Professor A.K.M. Saiful Islam DSMHT 403: Climate Modelling and Adaptation Lecture-5: Indices of Climate Extreme Professor A.K.M. Saiful Islam Institute of Water and Flood Management (IWFM) Bangladesh University of Engineering and Technology (BUET) 8 November 2016

Outline Prediction of climate change Global and regional climate change predictions Dynamic and static downscaling for impact study Uncertainty of predictions

Indices of Climate Extremes Outline of the lecture Climate indices for extreme climate Standard climate indices Calculating climate indices R-ClimIndex tool for calculating indices

Information on the Climate extremes Confidence has increased that some extremes will become more frequent, more widespread and/or more intense during the 21st century (IPCC, 2007). As a result, the demand for information services on weather and climate extremes is growing. The sustainability of economic development and living conditions depends on our ability to manage the risks associated with extreme events. Many practical problems require knowledge of the behavior of extreme values. In particular, the infrastructures, public services and other facilities we depend upon for food, water, energy, health, shelter and transportation are sensitive to high or low values of meteorological variables.

Assessment of extremes To gain a uniform perspective on observed changes in weather and climate extremes, the joint CCl/WCRP-Clivar/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI) has defined a core set of descriptive indices of extremes. The indices describe particular characteristics of extremes, including frequency, amplitude and persistence. The core set includes 27 extremes indices for temperature and precipitation.

Climate Indices Ott, W. 1978. Environmental Indices: Theory and Practice Indices are used to summarize and present a complex set of multivariate (several variables at the same time) changes so that the results can be easily understood and used in policy decisions made by non-specialists in the field.

400 Climate Indices ClimDex. 2001. ClimDex Version 3.1: User’s Guide. cccma.seos.uvic.ca/ETCCDMI/ClimDex/climdex-v1-3-users-guide.pdf Frich, P., L. V. Alexander, P. Della-Manta, B. Gleason, M. Haylock, A. M. G. Klein Tank and T. Peterson. 2002. Observed coherent changes in climatic extremes during the second half of the twentieth century. Clim. Res., 19:193-212. European Climate Assessment. 2008. European Climate Assessment and Dataset. eca.knmi.nl/ Klein Tank, A.M.G., J.B. Wijngaard, G.P. Können, R. Böhm, G. Demarée, A. Gocheva, M. Mileta, S. Pashiardis, L. Hejkrlik, C. Kern-Hansen, R. Heino, P. Bessemoulin, G. Müller-Westermeier, M. Tzanakou, S. Szalai, T. Pálsdóttir, D. Fitzgerald, S. Rubin, M. Capaldo, M. Maugeri, A. Leitass, A. Bukantis, R. Aberfeld, A.F.V. van Engelen, E. Forland, M. Mietus, F. Coelho, C. Mares, V. Razuvaev, E. Nieplova, T. Cegnar, J. Antonio López, B. Dahlström, A. Moberg, W. Kirchhofer, A. Ceylan, O. Pachaliuk, L.V. Alexander, and P. Petrovic, 2002. Daily dataset of 20th-century surface air temperature and precipitation series for the European Climate Assessment. Int. J. Climatol., 22, 1441-1453. Kiktev, D., D. Sexton, L. Alexander and C. Folland. 2003. Comparison of modelled and observed trends in indicators of daily climate extremes. J. Clim., 16, 3560-71. Stardex. 2008. Statistical and Regional dynamical Downscaling of Extremes for European regions. www.cru.uea.ac.uk/projects/stardex Bonsal, B.R., X. Zhang, L.A. Vincent and W.D. Hogg. 2001. Characteristics of daily and extreme temperatures over Canada. Journal of Climate 14 :1959-1976. Klein Tank, A.M.G. and G.P. Können, 2003. Trends in indices of daily temperature and precipitation extremes in Europe, 194699. J. Climate, 16, 3665-3680.

Gachon Indices of Climate Extremes 18 indices for extreme temperature and precipitation for Canadian regions must represent regional Canadian climate conditions; must be relevant to climate change impact studies; and must be adapted to the main characteristics of climate conditions at the regional scale. “providing a good mix of information – precipitation indices characterize the frequency, intensity, length of dry spells, magnitude and occurrence of wet extremes while temperature indices refer to variability, season lengths and cold and warm extremes in terms of magnitude, occurrence and duration.”

