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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)
2/27/2015 1
I Putu Santikayasa
Outlines
1. Introduction
2. What is climate?
3. Climate Indices Project
4. What is Climate indices?
5. R - climdex
6. Case Study
2/27/2015 Tutorial class 2
Introduction
2/27/2015 Tutorial class 3
Figure 1. Schematic view of the components of the climate system, their processes
and interactions. (source: IPCC)
Introduction
2/27/2015 Tutorial class 4
Please refer to the Koppen
cimate classification
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
2/27/2015 Tutorial class 5
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
2/27/2015 Tutorial class 6
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
2/27/2015 Tutorial class 7
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
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.
2/27/2015 Tutorial class 9
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
2/27/2015 Tutorial class 10
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
2/27/2015 Tutorial class 11
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).
2/27/2015 Tutorial class 12
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)
2/27/2015 Tutorial class 13
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)
2/27/2015 Tutorial class 14
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)
2/27/2015 Tutorial class 15
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)
2/27/2015 Tutorial class 16
*) not directly calculated by RClimDex but have been defined for this study as TXx–
TNn
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
2/27/2015 Tutorial class 17
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
2/27/2015 Tutorial class 18
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
2/27/2015 Tutorial class 19
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
2/27/2015 Tutorial class 20
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
2/27/2015 Tutorial class 21
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
2/27/2015 Tutorial class 22
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.
2/27/2015 Tutorial class 23
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.
2/27/2015 Tutorial class 24
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
2/27/2015 Tutorial class 25
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
2/27/2015 Tutorial class 26
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
2/27/2015 Tutorial class 27
• Software and user manual can be downloaded
from :
http://cccma.seos.uvic.ca/ETCCDMI/software.shtml
2/27/2015 Tutorial class 28
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)
2/27/2015 Tutorial class 29
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)
2/27/2015 Tutorial class 30
Rclimdex Quickguide
• Sample data:
Year
Month
Day
Precipitation
(mm)
TMax
(oC)
TMin
(oC)
Missing data
Calendar date order – missing dates are allowed
2/27/2015 Tutorial class 31
Rclimdex Quickguide
1. Load
RClimdex
2. Load
Data->Run
QC
3. Indices
Calculation
2/27/2015 Tutorial class 32
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
2/27/2015 Tutorial class 33
Rclimdex Quickguide
2/27/2015 Tutorial class 34
• 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
2/27/2015 Tutorial class 35
• Select “Load Data and Run QC” from the
RClimDex Menu to open a window
2/27/2015 Tutorial class 36
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
2/27/2015 Tutorial class 37
• 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
2/27/2015 Tutorial class 38
2/27/2015 Tutorial class 39
Calculation done
2/27/2015 Tutorial class 40
• 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
2/27/2015 Tutorial class 41
2/27/2015 Tutorial class 42
2/27/2015 Tutorial class 43
linear least square
locally weighted linear regression
THANK YOU
2/27/2015 Tutorial class 44
Hands-on Rclimdex tutorial
2/27/2015 Tutorial class 45
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
2/27/2015 Tutorial class 46
• Fill the form and click “SEARCH”
2/27/2015 Tutorial class 47
• Select “View Full detail”
• Select “see station list
below”
2/27/2015 Tutorial class 48
2/27/2015 Tutorial class 49
2/27/2015 Tutorial class 50
2/27/2015 Tutorial class 51
• The data link will be sent by email
2/27/2015 Tutorial class 52

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Climate Change Indices Software

  • 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) 2/27/2015 1 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 2/27/2015 Tutorial class 2
  • 3. Introduction 2/27/2015 Tutorial class 3 Figure 1. Schematic view of the components of the climate system, their processes and interactions. (source: IPCC)
  • 4. Introduction 2/27/2015 Tutorial class 4 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 2/27/2015 Tutorial class 5
  • 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 2/27/2015 Tutorial class 6
  • 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 2/27/2015 Tutorial class 7
  • 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. 2/27/2015 Tutorial class 9
  • 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 2/27/2015 Tutorial class 10
  • 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 2/27/2015 Tutorial class 11
  • 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). 2/27/2015 Tutorial class 12
  • 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) 2/27/2015 Tutorial class 13
  • 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) 2/27/2015 Tutorial class 14
  • 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) 2/27/2015 Tutorial class 15
  • 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) 2/27/2015 Tutorial class 16 *) 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 2/27/2015 Tutorial class 17
  • 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 2/27/2015 Tutorial class 18
  • 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 2/27/2015 Tutorial class 19
  • 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 2/27/2015 Tutorial class 20
  • 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 2/27/2015 Tutorial class 21
  • 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 2/27/2015 Tutorial class 22
  • 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. 2/27/2015 Tutorial class 23
  • 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. 2/27/2015 Tutorial class 24
  • 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 2/27/2015 Tutorial class 25
  • 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 2/27/2015 Tutorial class 26
  • 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 2/27/2015 Tutorial class 27
  • 28. • Software and user manual can be downloaded from : http://cccma.seos.uvic.ca/ETCCDMI/software.shtml 2/27/2015 Tutorial class 28
  • 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) 2/27/2015 Tutorial class 29
  • 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) 2/27/2015 Tutorial class 30
  • 31. Rclimdex Quickguide • Sample data: Year Month Day Precipitation (mm) TMax (oC) TMin (oC) Missing data Calendar date order – missing dates are allowed 2/27/2015 Tutorial class 31
  • 32. Rclimdex Quickguide 1. Load RClimdex 2. Load Data->Run QC 3. Indices Calculation 2/27/2015 Tutorial class 32
  • 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 2/27/2015 Tutorial class 33
  • 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 2/27/2015 Tutorial class 35
  • 36. • Select “Load Data and Run QC” from the RClimDex Menu to open a window 2/27/2015 Tutorial class 36
  • 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 2/27/2015 Tutorial class 37
  • 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 2/27/2015 Tutorial class 38
  • 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 2/27/2015 Tutorial class 41
  • 43. 2/27/2015 Tutorial class 43 linear least square locally weighted linear regression
  • 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 2/27/2015 Tutorial class 46
  • 47. • Fill the form and click “SEARCH” 2/27/2015 Tutorial class 47
  • 48. • Select “View Full detail” • Select “see station list below” 2/27/2015 Tutorial class 48
  • 52. • The data link will be sent by email 2/27/2015 Tutorial class 52