Climate Change Indices By: I Putu Santikayasa

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1 Climate Change Indices By: I Putu Santikayasa Climate Change and Water Resources CE Water Engineering and Management (WEM) School of Engineering and Technology (SET) Asian institute of Technology (AIT)

2 Introduction A main objective of constructing climate extremes indices is to use for climate change monitoring and detection studies Change in the frequency or severity of extreme climate events would have profound impacts on nature and society Very important to analyze extreme events Need daily data very difficult task

3 Introduction Need to develop, calculate, and analysis a suite of indices so that individuals, countries, and regions can calculate the indices in exactly the same way such that their analyses will fit seamlessly into the global picture Furthermore, need toolkits including software, documentation, and other material to guide the calculation and use of climate change detection indices and climate data homogenization, improvement of global coverage and assessment of indices.

4 Climate Indices Climate indices is used to monitor climate change as and when is happens. The indices based on daily temperature and precipitation as data input Some of them based on thresholds that are relevant on particular application 40 indices was approved 27 indices consider to be core indices

5 Climate Indices ID FD0 Indicator name Frost days Definitions Annual count when TN(daily minimum)<0ºc UNITS Days SU25 ID0 Summer days Ice days Annual count when TX(daily maximum)>25ºc Days Annual count when TX(daily maximum)<0ºc Days TR20 Tropical nights Annual count when TN(daily minimum)>20ºc Days

6 Climate Indices GSL Growing season Length Annual (1st Jan to 31 st Dec in NH, 1 st July to 30 th 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 Days TXx TNx TXn TNn Max Tmax Max Tmin Min Tmax Min Tmin Monthly maximum value of daily maximum temp Monthly maximum value of daily minimum temp Monthly minimum value of daily maximum temp Monthly minimum value of daily minimum temp ºC ºC ºC ºC

7 Climate Indices TN10p Cool nights Percentage of days when TN<10th percentile Days TX10p Cool days Percentage of days when TX<10th percentile Days TN90p Warm nights Percentage of days when TN>90th percentile Days TX90p Warm days Percentage of days when TX>90th percentile Days WSDI Warm spell duration indicator Annual count of days with at least 6 consecutive days when TX>90th percentile Days

8 Climate Indices CSDI Cold spell duration indicator Annual count of days with at least 6 consecutive days when TN<10th percentile Days DTR Diurnal temperature range Monthly mean difference between TX and TN ºC RX1day Max 1-day precipitation amount Monthly maximum 1-day precipitation Mm Rx5day Max 5-day precipitation amount Monthly maximum consecutive 5-day precipitation Mm SDII Simple daily intensity index Annual total precipitation divided by the number of wet days (defined as PRCP>=1.0mm) in the year Mm/d ay

9 Climate Indices 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 Days Rnn Number of days above nn mm Annual count of days when PRCP>=nn mm, nn is user defined threshold Days 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 Days

10 Climate Indices Very wet days R95p Annual total PRCP when RR>95 th percentile Mm Extremely wet days R99p Annual total PRCP when RR>99 th percentile mm PRCPTOT Annual total wetday precipitation Annual total PRCP in wet days (RR>=1mm) mm

11 Climdex Climdex : Microsoft Excel based program that provides an easy-to-use software package for the calculation of indices of climate extremes for monitoring and detecting climate change Developed by Byron Gleason at the National Climate Data Centre (NCDC) of NOAA, and has been used in CCl/CLIVAR workshops on climate indices since 2001

12 Climdex v.s RClimdex Climdex Ms. Excel platform Running under Window Difficult to fix the bug RClimdex R platform Free Powerfull for statistical analysis Running under window and unix Relatively easy to fix the bug

13 Rclimdex ver. 1.3 Used to calculate climate change indices 27 core indices recommended by the CCl/CLIVAR Expert Team for Climate Change Detection Monitoring and Indices (ETCCDMI) Developed under R 1.84 or higher Limitation: Simple data quality control Not include Data homogenization

14 Please Remember!!: 1. Not all indices are calculated on a monthly basis. 2. Monthly indices are calculated if no more than 3 days are missing in a month, while annual values are calculated if no more than 15 days are missing in a year. 3. No annual value will be calculated if any one month s data are missing. 4. For threshold indices, a threshold is calculated if at least 70% of data are present. 5. For spell duration indicators (marked with a *), a spell can continue into the next year and is counted against the year in which the spell ends e.g. a cold spell (CSDI) in the Northern Hemisphere beginning on 31 st December 2000 and ending on 6 th January 2001 is counted towards the total number of cold spells in 2001

15 Software and user manual :

16 How to use RClimdex R software is required to run Rclimdex Connect to R Project website: Download * Install the program *For window user : download window setup For unix user: download proper precompiled binaries (source code may need to be downloaded and compiled)

17 How to use RClimdex Data format: 1. ASCII text file 2. Columns as following sequences: Year, Month, Day, PRCP, TMAX, TMIN. (NOTE: PRCP units = millimeters and Temperature units= degrees Celsius) 3. The format as described above must be space delimited 4. Missing data must be coded as -99.9; data records must be in calendar date order. Missing dates allowed.

18 How to use RClimdex Sample data: Year Day TMax (oc) TMin (oc) Month Precipitation (mm)

19 How to use RClimdex 1. Load RClimdex 2. Load Data->Run QC 3. Indices Calculation

20 Load RClimdex Load Data->Run QC Indices Calculation 1. R consol prompt > Type: source ( rclimdex path ) source("c:\\climateindices\\rclimdex.r") source ( ) 2. File > Source R code

21 Load RClimdex Load Data->Run QC Indices Calculation Prerequisite for indices calculations Replace all missing values (currently coded as ) into an internal format that R recognizes Replace all unreasonable values into NA

22 What will be checked? Daily precipitation amounts less than zero Daily maximum temperature less than daily minimum temperature QC also identifies outliers in daily maximum and minimum temperature The outliers are daily values outside a region defined by the user Unreasonable values are identified automatically but identification of outliers in temperature data requires input from the user

23 Data QC files tempqc.csv unreasonable temperature prcpqc.csv unreasonable precipitation tepstdqc.csv all possible outliers in daily temperature with the dates on which those outliers occur indcal.csv QC d data and will be used for the indices calculation

24 Load RClimdex Load Data->Run QC Indices Calculation RClimDex is capable of computing all 27 core indices Parameter input: First and last year of base period for the threshold calculation Station Latitude (SH negative) daily precipitation threshold, P (in mm) Upper and Limit of Day High Upper and Limit of Day Low

25 Load RClimdex Load Data->Run QC Indices Calculation Selection of indices Result will be stored as excel file and jpeg format Jpeg format: trends computed by linear least square (solid line) and locally weighted linear regression (dashed line)

26 Class exercise

27 Case study: Analyze climate change indices by using data from your country Due date: 29 th March 2012 Submitted to Dr. Sangam

28 Thank you Have a nice day

Foralps 2nd conference. Assessment of Lombardy's climate in the last century: data analysis, methodologies and indices

Foralps 2nd conference. Assessment of Lombardy's climate in the last century: data analysis, methodologies and indices Alessia Marchetti, Angela Sulis Assessment of Lombardy's climate in the last century: data Contents The dataset The daily indices analysis Some preliminary monthly data indices analysis Some key points