Number of frost days

Annual count of days when TN (daily minimum temperature) < 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.

Number of summer days

Annual count of days when TX (daily maximum temperature) > 25°C. Let TX_ij be daily minimum temperature on day i in year j. Count the number of days where TX_ij > 25 °C.

Number of icing days

Annual count of days when TX (daily maximum temperature) < 0 °C. Let TX_ijbe daily maximum temperature on day i in year j. Count the number of days where TX_ij < 0 °C.

Number of tropical nights

Annual count of days when TN (daily minimum temperature) > 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.

Growing season length

Annual* count between the first span of at least 6 days with daily mean temperature TG >5 °C and the first span after July 1^st (Jan 1^st in SH) of 6 days with TG <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 1^st July (Jan 1^st in SH) of at least 6 consecutive days with TG_ij < 5 °C.

* Annual means Jan 1^st to Dec 31^st in the Northern Hemisphere (NH); July 1^st to June 30^th in the Southern Hemisphere (SH).

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).

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).

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)

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)

Percentage of days when TN < 10th 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 procedure. Details are described in Zhang et al. (2005).

Percentage of days when TX < 10th 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. (2005).

Percentage of days when TN > 90th 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. (2005)

Percentage of days when TX > 90th 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. (2005).

Warm spell duration index: annual count of days with at least 6 consecutive days when TX > 90th 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.

Cold spell duration index: annual count of days with at least 6 consecutive days when TN < 10th 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.

Daily temperature range

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:

$${\mathrm{DTR}}_j=\frac{\underset{i=1}{\overset{I}{\sum <!--\; \sum \; -->}}({\mathrm{TX}}_{ij}-{\mathrm{TN}}_{ij})}{I}$$

Extreme temperature range

Let TX_x be the daily maximum temperature in month k and TN_n the daily minimum temperature in month k. The extreme temperature range each month is then: $${\mathrm{ETR}}_k={\mathrm{TXx}}_k-{\mathrm{TNn}}_k$$

Cooling degree days

Annual sum of TM - n, where n is a user-defined, location-specific base temperature and TM > n. A measure of the energy demand needed to cool a building.

Growing degree days

Annual sum of TM - n, where n is a user-defined, location-specific base temperature and TM > n. A measure of the energy demand needed to cool a building.

Heating degree days

Annual sum of n - TM, where n is a user-defined, location-specific base temperature and TM < n. A measure of the energy demand needed to heat a building.

TM of greater than or equal to 5 °C

Number of days when TM (daily mean temperature) ≥ 5 °C.

TM of at least 5 °C

Number of days when TM (daily mean temperature) < 5 °C.

TM of greater than or equal to 10 °C

Number of days when TM (daily mean temperature) ≥ 10 °C.

TM of at least 10 °C

Number of days when TM (daily mean temperature) < 10 °C.

Mean TM

The mean daily mean temperature.

Mean TX

The mean daily maximum temperature.

Mean TN

The mean daily minimum temperature.

TX of greater than or equal to 30 °C

Number of days when TX ≥ 30 ≥C.

TX of greater than or equal to 35 °C

Number of days when TX ≥ 35 ≥C.

Percentage of days with above average temperature

Percentage of days when TX > 50th percentile.

TN below 2 °C

The number of days when TN < 2 °C.

TN below -2 °C

The number of days when TN < -2 °C.

TN below -20 °C

The number of days when TN < -20 °C.

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)

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)

Simple precipitation 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:

$${\mathrm{SDII}}_j=\frac{\underset{w=1}{\overset{W}{\sum <!--\; \sum \; -->}}{\mathrm{RR}}_{wj}}{W}$$

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

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

Annual count of days when PRCP ≥ nn mm, where 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.

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.

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.

Annual total PRCP when RR > 95th percentile

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:

$${\mathrm{R95}}_p=\underset{w=1}{\overset{W}{\sum <!--\; \sum \; -->}}{\mathrm{RR}}_{wj}\mathrm{where}{\mathrm{RR}}_{wj}>{\mathrm{RR}}_{wn}95$$

Annual total PRCP when RR > 99th percentile

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:

$${\mathrm{R99}}_p=\underset{w=1}{\overset{W}{\sum <!--\; \sum \; -->}}{\mathrm{RR}}_{wj}\mathrm{where}{\mathrm{RR}}_{wj}>{\mathrm{RR}}_{wn}99$$

Contribution to total precipitation from very wet days

$${\mathrm{R95pTOT}}_{}=\frac{\mathrm{100\; x\; R95p}}{\mathrm{PRCPTOT}}$$

Contribution to total precipitation from extremely wet days

$${\mathrm{R99pTOT}}_{}=\frac{\mathrm{100\; x\; R99p}}{\mathrm{PRCPTOT}}$$

Annual total precipitation on wet days

Let RR_ij be the daily precipitation amount on day i in period j, then:

$${\mathrm{PRCPTOT}}_j=\underset{i=1}{\overset{I}{\sum <!--\; \sum \; -->}}{\mathrm{RR}}_{ij}$$