The document provides information about climate change indices and software for calculating them. It discusses (1) the climate indices project led by WMO and WCRP to develop standardized climate change indices, (2) the 27 core climate indices defined by the project focusing on temperature and precipitation extremes, and (3) the RClimDex software for calculating the indices using R.

1. Climate Change Indices
Climate Change and Water Resources (CE74.9002)
Water Engineering and Management (WEM)
School of Engineering and Technology (SET),
Asian institute of Technology (AIT)
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I Putu Santikayasa

2. Outlines
1. Introduction
2. What is climate?
3. Climate Indices Project
4. What is Climate indices?
5. R - climdex
6. Case Study
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3. Introduction
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Figure 1. Schematic view of the components of the climate system, their processes
and interactions. (source: IPCC)

4. Introduction
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Please refer to the Koppen
cimate classification

5. What is climate?
• Weather: what is happening in the
atmosphere at any given time
– Air temperature at 7am = 24 deg celcius
• Climate: the “average weather”
• Climate is the status of the climate system
which comprises the atmosphere, the
hydrosphere, the cryosphere, the surface
lithosphere and the biosphere
– Average air temperature on July = 24 deg Celcius
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6. What is climate?
• Statistical analysis:
– Mean
– Maximum
– Minimum
– Percentile
• Climate change analysis
– Change in mean, max, min, etc.
• What about the changes in extremes?
– Number of days where T>90th percentile, etc
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7. Climate indices project
• Change on the extreme climate events
impacts on nature and society
• Analyze extreme events is very important
• The monitoring, detection and attribution of
changes in climate extremes require daily
resolution data
• However, the compilation and update of a
globally daily dataset is a very difficult task
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8. 2/27/2015 Tutorial class 8
World Meteorological
Organization Commission
for Climatology (CCl)
World Climate Research Programme (WCRP)
project on Climate Variability and Predictability
(CLIVAR) Expert Team on Climate Change
Detection, Monitoring and Indices (ETCCDMI)
International coordination of the development of a suite of
climate change indices which primarily focus on extremes 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
Output: 27 indices were defined and two software packages,
one written in R (RClimDex) and the other written in
FORTRAN (FClimDex), were developed

9. What is Climate indices?
• What is Climate Indices:
A climate indices is defined as a calculated
value that can be used to describe the state
and the changes in the climate system.
Climate indices allow a statistical study of
variations of the dependent climatological
aspects, such as analysis and comparison of
time series, means, extremes and trends.
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10. Climate Indices
• 27 indices:
– 16 indices related to the temperature
– 11 indices related to the precipitation
• Indices are driven from:
– Maximum temperature
– Minimum temperature
– Precipitation
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11. Climate Indices
• The climate indices can be categorized into
5(five) groups:
1. Percentile-based indices
2. Absolute indices
3. Threshold indices
4. Duration indices
5. Other indices
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12. Percentile-based indices
1. Occurrence of cold nights (TN10p)
2. Occurrence of warm nights (TN90p)
3. Occurrence of cold days (TX10p)
4. Occurrence of warm days (TX90p)
5. Very wet days (R95p)
6. Extremely wet days (R99p).
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13. Absolute indices
• Represent maximum or minimum values within a
season or year
1. Maximum daily maximum temperature (TXx),
2. Maximum daily minimum temperature (TNx),
3. Minimum daily maximum temperature (TXn),
4. Minimum daily minimum temperature(TNn),
5. Maximum 1-day precipitation amount (RX1day)
6. Maximum 5-day precipitation amount (RX5day)
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14. Threshold indices
• The number of days on which a temperature or
precipitation value falls above or below a fixed
threshold,
1. Annual occurrence of frost days (FD)
2. Annual occurrence of ice days (ID)
3. Annual occurrence of summer days (SU)
4. Annual occurrence of tropical nights (TR)
5. Number of heavy precipitation days > 10 mm (R10)
6. Number of very heavy precipitation days > 20 mm
(R20)
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15. Duration indices
• Periods of excessive warm, cold, wetness or
dryness or in the case of growing season
length, periods of mildness.
1. Cold spell duration indicator (CSDI)
2. Warm spell duration indicator (WSDI)
3. Growing season length (GSL)
4. Consecutive dry days (CDD)
5. Consecutive wet days (CWD)
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16. Others indices
• The indices do not fall into any of the above
categories but could have significant societal
impacts.
1. Annual precipitation total (PRCPTOT)
2. Diurnal temperature range (DTR)
3. Simple daily intensity index (SDII)
4. Extreme temperature range (ETR)*
5. Annual contribution from very wet days
(R95pT)
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*) not directly calculated by RClimDex but have been defined for this study as TXx–
TNn

