Recent temperature trends at mountain stations on the southern slope of the central Himalayas

Insufficient long-term in situ observations and complex topographic conditions pose major problems in quantifying the magnitude of climatic trends in mountainous regions such as Nepal. Presented here is three decades (1980–2009) of data on annual maximum, minimum and average temperature trends from 13 mountain stations on the southern slope of the central Himalayas. The stations are located at elevations between 1304 and 2566 m above sea level and with varied topography. Spatial analyses of the average temperature trend show warming in most of the stations. The magnitude of warming is higher for maximum temperatures, while minimum temperatures exhibit larger variability such as positive, negative or no change. These results are consistent with patterns reported in some parts of the Indian subcontinent and Upper Indus Basin, but different from conditions on the Tibetan Plateau (China), where the warming of minimum temperatures is more prominent than that of the maximum temperatures. From the temporal variations, a dramatic increase in temperature is observed in the latest decade, particularly in the average and maximum temperatures. The results from the cumulative sum chart analyses suggest that the thermal regime shifted in 1997. The dramatic enhancement of average temperature in the last decade is strongly consistent with the result of contemporary studies of the surrounding regions, where warming is attributed to an increase in anthropogenic greenhouse gases. However, as in the western Himalayas and the Upper Indus Basin, the mountain stations on the southern slope of the central Himalayas show variability in temperature trends, particularly for the minimum temperature. This inhomogeneous trend is likely ascribed to the differences in topography and microclimatic regime of the observed stations.

Appendix

1.1 Grubbs method

Grubb’s test is based on normal distribution of the data series. In this test, we have two hypotheses: Null-hypothesis (H₀) and alternative hypothesis (H₁)

H₀: There are no outliers in the dataset.

H₁: There is at least one outlier in the dataset.

The general formula for Grubb’s test is followed:

$$ G=\frac{\left| {X_i -\overline X } \right|}{\sigma }, $$

(3)

where X _i = element of the dataset, $\overline X$ = mean of the dataset and σ = standard deviation of the dataset. The calculated value of parameter G is compared with the critical value for Grubb’s test. When the calculated value is higher or lower than the critical value C, then the value can be accepted as an outlier. The critical value of the Grubbs’ test is calculated in equation (4)

$$ C=\frac{\left( {n-1} \right)}{\sqrt n }\sqrt {\frac{t_{\left( {\frac{\alpha }{2n},n-2} \right)}^2 }{n-2+t_{\left( {\frac{\alpha }{2n},n-2} \right)}^2 }} , $$

(4)

where $t_{\left( {\frac{\alpha }{2n},n-2} \right)}$ denotes the critical value of the t-distribution with (n −2) degrees of freedom and a significance level of $\alpha \mathord{\left/ {\vphantom {\alpha {2n}}} \right. \kern-\nulldelimiterspace} {2n}$. If G ≥ C, then the suspected value is confirmed as an outlier (Grubbs 1950).