Climate Change Indices

Definitions of the 27 core indices

1. FD, Number of frost days: Annual count of days when TN (daily minimum temperature) < 0^oC.

Let TN_ijbe daily minimum temperature on day i in year j. Count the number of days where:

TN_ij < 0^oC.

2. SU, Number of summer days: Annual count of days when TX (daily maximum temperature) > 25^oC.

Let TX_ij be daily maximum temperature on day i in year j. Count the number of days where:

TX_ij > 25^oC.

3. ID, Number of icing days: Annual count of days when TX (daily maximum temperature) < 0^oC.

Let TX_ijbe daily maximum temperature on day i in year j. Count the number of days where:

TX_ij < 0^oC.

4. TR, Number of tropical nights: Annual count of days when TN (daily minimum temperature) > 20^oC.

Let TN_ijbe daily minimum temperature on day i in year j. Count the number of days where:

TN_ij > 20^oC.

5. GSL, Growing season length: Annual (1^st Jan to 31^st Dec in Northern Hemisphere (NH), 1^st July to 30^th June in Southern Hemisphere (SH)) count between first span of at least 6 days with daily mean temperature TG>5^oC and first span after July 1^st (Jan 1^st in SH) of 6 days with TG<5^oC.

Let TG_ij be daily mean temperature on day i in year j. Count the number of days between the first occurrence of at least 6 consecutive days with:

TG_ij > 5^oC.

and the first occurrence after 1^st July (1^st Jan. in SH) of at least 6 consecutive days with:

TG_ij < 5^oC.

6. TX_x, Monthly maximum value of daily maximum temperature:

Let TX_x be the daily maximum temperatures in month k, period j. The maximum daily maximum temperature each month is then:

TX_xkj=max(TX_xkj)

7. TN_x, Monthly maximum value of daily minimum temperature:

Let TN_x be the daily minimum temperatures in month k, period j. The maximum daily minimum temperature each month is then:

TN_xkj=max(TN_xkj)

8. TX_n, Monthly minimum value of daily maximum temperature:

Let TX_n be the daily maximum temperatures in month k, period j. The minimum daily maximum temperature each month is then:

TX_nkj=min(TX_nkj)

9. TN_n, Monthly minimum value of daily minimum temperature:

Let TN_n be the daily minimum temperatures in month k, period j. The minimum daily minimum temperature each month is then:

TN_nkj=min(TN_nkj)

10. TN10p, Percentage of days when TN < 10^th percentile:

Let TN_ij be the daily minimum temperature on day i in period j and let TN_in10 be the calendar day 10^th percentile centred on a 5-day window for the base period 1961-1990. The percentage of time for the base period is determined where:

TN_ij < TN_in10

To avoid possible inhomogeneity across the in-base and out-base periods, the calculation for the base period (1961-1990) requires the use of a bootstrap processure. Details are described in Zhang et al. (2004) .

11. TX10p, Percentage of days when TX < 10^th percentile:

Let TX_ij be the daily maximum temperature on day i in period j and let TX_in10 be the calendar day 10^th percentile centred on a 5-day window for the base period 1961-1990. The percentage of time for the base period is determined where:

TX_ij < TX_in10

To avoid possible inhomogeneity across the in-base and out-base periods, the calculation for the base period (1961-1990) requires the use of a bootstrap processure. Details are described in Zhang et al. (2004) .

12. TN90p, Percentage of days when TN > 90^th percentile:

Let TN_ij be the daily minimum temperature on day i in period j and let TN_in90 be the calendar day 90^th percentile centred on a 5-day window for the base period 1961-1990. The percentage of time for the base period is determined where:

TN_ij > TN_in90

To avoid possible inhomogeneity across the in-base and out-base periods, the calculation for the base period (1961-1990) requires the use of a bootstrap processure. Details are described in Zhang et al. (2004) .

13. TX90p, Percentage of days when TX > 90^th percentile:

Let TX_ij be the daily maximum temperature on day i in period j and let TX_in90 be the calendar day 90^th percentile centred on a 5-day window for the base period 1961-1990. The percentage of time for the base period is determined where:

TX_ij > TX_in90

To avoid possible inhomogeneity across the in-base and out-base periods, the calculation for the base period (1961-1990) requires the use of a bootstrap processure. Details are described in Zhang et al. (2004) .

