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The Tarim Basin is a large inland arid basin in the arid region of northwest China and has been experiencing significant "warming and wetting" since 1987. As a result, the purpose of this paper is to determine whether the climate transition phenomenon occurred in the Tarim Basin as well as the role of atmospheric circulation in this process. We use meteorological data and atmospheric circulation indexes to study the seasonal trends of climate change in this region from 1987 to 2020 to understand how they are affected by atmospheric circulation. The findings show that, from 1987 to 2020, the Tarim Basin experienced significant warming and wetting; with the exception of the winter scale, all other seasonal scales exhibited a clear warming and wetting trend. From the perspective of spatial distribution, most of the areas showed a significant warming trend, and the warming amplitude around the basin is greater than that in the central area of the basin. However, there are significant regional differences in precipitation change rates. Meanwhile, wavelet analysis shows that there is a significant oscillation period of 17–20 years between climate change and the atmospheric circulation index during 1987–2020. The correlation analysis shows that the Pacific decadal oscillation (PDO) and El Niño-Southern Oscillation (ENSO) are the main influencing factors of climate change in the Tarim Basin at different seasonal scales, while the teleconnection of the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) is low and the PDO dominates the summer and autumn temperature changes in the Tarim Basin. The research results of this paper show that, despite the warming and wetting trends since 1987 in the Tarim Basin, the climate type did not change. From 1987 to 2020, the main teleconnection factors of climate change in the Tarim Basin were PDO and ENSO. [ABSTRACT FROM AUTHOR]

In the context of global warming, snow cover changes have an extremely important impact on the hydrological cycle and the redistribution of water resources in arid and semi-arid regions. In this paper, based on the daily cloud-free snow area remote sensing product data in the source region of Yangtze River (SRYR) from 2000 to 2019, the snow phenology variables such as the snow cover day (SCD), snow onset date (SOD), snow end date (SED), and snow duration day (SDD) were extracted separately for each hydrological year, and the vertical distribution of snow cover area (SCA) in the SRYR was analyzed by combining with the digital elevation model (DEM). In addition, we also combined climate factors and land cover types to further explore the spatiotemporal variation characteristics of snow phenology in response to different influencing factors, in order to reveal the spatiotemporal variation patterns of snow cover in the SRYR. The results showed that: (1) The SCA in the SRYR has a more obvious vertical distribution, with the maximum SCA reaching 61.58% at high elevation, while at low elevation, the SCA is mostly below 20%. The distribution of SCD in the study area showed a significant exponential correlation with DEM (R2 = 0.87). (2) The area of SOD in the SRYR showed an advanced trend of about 63.37%, while the area of SED showed a delayed trend of about 69.59%, and the area which showed significant trends is 4.29% and 4.36%, respectively. Therefore, the trends of both SOD and SED showed insignificant changes. (3) Temperature change is the main factor affecting the change of snow cover in the SRYR. Among them, 90.9% of the regions showed a significant positive correlation between temperature and SCD, while precipitation showed a significant negative correlation with SCD in about 75.3% of the total area of SRYR. Under the stable snow area (SCD > 60), the land cover type is glacial or permanent snow about 1.5 × 103 km2, which covers almost the entire glacial or permanent snow of the SRYR. [ABSTRACT FROM AUTHOR]

The effects of global climate change and human activities are anticipated to significantly impact ecosystem services (ESs), particularly in urban agglomerations of arid regions. This paper proposes a framework integrating the dynamic Bayesian network (DBN), system dynamics (SD) model, patch generation land use simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for predicting land use change and optimizing ESs spatial patterns that is built upon the SSP-RCP scenarios from CMIP6. This framework is applied to the oasis urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang (UANSTM), China. The findings indicate that both the SD model and PLUS model can accurately forecast the distribution of future land use. The SD model shows a relative error of less than 2.32%, while the PLUS model demonstrates a Kappa coefficient of 0.89. The land use pattern displays obvious spatial heterogeneity under different climate scenarios. The expansion of cultivated land and construction land is the main form of land use change in UANSTM in the future. The DBN model proficiently simulates the interactive relationships between ESs and diverse factors. The classification error rates for net primary productivity (NPP), habitat quality (HQ), water yield (WY), and soil retention (SR) are 20.04%, 3.47%, 4.45%, and 13.42%, respectively. The prediction and diagnosis of DBN determine the optimal ESs development scenario and the optimal ESs region in the study area. It is found that the majority of ESs in UANSTM are predominantly influenced by natural factors with the exception of HQ. The socio-economic development plays a minor role in such urban agglomerations. This study offers significant insights that can contribute to the fields of ecological protection and land use planning in arid urban agglomerations worldwide. • An integrated framework combining DBN, SD, PLUS and InVEST models was proposed. • Impact of natural and socioeconomic factors on ESs was determined under climate scenarios. • The spatial pattern of ESs was optimized and partitioned using DBNs. • ESs in arid oasis urban agglomerations are mainly affected by natural factors. [ABSTRACT FROM AUTHOR]