Gachon Indices related to precipitation  INDEX DEFINITION UNIT TIME SCALE Frequency Percentage of wet days (Threshold=1 mm) % days Season Intensity Simple daily intensity index : sum of daily precip/number of wet days mm/wet d Extremes Maximum number of consecutive dry days (<1 mm) days Magnitude Maximum 3-days precipitation total mm and 90th percentile of rainday amount ( (Threshold=1 mm) mm/days Occurrence Percentage of days Prec>90th percentile (61-90 based period)

Gachon Indices related to Temperature Daily variability Mean of diurnal temperature range °C Season Percentage of days with freeze and thaw cycle (Tmax>0°C, Tmin<0°C) % days Month Season length Frost season length :Tday<0°C more than 5 d.and Tday>0°C more than 5 d. days Year Growing season length :Tday>5°C more than 5 d.and Tday<5°C more than 5 d. Extremes Sum of sequences > 3 days where Tmin< daily Tmin normal - 5°C Winter cold & hot Sum of sequences > 3 days where Tmax> daily Tmax normal + 3°C summer 10th percentile of daily Tmax Magnitude  90th percentile of daily Tmax and 10th percentile of daily Tmin   90th percentile of daily Tmin Occurrence Percentage of days Tmax>90th percentile (61-90 based period) Percentage of days Tmin<10th percentile (61-90 based period)

ETCCDI Rainfall related indices ID Indicator name Definitions UNITS RX1day Max 1-day precipitation amount Monthly maximum 1-day precipitation Mm Rx5day Max 5-day precipitation amount Monthly maximum consecutive 5-day precipitation SDII Simple daily intensity index Annual total precipitation divided by the number of wet days (defined as PRCP>=1.0mm) in the year Mm/day R10 Number of heavy precipitation days Annual count of days when PRCP>=10mm Days R20 Number of very heavy precipitation days Annual count of days when PRCP>=20mm

ETCCDI Rainfall related indices ID Indicator name Definitions UNITS CDD Consecutive dry days Maximum number of consecutive days with RR<1mm Days CWD Consecutive wet days Maximum number of consecutive days with RR>=1mm R95p Very wet days Annual total PRCP when RR>95th percentile Mm R99p Extremely wet days Annual total PRCP when RR>99th percentile mm PRCPTOT Annual total wet-day precipitation Annual total PRCP in wet days (RR>=1mm)

ETCCDI Temperature related indices ID Indicator name Definitions UNITS FD0 Frost days Annual count when TN(daily minimum)<0ºC Days SU25 Summer days Annual count when TX(daily maximum)>25ºC ID0 Ice days Annual count when TX(daily maximum)<0ºC TR20 Tropical nights Annual count when TN(daily minimum)>20ºC GSL Growing season Length Annual (1st Jan to 31st Dec in NH, 1st July to 30th June in SH) count between first span of at least 6 days with TG>5ºC and first span after July 1 (January 1 in SH) of 6 days with TG<5ºC TXx Max Tmax Monthly maximum value of daily maximum temp ºC TNx Max Tmin Monthly maximum value of daily minimum temp

ETCCDI Temperature related indices ID Indicator name Definitions UNITS TNx Max Tmin Monthly maximum value of daily minimum temp ºC TXn Min Tmax Monthly minimum value of daily maximum temp TNn Min Tmin Monthly minimum value of daily minimum temp TN10p Cool nights Percentage of days when TN<10th percentile Days TX10p Cool days Percentage of days when TX<10th percentile TN90p Warm nights Percentage of days when TN>90th percentile TX90p Warm days Percentage of days when TX>90th percentile

Extreme climate Indices Using statistical package RClimIndex

Outline of the RClimDex Lecture To download and install R How to run R How to use RClimDex Input Data Format

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”

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”.

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.

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

How to use RClimDex

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

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

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

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.

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

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.

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.

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

Indices calculation

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

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

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”.

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.

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”

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. 

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  

Define Parameter

Indices