NmedianQ
4.2.4 Extreme rainfall and temperature indices
The analysis of rainfall and temperature extremes was based on the indices developed under the World Climate Research Programme on Climate Variability and Predictability (CLIVAR) Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI) (Peterson et al. 2001; Klein Tank et al. 2006; Alexander et al. 2006). Sixteen of the 27 indices recommended by the ETCCDMI are temperature related and eleven are precipitation related (Klein Tank et al. 2006). They are derived from daily maximum and minimum temperature and daily precipitation. Exact definitions of all the indices are available from the ETCCDI website (http://cccma.seos.uvic.ca/ETCCDI).
The rainfall threshold indices R10mm and R20mm were not considered because such events are very common in this region. The user defined threshold index Rnnmm was calculated in this study for rainfall 75 mm, 100 mm and 125 mm. Simple precipitation intensity index was calculated on rainy days (rainfall ≥ 2.5 mm) instead of wet days (rainfall ≥ 1 mm) given by Klein Tank et al. (2006). Seven temperature indices not relevant (4.11)
(4.12) (4.10)
to the studied region like number of frost days (FD), ice days (ID) etc were omitted.
Instead, four intensity indices with fixed threshold (Revadekar et al. 2012) were considered in this study. Selective indices used in the present study for rainfall are demonstrated in Table 4.4 and temperature in Table 4.5. Based upon availability of data, the period 1961–
1990 for rainfall and 1971–2000 for temperature was chosen as the base period for the indices that represent counts of days crossing the climatological percentile thresholds.
Table 4.4 Definition of rainfall indices used in the study
Sl No Index Descriptive name Definition Units
1 R75 mm Rainfall above 75 mm Count of days when R ≥75 mm d 2 R100 mm Rainfall above 100 mm Count of days when R ≥100 mm d 3 R125 mm Rainfall above 125 mm Count of days when R ≥125 mm d 4 Rx1-day Maximum 1-day rainfall Annual highest rainfall in a year mm 5 SDII Simple daily intensity index Average rainfall on rainy days mm/d 6 R99pTOT Extremely wet day rainfall Rainfall fraction due to R99p mm 7 R95pTOT Very wet day rainfall Rainfall fraction due to R95p mm 8 R75pTOT Moderate wet day rainfall Rainfall fraction due to R75p mm The annual as well as seasonal rainfall extreme indices were calculated for the entire 55 years (1955–2010) for the individual stations. In addition to station level analysis, trend analysis was performed for three sub-regions (eastern, central and western part) as well as for the Brahmaputra valley as a whole. The extreme rainfall indices for different parts of the Brahmaputra valley were computed by arithmetic means (Revadekar et al. 2012) of indices at all the individual stations falling in each part of the valley. Similarly, the extremes indices for the Brahmaputra valley as whole were estimated by averaging the indices of all three individual parts. As the extreme temperature indices showed broad spatial coherence (Alexander et al. 2006), the analysis was performed for the Brahmaputra valley as a whole. The extreme temperature indices for the Brahmaputra valley were also computed by arithmetic average of the indices of all the four stations considered in the study.
Table 4.5 Definition of temperature indices used in this study. TX and TN are daily maximum temperature and daily minimum temperature respectively
Sl No Index Descriptive name Definition Units
Intensity indices
1 TXx Hottest day Highest value of TX °C
2 TXn Coldest night Lowest value of TX °C
3 TNx Hottest night Highest value of TN °C
4 TNn Coldest day Lowest value of TN °C
Frequency indices with percentile thresholds
5 TX90p Hot day frequency Percentage of days when TX >90th percentile
d 6 TX10p Cold day frequency Percentage of days when TX <10th
percentile
d 7 TN90p Hot night frequency Percentage of days when TN >90th
percentile
d 8 TN10p Cold night frequency Percentage of days when TN <10th
percentile
d Frequency indices with fixed thresholds
9 TX 35 Hot days Number of days with TX >35°C °C
10 TX 20 Cold days Number of days with TX <20°C °C
11 TN 25 Hot nights Number of days with TN >25°C °C
12 TN 10 Cold nights Number of days with TN <10°C °C
Range index
13 DTR Diurnal temperature range Annual mean difference of TX and TN °C Non-parametric Sen’s slope method (Sen 1968) was used to detect any trends in extreme indices of rainfall and temperature and the significance of all the trends was assessed based on the Mann–Kendall test (Mann 1945; Kendall 1975) as described in sections 4.2.1.1 and 4.2.1.2. Mann–Kendal test was used by various researchers around the world. For example – Kothawale et al. (2010), Ravekedar et al. (2012) in India; Klein Tank et al. (2006) in central and South Asia; Vincent et al. (2005) in South America; Plummer et al. (1999) in Australia.
To determine whether marked changes have occurred in the annual cycles of extreme temperature events in the Brahmaputra valley, semi-average method (Revadekar et al.
2012) was followed to estimate the change. For this purpose, the annual cycles in terms of mean indices for two halves of the period consisting of 20 years each has been analysed.
Changes in mean indices for two sub-periods, viz., 1971–1990 and 1991–2010 have been computed for each month with respect to data for the entire period 1971–2010.