Extremes analysis: the. ETCCDI twopronged

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1 Manola Brunet University Rovira i Virgili, Tarragona, Catalonia Extremes analysis: the Title ETCCDI twopronged approach 5 December 2017

Fourth Session of the ETCCDI, Victoria, Feb 2011 The role of the joint WMO-CCl/WCRP-CLIVAR/JCOMM Expert Team on Detection and Indices (ETCCDI) to assess climate extremes In 1999 a group of

2 Fourth Session of the ETCCDI, Victoria, Feb 2011 The role of the joint WMO-CCl/WCRP-CLIVAR/JCOMM Expert Team on Detection and Indices (ETCCDI) to assess climate extremes In 1999 a group of international experts decided to enhance climate change detection studies by 1. Internationally defining a suite of extreme indices and coordinating their estimation globally as well as regionally Core set consists of 27 descriptive indices for moderate extremes Focus on counts of days crossing a threshold; either absolute/fixed thresholds or percentile/variable thresholds relative to local climate Simple, straight forward, reliable, and consistent across different regions Easy to calculate, update, understand, having physical meaning and high S/N ratio for climate change detection Derived from daily data of quality proven Used in trend analysis, model evaluation, projection and can be coupled with standard detection and attribution methods

The role of the joint WMO-CCl/WCRP-CLIVAR/JCOMM Expert Team on Detection and Indices (ETCCDI) to assess climate extremes Observations provide crucial In 1999 a

Holding regional climate change workshops (modelled after the Asia-Pacific Network Workshops) to fill in knowledge and data gaps of how moderate extremes are

hands-on training + post workshop follow-ups Building capacity to analyse observed changes in extremes Publishing peer-reviewed papers from each workshop

3 The role of the joint WMO-CCl/WCRP-CLIVAR/JCOMM Expert Team on Detection and Indices (ETCCDI) to assess climate extremes Observations provide crucial In 1999 a group of international experts decided to enhance climate change detection studies by 2. Holding regional climate change workshops (modelled after the Asia-Pacific Network Workshops) to fill in knowledge and data gaps of how moderate extremes are changing regionally and globally and provide: underpinning but are often not well-constrained and critical gaps exist in the amount, quality, Free software + hands-on training + post workshop follow-ups Building capacity to analyse observed changes in extremes Publishing peer-reviewed papers from each workshop Contributing to worldwide database of derived indices (e.g. HadEX) More than 25 regional workshops organised by the ETCCDI over the period, with many regions now self-organising them consistency and availability, especially for extremes analysis

4 The ETCCDI core indices: a classification Indices based on percentiles Absolute indices Thresholds Indices Duration indices Other indices 4

5 Indices based on percentiles (global results from Donat et al., 2013) Cold nights and days (TN10p & TX10p): Number of nights (TN) and days (TX) below the 10th percentile Warm nights and days (TN90p & TX90p): Number of nights and days with TN and Tx above the 90th percentile Very wet days (R95p) & extremely wet days (R99p): number of wet days exceeding the 95th & 99th percentiles of the base period Easy to compare among the different stations and find out common spatial signals 5

day (TXx) and night (TNx) The coldest day (TXn) an

6 Absolute indices The highest and the lowest annual or seasonal values of TN & TX or RR, such as: The warmest day (TXx) and night (TNx) The coldest day (TXn) an night (TNn) The highest 1 (RX1day) & 5 (RX5day) wet days 6

Thresholds indices Defined as number of days falling down below or above a predefined absolute threshold that have physical meaning, such as: Frost days (FD) where TN < 0ºC & icy days (ID) where TX <

7 Thresholds indices Defined as number of days falling down below or above a predefined absolute threshold that have physical meaning, such as: Frost days (FD) where TN < 0ºC & icy days (ID) where TX < 0ºC Summer days (SU): No. of days with TX > 25 C Tropical nights (TR): No. of days with TX > 20 ºC Heavy precipitation days (R10): Annual count of days when RR 10 mm Very heavy precipitation days (R20): Annual count of days when RR 20 mm 7

Duration Index (WSDI) Annual count of days with at least 6 consecutive days when TX > 90th percentile Consecutive Dry

8 Duration indices They define periods of excessive heat, cold, rain or drought or the growing season length: Cold Spell Duration Index (CSDI): Annual count of days with at least 6 consecutive days when TN < 10th percentile Warm Spell Duration Index (WSDI) Annual count of days with at least 6 consecutive days when TX > 90th percentile Consecutive Dry Days (CDD) Max number of consecutive dry days RR<1mm) Consecutive Wet Days (CWD) Max number of consecutive dry days RR 1mm 8

Other indices Total Annual precipitation (PRCPTOT): Annual total precipitation from wet days Diurnal Temperature Range (DTR): Mean of the difference

