nearest site from the list of CRAN Mirrors, e.g., India, Singapore Select the target operating system, e.g., Windows, from the main panel Select the module “base”

  4. To download and install R: Click on “Download R 2.14.0 for Windows” (the version number may change due to the R group development) Choose “Run” to run the setup to install R directly without saving the .exe setup file, or “Save” to save the .exe file to your machine and run it later If you choose “Run”, it will download the .exe file to your Windows temporary folder and then run it. The following windows will pop up subsequently: - Choose the language, then click “Next”.

  5. To work in R: When the installation is finished, you can run R by double-click the shortcut icon on your desktop: or by choosing to run R in your “All Programs”. Then, you can either use the drop-down menu or type-in command lines. Most items in the drop-down menu can be translated to command lines of function names along with parameters.

  6. How to use RClimDex • Loading of RClimDex • Within the R consol prompt “>”, enter source(“rclimdex.r”). • rclimdex.r http://cccma.seos.uvic.ca/ETCCDMI/RClimDex/rclimdex.r

  7. How to use RClimDex

  8. How to use RClimDex Once the source code is successfully loaded, the RClimDex main menu will appear-

  9. Load Data and Run QC Select “Load Data and Run QC” from the RClimDex Menu to open a window as shown below

  10. Load Data and Run QC Error messages will appear in the R console if this step has not been completed successfully. This is usually caused by the wrong input data format

  11. Load Data and Run QC The default value for n is 3 (Criteria in the “Set Parameters for Data QC”) window, but this number may be overwritten by the user. As a value of 3 may flag a very large number of values, users may wish to start by setting this value to 4. After setting the parameter, click “OK” to continue.

  12. Load Data and Run QC If there are outliers, the following window appears.

  13. Load Data and Run QC A pop-up window appears once the data QC is complete. At the same time, four Excel files, “21946tempQC.csv”, “21946prcpQC.csv”, “21946tepstdQC.csv”, and “21946indcal.csv” are created in a subdirectory called log. The first two files contain information about unreasonable values for temperature and precipitation. The third file flags all possible outliers in daily temperature with the dates on which those outliers occur. The last file contains the QC’d data and will be used for the indices calculation.

  14. Load Data and Run QC At this point, the user may check the data in the file “21946tepstdQC.csv” to determine if any value marked as an outlier is really an outlier. The file “21946indcal.csv” can be modified using Excel under Windows and any editor under Unix if any action needs to be taken.

  15. Load Data and Run QC After the completion of this step, the user may Click OK on the following window to proceed with indices calculation the indices are computed from the QC’d data. The original input file is not altered in any manner. So if a user chose to modify the original data file to correct some of the problematic values, the Load Data and Run QC procedure needs to be performed again on the improved data set before the changes can be reflected in the indices calculation

  16. Indices calculation

  17. Indices calculation Base Period: 1961-2009 User defined upper threshold of daily maximum temp: MAM average temp 33°C. 30°C is taken User defined lower threshold of daily maximum temp: 0 User defined upper threshold of daily minimum temp: DJF average temperature 14°C. 15°C is taken User defined upper threshold of daily minimum temp: 0 User defined daily precipitation threshold: JJAS average daily rainfall 11.2 mm. 10 mm is taken

  18. Indices calculation A pop-up window will appear once the selected indices are computed.

  19. Indices calculation Resulting indices series are stored in a sub-directory called indices in Excel format. The indices files have names “21946_XXX.cvs” where XXX represents the name of the index. Data columns are separated by a comma (“,”). For the purpose of visualization, we plot annual series, along with trends computed by linear least square (solid line) and locally weighted linear regression (dashed line). Statistics of the linear trend fitting are displayed on the plots. These plots are stored in a sub-directory called plots in JPEG format. The filenames for plots follow the same rule except that “cvs” is changed to “jpg”.

  20. Indices calculation Select “Indices Calculation” from the main menu to compute additional indices for the same station. For additional stations, select “Data QC” and repeat the above process. Select “Exit” if all required calculations are completed.

  21. Indices calculation if base period is 1961-1990 and the data also starts in 1961, one may add “1960 12 31 -99.9 -99.9 -99.9”

  22. Input Data Format ASCII text file Columns as following sequences: Year, Month, Day, PRCP, TMAX, TMIN. (NOTE: PRCP units = millimeters and Temperature units= degrees Celsius) The format as described above must be space delimited (e.g. each element separated by one or more spaces). For data records, missing data must be coded as -99.9; data records must be in calendar date order. Missing dates allowed.

  23. Input Data Format Example data Format for the initial data file (e.g. used in the ‘Quality Control’ step): 1901 1 1 -99.9 -3.1 -6.8 1901 1 2 -99.9 -1.3 -3.6 1901 1 3 -99.9 -0.5 -7.9 1901 1 4 -99.9 -1 -9.1 1901 1 7 -99.9 -1.8 -8.4

  24. THANK YOU

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