Variability in soil moisture has implications for regional terrestrial environments under a warming climate. This paper focuses on the spatiotemporal variability in the intra-annual persistence of soil moisture in China using the fifthgeneration reanalysis dataset by the European Centre for Medium-Range Weather Forecasts for the period 1979-2018. The results show that in China, the mean intra-annual persistence in the humid to arid zones increased from 60 to 115 days in the lower layer but decreased from 19 to 13 days and from 25 to 14 days in the upper and root layers, respectively. However, these changes were strongly attenuated in extremely dry and wet regions due to the scarcity of soil moisture anomalies. Large changes in persistence occurred in the lower soil layer in dryland areas, with a mean difference of up to 40 days between the 2010s and the 1980s. Overall increasing trends dominated the large-scale spatial features, despite regional decreases in the eastern arid zone and the North and Northeast China plains. In the root layer, the two plains experienced an expanded decrease while on the Tibetan Plateau it was dominated by decadal variability. These contrasting changes between the lower and root layers along the periphery of the transition zone was a reflection of the enhanced soil hydrological cycle in the root layer. The enhanced persistence in drylands lower layer is an indication of the intensified impacts of soil moisture anomalies (e.g., droughts) on terrestrial water cycle. These findings may help the understanding of climate change impacts on terrestrial environments. [ABSTRACT FROM AUTHOR]

The systematic bias of the estimated average temperature using daily Tmax and Tmin records relative to the standard average temperature of four time-equidistant observations and its effect on the estimated trend of long-term temperature change have not been well understood. This paper attempts to evaluate the systematic bias across mainland China using the daily data of national observational stations. The results revealed that the positive bias of annual mean temperature was large, reaching 0.58°C nationally on average; regional average bias was lowest in the northwest arid region and highest in the Qinghai–Tibetan Plateau; the bias was low in spring and summer and high in autumn and winter, reaching its lowest point in mid- and late May and highest point in early November. Furthermore, the bias showed a significant upward trend in the past 50 years, with a rising rate of 0.021°C (10 yr)−1, accounting for about 12% of the overall warming as estimated from the data of the observational network; the largest positive trend bias was found in the northwest arid region, while the east monsoon region experienced the smallest change; the most remarkable increase of the bias occurred after early 1990s. These results indicate that the customarily applied method to calculate daily and monthly mean temperature using Tmax and Tmin significantly overestimates the climatological mean and the long-term trend of surface air temperature in mainland China. [ABSTRACT FROM AUTHOR]

In recent years, climate extreme events have caused increasing direct economic and social losses in the arid region of northwestern China. Based on daily temperature and precipitation data from 1960 to 2010, this paper discussed the linear trend and abrupt changes of climate indices. The general evolution was obtained by the empirical orthogonal function (EOF), the Mann-Kendall test, and the distribution-free cumulative sum chart (CUSUM) test. The results are as follows: (1) climate showed a warming trend at annual and seasonal scale, with all temperature indices exhibiting statistically significant changes. The warm indices have increased, with 1.37%days/decade of warm days (TX90p), 0.17 °C/decade of warmest days (TXx) and 1.97 days/decade of warm spell duration indicator (WSDI), respectively. The cold indices have decreased, with − 1.89%days/decade, 0.65 °C/decade and − 0.66 days/decade for cold nights (TN10p), coldest nights (TNn) and cold spell duration indicator (CSDI), respectively. The precipitation indices have also increased significantly, coupled with the changes of magnitude (max 1-day precipitation amount (RX1day)), frequency (rain day (R0.1)), and duration (consecutive dry days (CDD)). (2) Abrupt changes of the annual regional precipitation indices and the minimum temperature indices were observed around 1986, and that of the maximum temperature indices were observed in 1996. (3) The EOF1 indicated the overall coherent distribution for the whole study area, and its principal component (PC1) was also observed, showing a significant linear trend with an abrupt change, which were in accordance with the regional observation results. EOF2 and EOF3 show contrasts between the southern and northern study areas, and between the eastern and western study areas, respectively, whereas no significant tendency was observed for their PCs. Hence, the climate indices have changed significantly, with linear trends and abrupt changes noted for all climate indices, which will have serious impacts on water resources and ecological environment in the arid region of China. [ABSTRACT FROM AUTHOR]