14. WSDI, Warm speel duration index: Annual count of days with at least 6 consecutive days when TX > 90^th percentile

Let TX_ij be the daily maximum temperature on day i in period j and let TX_in90 be the calendar day 90^th percentile centred on a 5-day window for the base period 1961-1990. Then the number of days per period is summed where, in intervals of at least 6 consecutive days:

TX_ij > TX_in90

15. CSDI, Cold speel duration index: Annual count of days with at least 6 consecutive days when TN < 10^th percentile

Let TN_ij be the daily maximum temperature on day i in period j and let TN_in10 be the calendar day 10^th percentile centred on a 5-day window for the base period 1961-1990. Then the number of days per period is summed where, in intervals of at least 6 consecutive days:

TN_ij < TN_in10

16. DTR, Daily temperature range: Monthly mean difference between TX and TN

Let TX_ij and TN_ij be the daily maximum and minimum temperature respectively on day i in period j. If I represents the number of days in j, then:

17. Rx1day, Monthly maximum 1-day precipitation:

Let RR_ij be the daily precipitation amount on day i in period j. The maximum 1-day value for period j are:

Rx1day_j = max (RR_ij)

18. Rx5day, Monthly maximum consecutive 5-day precipitation:

Let RR_kj be the precipitation amount for the 5-day interval ending _k, period j. Then maximum 5-day values for period j are:

Rx5day_j = max (RR_kj)

19. SDII Simple pricipitation intensity index: Let RR_wj be the daily precipitation amount on wet days, w (RR ≥ 1mm) in period j. If W represents number of wet days in j, then:

20. R10mm Annual count of days when PRCP≥ 10mm: Let RR_ij be the daily precipitation amount on day i in period j. Count the number of days where:

RR_ij ≥ 10mm

21. R20mm Annual count of days when PRCP≥ 20mm: Let RR_ij be the daily precipitation amount on day i in period j. Count the number of days where:

RR_ij ≥ 20mm

22. Rnnmm Annual count of days when PRCP≥ nnmm, nn is a user defined threshold: Let RR_ij be the daily precipitation amount on day i in period j. Count the number of days where:

RR_ij ≥ nnmm

23 CDD. Maximum length of dry spell, maximum number of consecutive days with RR < 1mm: Let RR_ij be the daily precipitation amount on day i in period j. Count the largest number of consecutive days where:

RR_ij < 1mm

24 CWD. Maximum length of wet spell, maximum number of consecutive days with RR ≥ 1mm: Let RR_ij be the daily precipitation amount on day i in period j. Count the largest number of consecutive days where:

RR_ij ≥ 1mm

25. R95pTOT. Annual total PRCP when RR > 95p. Let RR_wj be the daily precipitation amount on a wet day w (RR ≥ 1.0mm) in period i and let RR_wn95 be the 95^th percentile of precipitation on wet days in the 1961-1990 period. If W represents the number of wet days in the period, then:

26. R99pTOT. Annual total PRCP when RR > 99p: Let RR_wj be the daily precipitation amount on a wet day w (RR ≥ 1.0mm) in period i and let RR_wn99 be the 99^th percentile of precipitation on wet days in the 1961-1990 period. If W represents the number of wet days in the period, then:

27. PRCPTOT. Annual total precipitation in wet days: Let RR_ij be the daily precipitation amount on day i in period j. If I represents the number of days in j, then

References

• Karl, T.R., N. Nicholls, and A. Ghazi, 1999: CLIVAR/GCOS/WMO workshop on indices and indicators for climate extremes: Workshop summary. Climatic Change, 42, 3-7.
• Peterson, T.C., and Coauthors: Report on the Activities of the Working Group on Climate Change Detection and Related Rapporteurs 1998-2001. WMO, Rep. WCDMP-47, WMO-TD 1071, Geneve, Switzerland, 143pp.