Definitions of the core climate extreme indices (Climdex)

There are 27 core climate extreme indices^{Footnote 1}

Index	Definition	Variable
Number of frost days (FD)	Annual count of days when daily minimum temperature is less than 0°C. Let TN_ij be daily minimum temperature on day i in year j. Count the number of days where: TN_ij < 0°C	minimum temperature
Number of summer days (SU)	Annual count of days when daily maximum temperature is greater than 25°C. Let TX_ij be daily maximum temperature on day i in year j. Count the number of days where: TX_ij > 25°C	maximum temperature
Number of icing days (ID)	Annual count of days when daily maximum temperature is less than 0°C. Let TX_ij be daily maximum temperature on day i in year j. Count the number of days where: TX_ij < 0°C	maximum temperature
Number of tropical nights (TR)	Annual count of days when daily minimum temperature is greater than 20°C. Let TN_ij be daily minimum temperature on day i in year j. Count the number of days where: TN_ij > 20°C	minimum temperature
Growing season length (GSL)	Annual (January 1 to December 31 in Northern Hemisphere (NH), July 1 to June 30 in Southern Hemisphere (SH)) count between first span of at least 6 days with daily mean temperature greater than 5°C and first span after July 1 (January 1 in SH) of 6 days with daily mean temperature less than 5°C. 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°C and the first occurrence after July 1 (January 1 in SH) of at least 6 consecutive days with: TG_ij < 5°C.	mean temperature
Monthly maximum value of daily maximum temperature (TX_x)	Let TX_x be the daily maximum temperatures in month k, period j. The maximum daily maximum temperature each month is then: TX_{x_kj} = max(TX_{x_kj})	maximum temperature
Monthly maximum value of daily minimum temperature (TN_x)	Let TN_x be the daily minimum temperatures in month k, period j. The maximum daily minimum temperature each month is then: TN_{x_kj} = max(TN_{x_kj})	minimum temperature
Monthly minimum value of daily maximum temperature (TX_n)	Let TX_n be the daily maximum temperatures in month k, period j. The minimum daily maximum temperature each month is then: TX_{n_kj} = min(TX_{n_kj})	maximum temperature
Monthly minimum value of daily minimum temperature (TN_n)	Let TN_n be the daily minimum temperatures in month k, period j. The minimum daily minimum temperature each month is then: TN_{n_kj} = min(TN_{n_kj})	minimum temperature
Percentage of days when daily minimum temperature is less than the 10th percentile (TN10p)	Let TN_ij be the daily minimum temperature on day i in period j and let TN_in10 be the calendar day 10th 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 procedure. Details are described in Zhang et al. (2005).	minimum temperature
Percentage of days when daily maximum temperature is less than the 10th percentile (TX10p)	Let TX_ij be the daily maximum temperature on day i in period j and let TX_in10 be the calendar day 10th 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 procedure. Details are described in Zhang et al. (2005).	maximum temperature
Percentage of days when daily minimum temperature is greater than the 90th percentile (TN90p)	Let TN_ij be the daily minimum temperature on day i in period j and let TN_in90 be the calendar day 90th 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. (2005).	minimum temperature
Percentage of days when daily maximum temperature is greater than the 90th percentile (TX90p)	Let TX_ij be the daily maximum temperature on day i in period j and let TX_in90 be the calendar day 90th 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. (2005).	maximum temperature
Warm spell duration index (WSDI)	Annual count of days with at least 6 consecutive days when daily maximum temperature is greater than the 90th percentile. Let TX_ij be the daily maximum temperature on day i in period j and let TX_in90 be the calendar day 90th 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	maximum temperature
Cold spell duration index (CSDI)	Annual count of days with at least 6 consecutive days when daily minimum temperature is less than the 10th percentile. Let TN_ij be the daily minimum temperature on day i in period j and let TN_in10 be the calendar day 10th 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	minimum temperature
Daily temperature range (DTR)	Monthly mean difference between daily maximum and minimum temperature 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: DTR_j = $\frac{\sum_{i = 1}^{I} (T X_{i j} - T N_{i j})}{I}$	minimum temperature maximum temperature
Monthly maximum 1-day precipitation (Rx1day)	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)	precipitation
Monthly maximum consecutive 5-day precipitation (Rx5day)	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)	precipitation
Annual count of days when precipitation is greater than or equal to 10mm (R10mm)	Let RR_ij be the daily precipitation amount on day i in period j. Count the number of days where: RR_ij ≥ 10mm	precipitation
Simple precipitation intensity index (SDII)	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: SDII_j = $\frac{\sum_{w = 1}^{W} R R_{w j}}{W}$	precipitation
Annual count of days when precipitation is greater than or equal to 20mm (R20mm)	Let RR_ij be the daily precipitation amount on day i in period j. Count the number of days where: RR_ij ≥ 20mm	precipitation
Annual count of days when precipitation is greater than or equal to "nnmm", nn is a user defined threshold (Rnnmm)	Let RR_ij be the daily precipitation amount on day i in period j. Count the number of days where: RR_ij ≥ nnmm	precipitation
Maximum length of dry spell, maximum number of consecutive days with daily precipitation less than 1mm (CDD)	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	precipitation
Maximum length of wet spell, maximum number of consecutive days with daily precipitation greater than or equal to 1mm (CWD)	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	precipitation
Annual total precipitation when daily precipitation is greater than the 95th percentile (R95pTOT)	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 95th percentile of precipitation on wet days in the 1961-1990 period. If W represents the number of wet days in the period, then: R95p_j = $\sum_{w = 1}^{W}$ RR_wj where RR_wj > RR_wn95	precipitation
Annual total precipitation when daily precipitation is greater than the 99th percentile (R99pTOT)	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 99th percentile of precipitation on wet days in the 1961-1990 period. If W represents the number of wet days in the period, then: R99p_j = $\sum_{w = 1}^{W}$ RR_wj where RR_wj > RR_wn99	precipitation
Annual total precipitation in wet days (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: PRCPTOT_j = $\sum_{i = 1}^{I}$ RR_ij	precipitation

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Date modified:: 2019-03-01

Definitions of the core climate extreme indices (Climdex)

There are 27 core climate extreme indicesFootnote 1

"Page details"

There are 27 core climate extreme indices^{Footnote 1}