This paper reports a comprehensive study on the observed and projected spatiotemporal changes in mean and extreme climate over the arid region of northwestern China, based on gridded observation data and CMIP5 simulations under the RCP4.5 and RCP8.5 scenarios. The observational results reveal an increase in annual mean temperature since 1961, largely attributable to the increase in minimum temperature. The annual mean precipitation also exhibits a significant increasing tendency. The precipitation amount in the most recent decade was greater than in any preceding decade since 1961. Seasonally, the greatest increase in temperature and precipitation appears in winter and in summer, respectively. Widespread significant changes in temperature-related extremes are consistent with warming, with decreases in cold extremes and increases in warm extremes. The warming of the coldest night is greater than that of the warmest day, and changes in cold and warm nights are more evident than for cold and warm days. Extreme precipitation and wet days exhibit an increasing trend, and the maximum number of consecutive dry days shows a tendency toward shorter duration. Multi-model ensemble mean projections indicate an overall continual increase in temperature and precipitation during the 21st century. Decreases in cold extremes, increases in warm extremes, intensification of extreme precipitation, increases in wet days, and decreases in consecutive dry days, are expected under both emissions scenarios, with larger changes corresponding to stronger radiative forcing. [ABSTRACT FROM AUTHOR]

Warming of the climate system is unequivocal, and the change of climate variables will eventually have a great impact on vegetation cover and agricultural practices, especially in the arid area Xinjiang in China, whose agriculture and ecosystems are heavily vulnerable to climate change. In this paper, normalized difference vegetation index (NDVI) was used to study the vegetation growth and its response to climate change in Xinjiang. Firstly, two NDVI datasets (Global Inventory Modeling and Mapping Studies (GIMMS) and Moderate Resolution Imaging Spectroradiometer (MODIS)) were merged through a pixel-wise regression analysis to obtain a long time series of NDVI data, and then, relationships between yearly NDVI and yearly climate variables, and monthly NDVI and monthly climate variables were extensively investigated for grassland and cropland in northern and southern Xinjiang, respectively. Results show the following: (1) there was an increasing trend in NDVI for both grassland and cropland in both northern and southern Xinjiang over the past decades and trends were significant except that for grassland in northern Xinjiang; (2) precipitation and evaporation were more important than temperature for grassland in northern Xinjiang, while precipitation and temperature were more important than evaporation for grassland in southern Xinjiang and cropland in both northern and southern Xinjiang; (3) NDVI was highly correlated with accumulated monthly precipitation instead of monthly precipitation, and there was a lagged effect of precipitation, temperature, and evaporation on NDVI change. However, lagged effects were only significant in specific months. The results could be helpful to agricultural practices; e.g., based on lagged effect of precipitation, irrigation in July is very important for crop growth. [ABSTRACT FROM AUTHOR]

As an important part of the global ecosystem, wetlands and their dynamics greatly influence regional eco-environment systems. To understand the distributions, change processes and temporal-spatial characteristics of the wetlands of the inland river basin in an arid region (Heihe River Basin, HRB), this paper employed multi-source remote sensing data to facilitate multi-temporal monitoring of the HRB wetland using a wetland information extraction method. First, we performed monitoring of these wetlands for the years 2000, 2007, 2011 and 2014; then, we analyzed the variation characteristics of the spatial-temporal dynamics of the wetlands in the HRB over the last 15 years via the landscape dynamic change model and the transformation matrix. In addition, we studied the possible driving mechanisms of these changes. The research results showed that the total area of the HRB wetlands had decreased by 2959.13 hectares in the last 15 years (Since 2000), and the annual average loss was 1.09%. The dynamics characterizing the HRB wetlands generally presented a trend of slow increase after an initial decrease, which can be classified into three stages. From 2000 to 2007, the total wetland area rapidly decreased; from 2007 to 2011, the area slowly decreased; and from 2011 to 2014, the area gradually increased. The dynamic changing processes characterizing the wetland resources were ascribed to a combination of natural processes and human activities. The main driving mechanisms of wetland dynamic changes include climatic conditions, upper reach water inflows, population, water resources, cultivated area, and policy. The findings of this study can served as reference and support for the conservation and management of wetland resources in the HRB. [ABSTRACT FROM AUTHOR]