17. Climate 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 Days
ID0 Ice days Annual count when TX(daily maximum)<0ºC Days
TR20 Tropical nights Annual count when TN(daily minimum)>20ºC Days
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18. Climate Indices
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
Days
TXx Max Tmax Monthly maximum value of daily maximum temp ºC
TNx Max Tmin Monthly maximum value of daily minimum temp ºC
TXn Min Tmax Monthly minimum value of daily maximum temp ºC
TNn Min Tmin Monthly minimum value of daily minimum temp ºC
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19. 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
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20. 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
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21. 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
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22. Climate Indices
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) mm
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23. Software for index calculation
• RClimDex: The RClimDex provides a friendly graphical
user interface to compute all 27 core indices . It also
conducts simple quality control on the input daily data.
It has been developed and maintained by Xuebin Zhang
and Yang Feng at Climate Research Division. The
software was used first at the South Africa Workshop in
Cape Town, South Africa, in June 2004
• FClimDex: The FClimDex is a FORTRAN program that
conducts data quality control and computes all the
indices. Note that a FORTRAN 90 compiler is required
to use this program.
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24. Software for index calculation
• ClimDex: An older MicroSoft Excel based
indices software ClimDex, developed by Byron
Gleason of the U.S. National Climatic Data
Centre is still available. This software was used
at the Caribbean Regional Climate Change
workshop was held in Kingston, Jamaica in
January 2001. Note that this software does
not include recent improvements
recommended by ET and is not supported
anymore.
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25. Climdex and 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
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26. Rclimdex ver. 1.3
• Can be used to calculate 27 core indices (as
recommended by the CCl/CLIVAR )
• Developed under R 1.84 or higher
• Limitation:
– Simple data quality control
– Not include Data homogenization
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27. Rclimdex ver. 1.3
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 cover of 70% of data
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28. • Software and user manual can be downloaded
from :
http://cccma.seos.uvic.ca/ETCCDMI/software.shtml
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29. Rclimdex Quickguide
• The R software must be installed before run
Rclimdex
• R software can be downloaded from:
http://www.r-project.org
Select the R software based on the OS
(Microsoft Window or UNIX)
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30. Rclimdex Quickguide
Data Preparation:
1. Data must be formatted as 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 are allowed)
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31. Rclimdex Quickguide
• Sample data:
Year
Month
Day
Precipitation
(mm)
TMax
(oC)
TMin
(oC)
Missing data
Calendar date order – missing dates are allowed
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32. Rclimdex Quickguide
1. Load
RClimdex
2. Load
Data->Run
QC
3. Indices
Calculation
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33. 1. Within the R consol prompt “>”, enter
source(“rclimdex.r”). This will load RClimDex
into R environment
Type: source (“rclimdex path”)
– source("C:climateindicesrclimdex.r")
– source (“http://cccma.seos.uvic.ca/ETCCDMI/RClimDex/rclimdex.r”)
2. Choose the “File” from the RGui menu, and
then select “Source R code” (recommended)
Load RClimdex
Load Data->Run
QC
Indices Calculation
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34. Rclimdex Quickguide
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35. • Data Quality Control is a prerequisite for indices
calculations
• The RClimDex QC performs the following procedure:
– Replace all missing values (currently coded as -99.9) into an
internal format that R recognizes (i.e. NA, not available)
– Replace all unreasonable values into NA
• Unreasonable values include s
– 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
Load RClimdex
Load Data->Run
QC
Indices Calculation
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36. • Select “Load Data and Run QC” from the
RClimDex Menu to open a window
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37. QC result
1. ____tempQC.csv unreasonable temperature
2. ____prcpQC.csv unreasonable precipitation
3. ____tepstdQC.csv all possible outliers in daily
temperature with the dates on which those outliers occur
4. ____indcal.csv QC’d data and will be used for the
indices calculation
Note:
The indices are computed from the QC’d data. If a user
modifies the original data file to correct some of the
problematic values, the Load Data and Run QC procedure
needs to be performed again before continue to the next
steps
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38. • RClimDex computes 27 core climate indices
• Parameters input:
– First and last year of base period for the threshold
calculation
– Station Latitude (South hemisphere (-))
– Daily precipitation threshold, P (in mm)
– Upper and Limit of Day High
– Upper and Limit of Day Low
Load RClimdex
Load Data->Run
QC
Indices Calculation
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40. Calculation done
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41. • Selection of indices
• Outputs are stored as the excel and jpeg files
(folder)
• Jpeg file format: trends computed by linear
least square (solid line) and locally weighted
linear regression (dashed line)
Load RClimdex
Load Data->Run
QC
Indices Calculation
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linear least square
locally weighted linear regression

44. THANK YOU
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45. Hands-on Rclimdex tutorial
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46. Accessing climate data from NOAA
data center
• Go to http://www.ncdc.noaa.gov/
• Select Data Access > Land Base station
• Select Climate data Online (CDO)
• Select Search Tool
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47. • Fill the form and click “SEARCH”
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48. • Select “View Full detail”
• Select “see station list
below”
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52. • The data link will be sent by email
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