Low-frequency drought variability based on SPEI in association with climate indices in Beijing

Abstract

Drought occurs in nature when precipitation is significantly lower than normal. When lasting many months or even years in a large area, drought will develop into a natural hazard that permanently damages the environment and causes great economic losses. Thus, improving our knowledge about the variability and impacts of drought is fundamental to quantify the drought hazard and improve the prediction and drought mitigation. Beijing is located in the middle and lower reaches of Haihe River Basin, which belong to a temperate continental monsoon climate zone. The precipitation distribution is very uneven, and often accompanied by high temperature. So drought is one of the most frequently and enduring natural hazard that influences most area in Beijing, north China. In this paper, we analyzed the variability and possible teleconnections between drought occurrences and large-scale climate indices between 1868-2010 in Beijng, such as El Ni?o-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Arctic Oscillation (AO), and Pacific Decadal Oscillation (PDO). The drought occurrences were quantified by a new drought index, Standardized Precipitation Evapotranspiration Index (SPEI) based on the data of monthly mean temperature and precipitation. The SPEI considers not only precipitation but also temperature data by means of evapotranspiration in calculation, allowing for a more complete approach to explore the effects of climate changes on drought occurrences under global warming. The SPEI can also be calculated at several time scales to adapt to the critical times of responses to drought in target natural and economic systems and to determine their resistance to drought. Local historical drought hazard records in Beijing since 1868 were used to improve the validation of SPEI. We then used the method of continuous wavelet transform (CWT) to analyze inter-decadal and decadal oscillation in the time and frequency of drought. Finally, we analyzed the correlations between SPEI and four large scale climate indices through the cross wavelet transform (XWT). The good agreement between SPEI and historical drought records proves that SPEI can effectively reflect the intensity and duration of drought in multi-temporal dimension in this region. SPEI of Beijing had 80-120 month, 250 month, and 480 month oscillation circles, which was similar to the pattern of the four large-scale climate indices. The significant coherence was found between SPEI and the four large-scale climate indices. There were the common patterns of 100-120 month decadal and 250 month inter-decadal oscillation circles between SPEI and NAO, AO, PDO, as well as a common pattern of 32-64 month inter-decadal oscillation circle between SPEI and ENSO during the whole period. There was a clear lag time (2-6 months) during the coherence circle. Therefore, we can forecast the future drought variations in Beijing based on the data of large scale climate indices and SPEI, which is useful for water resources management and agriculture. This article is an initial step to application of the new multi-scalar SPEI drought index in studying the drought variability and impacts in China.