Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
doi:10.5194/hess-2017-6
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
01 Feb 2017
Review status
This discussion paper is under review for the journal Hydrology and Earth System Sciences (HESS).
A discrete wavelet spectrum approach to identifying non-monotonic trend pattern of hydroclimate data
Yan-Fang Sang1, Fubao Sun1, Vijay P. Singh2, Ping Xie3, and Jian Sun1 1Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2Department of Biological and Agricultural Engineering & Zachry Department of Civil Engineering, Texas A and M University, 321 Scoates Hall, 2117 TAMU, College Station, Texas 77843-2117, USA
3State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
Abstract. Hydroclimate system is changing non-monotonically and identifying its trend pattern is a great challenge. Building on the discrete wavelet transform theory, we develop a discrete wavelet spectrum (DWS) approach for identifying non-monotonic trend patterns in hydroclimate time series and evaluating their statistical significance. After validating the DWS approach using two typical synthetic time series, we examined the temperature and potential evaporation over China from 1961–2013, and found that the DWS approach detected both the warming and the warming hiatus in temperature, and the reversed changes in potential evaporation. Interestingly, the identified trend patterns showed stable significance when the time series was longer than 30 years or so (i.e., the widely defined climate timescale). Our results suggest that non-monotonic trend patterns of hydroclimate time series and their significance should be carefully identified, and the DWS approach has the potential for wide use in hydrological and climate sciences.

Citation: Sang, Y.-F., Sun, F., Singh, V. P., Xie, P., and Sun, J.: A discrete wavelet spectrum approach to identifying non-monotonic trend pattern of hydroclimate data, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2017-6, in review, 2017.
Yan-Fang Sang et al.
Yan-Fang Sang et al.
Yan-Fang Sang et al.

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