The arid region of Northwest China, located in the central Asia, responds sensitively to global climate change. Based on the newest research results, this paper analyzes the impacts of climate change on hydrology and the water cycle in the arid region of Northwest China. The analysis results show that: (1) In the northwest arid region, temperature and precipitation experienced “sharply” increasing in the past 50 years. The precipitation trend changed in 1987, and since then has been in a state of high volatility, during the 21st century, the increasing rate of precipitation was diminished. Temperature experienced a “sharply” increase in 1997; however, this sharp increasing trend has turned to an apparent hiatus since the 21st century. The dramatic rise in winter temperatures in the northwest arid region is an important reason for the rise in the average annual temperature, and substantial increases in extreme winter minimum temperature play an important role in the rising average winter temperature; (2) There was a significant turning point in the change of pan evaporation in the northwest arid area in 1993, i.e., in which a significant decline reversed to a significant upward trend. In the 21st century, the negative effects of global warming and increasing levels of evaporation on the ecology of the northwest arid region have been highlighted; (3) Glacier change has a significant impact on hydrology in the northwest arid area, and glacier inflection points have appeared in some rivers. The melting water supply of the Tarim River Basin possesses a large portion of water supplies (about 50%). In the future, the amount of surface water will probably remain at a high state of fluctuation. [ABSTRACT FROM AUTHOR]

[Display omitted] • Grassland degradation is the main reason for the decline in carbon storage. • The carbon storage of farmland has increased significantly. • The risk of carbon storage reduction in the future is still high. The carbon storage of terrestrial ecosystems is closely related to global climate change. Therefore, assessing the impact of land-use changes on carbon storage is instructive to reduce global carbon emissions. Taking an arid region in northwest China as an example, this paper analyzed the land-use changes in arid region from 1980 to 2015. It used the CA-Markov model to predict the land-use pattern from 2020 to 2050, the carbon storage and sequestration module in Integrated Valuation of Ecosystem Services and Tradeoffs (Invest) mode to assess and predict ecosystem carbon storage over the past 35 years and in the next 30 years and discusses the impact of land-use changes on the carbon storage of terrestrial ecosystems. The results showed that: (1) The high-value areas of carbon storage in arid region were primarily concentrated in grassland, forests and farmland, and the low-value areas of carbon storage were mainly in desert areas. (2) The carbon storage in arid region showed a downward trend. From 1980 to 2015, the carbon reserves of terrestrial ecosystems in arid region decreased by 90.95 Tg, and the net loss of carbon reserves from 2020 to 2050 was 14.72 Tg. Grassland degradation was the main reason for the reduction of carbon storage in arid region. (3) The carbon storage of farmland had increased significantly, but the expansion of farmland dominated by high carbon density grassland, wetland and forest, had reduced the overall carbon storage of the arid region. [ABSTRACT FROM AUTHOR]

Optimization of the urban landscape composition and configuration through initiative planning is important to sustainable development of the drylands of northern China (DNC). Taking the agro-pastoral transitional zone of northern China (APTZNC) as an example, this paper developed an approach of sustainable urban landscape planning (SULP) under the stress of climate change in the DNC. First, we quantify the amount of water resources under the future climate change impacts (CCI). Then, we adjust the urban land area based on water resources carrying capacity constraints. Finally, we use the LUSD-urban (Land Use Scenario Dynamics-urban) model to adjust the configuration of the urban landscape to avoid occupying important natural habitats and corridors, prime croplands, and floodplains. We find that the SULP can effectively mitigate the comprehensive effects of regional urban landscape dynamics on water resources, food security, ecological security, and flood risks. By performing the SULP, prime croplands, floodplains, and important natural habitats and corridors occupied by urban land will decrease by 2,187 km2, 750 km2, and 130 km2, respectively, during the period of 2015–2050 in the APTZNC. We also find that the proposed approach can effectively manage the impacts of climate change on water resource capacity and reduce water stress of the entire APTZNC and its sub-regions. Thus, the proposed SULP approach and the experiences from the case study in the APTZNC are helpful for guiding urban landscape planning to achieve sustainable development of cities in the DNC and even in the drylands around the world. • Sustainable urban landscape planning under the stress of climate change was performed. • Urban land area was adjusted based on water resources carrying capacity constraints. • Urban landscape configuration was adjusted to avoid occupying important areas. • The planning can mitigate the comprehensive effects of urban landscape dynamics. • Addressing the climate change impacts should be incorporated into urban landscape planning. [ABSTRACT FROM AUTHOR]