Annually averaged precipitation from wet days Very wet day proportion (R95pTOT): Percentage of annual total precipitation from days with RR 95 th

9 Other indices Total Annual precipitation (PRCPTOT): Annual total precipitation from wet days Diurnal Temperature Range (DTR): Mean of the difference between TX and TN Extreme Temperature Range (ETR): Difference between highest TX and lowest TN during the year Simple Daily Intensity Index (SDII): Annually averaged precipitation from wet days Very wet day proportion (R95pTOT): Percentage of annual total precipitation from days with RR 95 th percentile of the base period Extremely wet day proportion (R99pTOT): Percentage of annual total precipitation from days with RR 95 th percentile of the base period 9

The RClimDex software for QC and extreme indices calculation: a general overview The ETCCDI developed and provides (http://etccdi.pacificclimate.org/software.

extreme indices The RClimDex is based on ClimDex (an Excel based program developed by Byron Gleason at NCDC time ago).

10 The RClimDex software for QC and extreme indices calculation: a general overview The ETCCDI developed and provides ( the RClimDex code to ensure daily time-series (Tx, Tn, RR) are reasonably free of non-systematic biases and the values they contain are true observations It also calculates the 27 ETCCDI core extreme indices The RClimDex is based on ClimDex (an Excel based program developed by Byron Gleason at NCDC time ago). Moving to R platform to solve a problem in percentile indices calculation and because limitations associated with excel environment. Developed, updated and maintained by Environmental Canada (EC) R platform chosen because there is a powerful computing environment for statistical analysis, it s freely available, it is portable across all platforms (Unix, MS-Windows, MacOS), GUI and command line User guide available in English and Spanish and technical support provided by EC

12 Demonstration: Applying RClimDex to QC daily Tx and Tn and RR time-series and estimate extremes The data must be in the format known internationally as "RClimDex format: Data samples provided in correct format to ease the exercise, such as: Each row containing one date of daily data following the calendar order & six fields (columns) with this sequence: Year, Month, Day, RR (mm), Tx and Tn (Cdeg) and missing values coded as It is advisable to install the script (rclimdex.r) and data files in the same folder Labeling files using a numeric code, such as: VVCCCCCCCC.txt VV: file version (ra, for raw data; qc for QC ed data. CCCCCCCC: station code..txt: for the extension For example: ra txt, qc txt

13 Running the RClimDex software To have downloaded platform R in your laptop Only for the first time running the RClimDex, it s in need to install the tkrplot statistical package by setting your CRAM mirror and selecting the tkrplot package

14 Changing directory and upload time-series Running the RClimDex software

15 Running QC tests Running the RClimDex software

variable climates and more restrictive if the annual cycle is more uniform) Give an

16 Running the RClimDex software Setting parameters Code or name the station (same code than the data file) Set number of SD depending on the climate uniformity (4 SD for variable climates and more restrictive if the annual cycle is more uniform) Give an upper limit for daily RR in mm Click OK and after few minutes several messages will appear

17 Running the RClimDex software Several folders have been created: indices, log, plots, trends Look at the folder log first

18 RClimDex QC files: graph files: prcpplot tmaxplot tminplot dtrplot Running the RClimDex software

19 RClimDex QC text files: tempqc (Tx Tn) tepstdqc (Tx/Tn ± x SD) prcpqc nastatistic Running the RClimDex software

20 Verifying QC results Checking suspicious values against original data source, if possible Using expert judgment if original source is not available. E.g. checking value consistency comparing it with previous and next days values or with other observations taken in nearby stations Decisions to take: Validate it Reject it and set it to missing Reject it, but it is recoverable: correct it Make corrections in a copied file (never in the original file), document decisions taken to guarantee QC exercise traceability (e.g. identify station name, country, WMO code, date: year, month, day, variable, original value, replacement value, detection test)

Before estimating extreme indices there is in need to ensure time series homogeneity After QC ing daily data, make sure any time series is homogeneous:

21 Before estimating extreme indices there is in need to ensure time series homogeneity After QC ing daily data, make sure any time series is homogeneous: testing homogeneity and homogenising records, if in need Why homogeneous time series are required before using them in any climate assessment-product-service? They ensure variations and trends in the time series only respond to the forcing of weather and climate factors and aren t the results of artificial causes Provide reliability and robustness to any analysis based on high-quality and homogeneous data Provide the expectable coherent spatial pattern

22 RClimDex extreme indices calculation The RClimDex is also used to compute the ETCCDI extreme indices, once time-series have been QC ed and their homogeneity proven

23 RClimDex extreme indices calculation Indices calculation folders: indices, plots, trend

24 Extreme indices plots

25 Thanks for your attention Questions/Comments Title

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