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Extending across three major plateaus, namely the Qinghai-Tibetan Plateau, the Inner Mongolia-Xinjiang Plateau and the Loess Plateau, Northwest China has the complex terrain and spatio-temporal climate variations, and is affected by the interactions among different circulation systems, such as the summer monsoon, the westerlies and the plateau monsoon. The understanding of the climate variability, as well as its characteristics and evolution mechanisms in this area has been limited so far. In this paper, the precipitation characteristics and mechanisms in the eastern and western parts of Northwest China during the flood season are compared and analyzed based on the data from 192 national meteorological observational sites in Northwest China in 1961–2016. The results show that, divided by the northern boundary of the East Asian summer monsoon, there are huge differences in the precipitation variation characteristics between the eastern and western parts. The inter-annual variations, inter-decadal variations and total trends in the two parts all show a significant seesaw phenomenon. Moreover, it is found that the seesaw phenomenon of precipitation variation is closely related to the opposite variation between the East Asian summer monsoon index (MI) and the westerly circulation index (WI). In addition, the inverse variations on different time scales are only related to the contributions of precipitation at specific grades. Besides, in the two matching patterns of precipitation in the seesaw phenomenon, the middle and high latitudes are occupied by the "high-low-high" wave trains in the precipitation increases in the east of Northwest China (ENWC) and decreases in the west of Northwest China (WNWC) pattern, meaning precipitation increases in ENWC and decreases in WNWC. Whereas the opposite "low-high-low" wave trains at 500 hPa height are observed in the middle and high latitudes in the WH-EA pattern at 500 hPa height, meaning precipitation increases in WNWC and decreases in ENWC. Thus, the atmosphere circulation situation with two wave train types can support both the precipitation seesaw phenomenon and the opposite variation between MI and WI. Moreover, the seesaw phenomenon is shown to be related to the separate or joint effects of the South Asian High, ENSO and the plateau heating on the common but opposite effect on the summer monsoon and the westerlies, in which the South Asian High probably plays a more critical role. This study could deepen the scientific understanding of precipitation mechanisms and improve the weather forecast technology in Northwest China during the flood season. [ABSTRACT FROM AUTHOR]

Water availability is one of the most important environmental controls on vegetation phenology, especially in semi-arid regions. It is often represented in terms of soil moisture in small-scale studies, whereas it tends to be represented by precipitation in large-scale (e.g., regional) studies. Clearly, soil moisture is the more appropriate indicator for root water uptake and vegetation growth/phenology. Its potential advantage and applicability needs to be demonstrated at regional scales. The paper presents a data-based regional study of the effectiveness of novel water and temperature-based indices to predict spring vegetation green-up dates based on the Normalized Difference Vegetation Index (NDVI) observations in the grasslands of Inner Mongolia, China. The macro-scale hydrological model, VIC (Variable Infiltration Capacity), is employed to generate a soil moisture database across the region. In addition to a standard index based on temperature, two potential hydrology-based indices for prediction of spring onset dates are defined, based on the simulated soil moisture data as well as on observed precipitation data. Results indicate that the correspondence between the NDVI-derived green-up onset date and the soil-moisture-derived potential onset date exhibits a significantly better correlation as a function of increasing aridity compared to that based on precipitation. In this way the soil-moisture-based index is demonstrated to be superior to the precipitation-based index in terms of capturing grassland spring phenology. The results also showed that both of the hydrological (water-based) indices were superior to the thermal (temperature-based) index in determining the patterns of grass green-up in the Inner Mongolia region, indicating water availability to be the dominant control on average. The understanding about the relative controls on grassland phenology and the effectiveness of alternative indices to capture these controls are important for future studies of vegetation phenology change under climate change. [ABSTRACT FROM AUTHOR]

This study mainly examined the relationships among primary productivity, precipitation and temperature by identifying trends of change embedded in time-series data. The paper also explores spatial variations of the relationship over four types of vegetation and across two precipitation zones in Inner Mongolia, China. Traditional analysis of vegetation response to climate change uses minimum, maximum, average or cumulative measurements; focuses on a whole region instead of fine-scale regional or ecological variations; or adopts generic analysis techniques. We innovatively integrate Empirical Mode Decomposition (EMD) and Redundancy Analysis (RDA) to overcome the weakness of traditional approaches. The EMD filtered trend surfaces reveal clear patterns of Enhanced Vegetation Index (EVI), precipitation, and temperature changes in both time and space. The filtered data decrease noises and cyclic fluctuations in the original data and are more suitable for examining linear relationship than the original data. RDA is further applied to reveal partial effect of precipitation and temperature, and their joint effect on primary productivity. The main findings are as follows: (1) We need to examine relationships between the trends of change of the variables of interest when investigating long-term relationships among them. (2) Long-term trend of change of precipitation or temperature can become a critical factor influencing primary productivity depending on local environments. (3) Synchronization (joint effect) of precipitation and temperature in growing season is critically important to primary productivity in the study area. (4) Partial and joint effects of precipitation and temperature on primary productivity vary over different precipitation zones and different types of vegetation. The method developed in this paper is applicable to ecosystem research in other regions. [ABSTRACT FROM AUTHOR]

Understanding the effects of climate change, in particular, climate extremes on plant functional traits can provide a mechanistic basis for predicting how plant communities may be altered in the future. Here, we focused on a dominant species in Inner-Mongolia typical temperate steppe, Leymus chinensis (Trin.) Tzvei, to examine the responses of plant functional traits to experimentally imposed extreme drought at three sites along an aridity gradient. When comparing the driest (high aridity) to the wettest sites (low aridity), plant height, leaf dry matter content and δ13C (water use efficiency) were increased at the intermediate and low aridity sites, whereas specific leaf area and leaf nitrogen content were reduced at the high-aridity site. When extreme drought (~ 66% reduction in the growing season precipitation) was experimentally imposed at all sites, plant height decreased and δ13C of L. chinensis increased at the intermediate and low aridity sites. The extreme drought of 66% precipitation reduction also increased leaf dry matter content in high- and low-aridity sites. Compared to the control (ambient precipitation), extreme drought increased the strength of the positive association between plant height and δ13C, as well as the negative associations of specific leaf area with plant height and leaf dry matter content. Thus, extreme drought altered key functional traits of the dominant grass of Inner Mongolia steppe, particularly at the low-aridity site where the drought decreased plant size and increased water use efficiency and affected relationships between these traits. [ABSTRACT FROM AUTHOR]

Exploring possible relationships between climate-induced maize yield and rainy-season precipitation under climate change is fundamental to science-based decision for food security in Inner Mongolia Autonomous Region (IMAR). To determine the relationship of maize yield with precipitation variables across IMAR during 1960-2012, we selected 11 precipitation indices of rainy season and divided IMAR into four sub-regions-west, middle, east, and northeast using principal component analysis and K-means clustering methods. Results show that climate-induced maize yield is more sensitive to precipitation variability in the west and middle IMAR. The most important precipitation factor that limits maize yield is moderate precipitation days in these two sub-regions. Moreover, west and middle Inner Mongolia was dominated by decreasing precipitation during the rainy season. Furthermore, the El Niño/La Niña-Southern Oscillation cycle has the significant influence on the rainy-season precipitation in the west and middle IMAR. [ABSTRACT FROM AUTHOR]