Abstract The absence of continuous long term meteorological dataset has led to limited knowledge of glaciers’ response to climate change over Himalayas. This study presents an open source long term temperature dataset Climatic Research Unit (CRU) available since 1901 to study trend analysis of temperature (Tmax, Tmin and Tmean) for Gangotri basin in Himalayas. The study first establishes close agreement between CRU time series data and observed temperature dataset available from National Institute of Hydrology (NIH), Roorkee for a period of 11 years from 2005 to 2015 using standard anomaly, Wilcoxon Signed-Rank (WSR) and correlation tests. The close agreement of CRU with NIH data validate the use of CRU time series to study variation in meteorological parameter for hilly terrain of Himalayas. The second part includes application of different statistical tests such as Mann-Kendall (MK), Sen’s slope and CUSUM technique on CRU data to detect existence of any possible trends and identification of change points in Tmax, Tmin and Tmean on long term scale. On annual scale, significant increasing trends for Tmean and Tmin were observed with no significant trend for Tmax. On seasonal and monthly scale, Tmax showed significant decreasing trend for monsoon season and increasing trend for winters while Tmin show significant increasing trend for all months (except May) and seasons. CUSUM technique identified 8 change points from 3 annual time series with 2 for Tmean (1974 and 1999), 3 each for Tmax (1941, 1975 and 1999) and Tmin (1941, 1965 and 1999) respectively. Overall, significant increase in Tmin with no significant trend for Tmax has been identified over the study area.

中文翻译：

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印度甘戈特里冰川气候研究单位温度数据集趋势分析

摘要 由于缺乏连续的长期气象数据集，人们对喜马拉雅山冰川对气候变化的响应认识有限。本研究提供了自 1901 年以来可用的开源长期温度数据集气候研究单位 (CRU)，用于研究喜马拉雅山甘戈特里盆地的温度趋势分析（Tmax、Tmin 和 Tmean）。该研究首先使用标准异常、Wilcoxon Signed-Rank (WSR) 和相关性检验，在 2005 年至 2015 年的 11 年期间，建立了 CRU 时间序列数据与来自 Roorkee 国家水文研究所 (NIH) 的观测温度数据集之间的密切一致性. CRU 与 NIH 数据的密切一致性验证了 CRU 时间序列用于研究喜马拉雅山丘陵地形气象参数变化的有效性。第二部分包括在 CRU 数据上应用不同的统计测试，例如 Mann-Kendall (MK)、Sen 斜率和 CUSUM 技术，以检测是否存在任何可能的趋势，并在长期尺度上识别 Tmax、Tmin 和 Tmean 的变化点。在年度尺度上，观察到 Tmean 和 Tmin 的显着增加趋势，而 Tmax 没有显着趋势。在季节和月度尺度上，Tmax 在季风季节呈显着下降趋势，在冬季呈上升趋势，而 Tmin 在所有月份（5 月除外）和季节均呈显着上升趋势。CUSUM 技术从 3 个年度时间序列中确定了 8 个变化点，其中 Tmean（1974 和 1999）有 2 个，Tmax（1941、1975 和 1999）和 Tmin（1941、1965 和 1999）各有 3 个。全面的，