Climate change is one of the great environmental issues of the 21st century. However, variations and trends in extreme climate are more sensitive to climate change than the mean values and thus have received significantly more attention [1
]. Extreme weather and climate events have received increased attention because they are associated with high losses of human life and increasing expenses [2
]. The greatest threat to humans and the natural environment is manifested locally via changes in regional extreme weather and climate events [4
]. Changes in the frequency or intensity of extreme weather and climate events have profound impacts on both human society and the natural environment [1
] because society as a whole is vulnerable to extreme weather and climate [6
The Mongolian Plateau (MP) is located in an arid to semi-arid region. Its annual precipitation is only 246.1 mm. In contrast, annual potential evaporation (PE) is 986.4 mm, which significantly increases the aridity index. The MP has experienced several extreme climate events during the past decades, including severe extreme cold and droughts [7
]. The consecutive 1999–2002 droughts and dzuds were the worst recorded during the last 50 years and caused 30% of the national herd losses in Mongolia [9
]. The 2009–2010 dzud was also very severe in which 8.5 million livestock died in Mongolia, amounting to 20% of the national herd [10
]. The frequency and magnitude of these extreme events have increased during the 2000–2010 period, compared with those recorded in a few decades prior to 2000 [11
], and are expected to increase with future climate changes [10
]. Therefore, it is meaningful to investigate extreme cold and drought over the MP.
Various approaches have been taken to address the potential changes in extreme climate. The World Meteorological Organization Commission for Climatology/Climate Variability held a meeting in Geneva in November 1999, and was the first to recommended 10 simple and feasible indices for climate extremes [12
]. A number of indices of climate extremes have been developed for easy calculation and application in different parts of the world [13
]. It has been suggested that the worldwide use of accepted climate extreme indices should allow for comparisons with associated information from various regional-scale studies and provide evidence of changes in extreme weather and climate events [14
]. The most frequently used of these indices is the Expert Team on Climate Change Detection and Indices (ETCCDI), which have been recommended by the Royal Netherlands Meteorological Institute. In this study, ETCCDI indices are used to evaluate the extreme cold of the MP by percentile and frequency of daily air temperature.
There are many drought indices that have been proposed [15
]. These indices can be categorized into three forms, the meteorological, hydrological, and agricultural drought indices. In this study, we focus on meteorological drought. Some popular meteorological drought indices, which are calculated by climate data, include the standardized precipitation index (SPI), Palmer drought severity index (PDSI), standardized precipitation evapotranspiration index, and the regional drought area index. Each index has particular strengths and weaknesses [16
]. The SPI and the PDSI are more popular than other indices [17
]. Keyantash and Dracup [15
] evaluated these meteorological drought indices by applying a weighted set of six evaluation criteria and found that the SPI showed better performance than the PDSI. Hayes et al. [17
] found that the SPI improved drought detection and monitoring capabilities over the PDSI when monitoring the 1996 drought in the United States. The SPI is an ideal candidate for drought risk analysis due to its intrinsic probabilistic nature [19
]. It has several advantages in terms of great flexibility, less complexity, and statistical consistency [20
]. The length of precipitation records for SPI calculation is a continuous period of at least 30 years [21
]. Because the SPI is a probability-related index, longer record lengths relate to greater confidence in the stability of the underlying statistics. Therefore, it is recommended that the length of precipitation data used in SPI calculation should be as long as possible [22
In this study, extreme cold and meteorological drought in the MP are evaluated by meteorological observed data and statistical recorded historical data. Firstly, several extreme temperature indices, defined by ETCCDI, are calculated as extreme cold indices. Trends of extreme cold indices are detected by using a non-parametric Mann–Kendall test method. Their spatial distribution is also investigated. Secondly, drought indices, including multiple timescales of the SPI and the comprehensive meteorological drought index (CMDI), are calculated and evaluated by using recorded historical drought data in the Chinese region of the MP. Finally, the evaluated drought indices that performed better in the Chinese region were applied for detecting drought characteristics of the entire MP. Drought characteristics include spatial patterns, temporal characteristics, and trends.
Extreme cold and meteorological drought in the MP were investigated in this study. Several drought indices were evaluated by using recorded historical drought data in the Chinese region of the MP. The evaluated drought indices that performed better at the Chinese region were then applied to detect drought characteristics in the entire MP. The conclusions are presented in this section.
Trends of extreme cold indices showed that the climate of the MP has warmed during the past 49 years. Extreme air temperature (TXn, TNn, TX_Ann, and TN_Ann) increased by 0.12 °C/10 years, 0.28 °C/10 years, 0.30 °C/10 years, and 0.42 °C/10 years, respectively. The frequency of cold days and nights decreased by −0.33%/10 years and −0.73%/10 years, respectively. FD and ID decreased by −2.95 days/10 years and −2.48 days/10 years, respectively. Similar trends of extreme cold indices were exhibited in the Chinese region. In general, the significance level of these trends in the Chinese region was greater than that in the Mongolian region; however, the frequency of cold days/nights was increased in the Mongolian region. The climate of Mongolia showed colder temperatures in the spring season. Moreover, the coldest day showed a decreasing trend in the Hulunbuir pasture land, which indicates that the coldest day became even colder in this region.
The CMDI and the SPI6 exhibited the best performances when detecting drought areas of the Inner Mongolia Autonomous Region and the number of drought events at 15 stations, respectively. The CMDI tended to identify more mild droughts and moderate droughts, whereas the SPI6 tended to detect more severe and extreme drought events. Spring droughts were more severe than those in other seasons in the MP. Because agricultural water is in urgent demand in spring, this result was undesirable for agriculture in the MP.
In general, drought in the MP was enhanced during the period 1969–2017. Drought in the Chinese region was enhanced greater than that in the Mongolian region. Drought represented by the SPI6 was enhanced more than that expressed by the CMDI. Spring drought showed weakening, which was beneficial for agriculture and husbandry in some regions of the MP where water demand in the spring is critical for crops and pastures. Drought was enhanced from August to October, which is consistent with that in the annual cycle. This enhanced trend of drought was greater for the CMDI than that for the SPI6, greater in the Mongolian region than that in the Chinese region, and opposite to the annual cycle. These results challenged the agriculture and husbandry sectors in the MP, particularly in the Mongolian region.
Drought represented by the two indices was consistent with precipitation for the monthly cycle but not for the annual cycle. In the Chinese region, drought represented by the two indices was enhanced more at the Ordos Plateau, Alashan Plateau, and the Xiliao River basin.