What is a climate index#

A climate index is a calculated value that can be used to describe the state and the changes in the climate system. The climate at a defined place is the average state of the atmosphere over a longer period of, for example, months or years. Changes on climate are much slower than on the weather, that can change strongly day by day.

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.

Note

A good introduction for climate indices is on the website of the Integrated Climate Data Center (ICDC) of the University of Hamburg.

icclim capabilities#

Currently, the climate indices as defined by European Climate Assessment & Dataset based on air temperature and precipitation variables can be computed with icclim:

  • 11 cold indices (GD4, CFD, FD, HD17, ID, CSDI, TG10p, TN10p, TX10p, TXn, TNn)

  • 1 drought indice (CDD)

  • 9 heat indices (SU, TR, WSDI, TG90p, TN90p, TX90p, TXx, TNx, CSU)

  • 14 rain indices (PRCPTOT, RR1, SDII, CWD, R10mm, R20mm, RX1day, RX5day, R75p, R75pTOT, R95p, R95pTOT, R99p, R99pTOT)

  • 4 snow indices (SD, SD1, SD5cm, SD50cm)

  • 6 temperature indices (TG, TN, TX, DTR, ETR, vDTR)

  • 4 compound indices (CD, CW, WD, WW)

Detailed description of each indice is available at https://knmi-ecad-assets-prd.s3.amazonaws.com/documents/atbd.pdf. See table below for a short description of each indices. Most descriptions are extracted from clix-meta. Initially icclim was designed for online computing of climate indices through the climate4impact portal. In spite of existence of other packages able to compute climate indices (CDO, R package ), it was decided to develop a new software in Python. Python language was first of all chosen to interface with PyWPS: Python implementation of Web Processing Service (WPS) Standard. Another reason was to interface eventually with the OpenClimateGIS.

short name

Description

TG

Mean of daily mean temperature

TN

Mean of daily minimum temperature

TX

Mean of daily maximum temperature

DTR

Mean Diurnal Temperature Range

ETR

Intra-period extreme temperature range

vDTR

Mean day-to-day variation in Diurnal Temperature Range

SU

Number of Summer Days (Tmax > 25C)

TR

Number of Tropical Nights (Tmin > 20C)

WSDI

Warm-spell duration index

TG90p

Percentage of days when Tmean > 90th percentile

TN90p

Percentage of days when Tmin > 90th percentile

TX90p

Percentage of days when Tmax > 90th percentile

TXx

Maximum daily maximum temperature

TNx

Maximum daily minimum temperature

CSU

Maximum number of consecutive summer days (Tmax >25 C)

GD4

Growing degree days (sum of Tmean > 4 C)

FD

Number of Frost Days (Tmin < 0C)

CFD

Maximum number of consecutive frost days (Tmin < 0 C)

HD17

Heating degree days (sum of Tmean < 17 C)

ID

Number of sharp Ice Days (Tmax < 0C)

TG10p

Percentage of days when Tmean < 10th percentile

TN10p

Percentage of days when Tmin < 10th percentile

TX10p

Percentage of days when Tmax < 10th percentile

TXn

Minimum daily maximum temperature

TNn

Minimum daily minimum temperature

CSDI

Cold-spell duration index

CDD

Maximum consecutive dry days (Precip < 1mm)

PRCPTOT

Total precipitation during Wet Days

RR1

Number of Wet Days (precip >= 1 mm)

SDII

Average precipitation during Wet Days (SDII)

CWD

Maximum consecutive wet days (Precip >= 1mm)

R10mm

Number of heavy precipitation days (Precip >=10mm)

R20mm

Number of very heavy precipitation days (Precip >= 20mm)

RX1day

Maximum 1-day precipitation

RX5day

Maximum 5-day precipitation

R75p

(in discussion) Days with RR > 75th percentile of daily amounts (wet days)

R75pTOT

(in discussion) Precipitation fraction due to very wet days (> 75th percentile)

R95p

(in discussion) Days with RR > 95th percentile of daily amounts (very wet days)

R95pTOT

(in discussion) Precipitation fraction due to very wet days (> 95th percentile)

R99p

(in discussion) Days with RR > 99th percentile of daily amounts (extremely wet days)

R99pTOT

(in discussion) Precipitation fraction due to very wet days (> 99th percentile)

SD

Mean of daily snow depth

SD1

Snow days (SD >= 1 cm)

SD5cm

Number of days with snow depth >= 5 cm

SD50cm

Number of days with snow depth >= 50 cm

CD

Days with TG < 25th percentile of daily mean temperature and RR <25th percentile of daily precipitation sum

CW

Days with TG < 25th percentile of daily mean temperature and RR >75th percentile of daily precipitation sum

WD

Days with TG > 75th percentile of daily mean temperature and RR <25th percentile of daily precipitation sum

WW

Days with TG > 75th percentile of daily mean temperature and RR >75th percentile of daily precipitation sum