Search

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

China's Yellow River Basin (YRB) is sensitive to climate change due to its delicate ecosystem and complex geography. Water scarcity, soil erosion, and desertification are major challenges. To mitigate the YRB's ecological difficulties, climate change must be predicted. Based on the analysis of the evolution features of hydro-meteorological elements, the CMIP6 climate model dataset with Delta downscaling and the Empirical Orthogonal Function (EOF) is utilized to quantitatively explore the future variations in precipitation and temperature in the YRB. The following results are drawn: The spatial resolution of the CMIP6 climate model is less than 0.5° × 0.5° (i.e., about 55 km × 55 km), which is improved to 1 km × 1 km by the downscaling of Delta and has outstanding applicability to precipitation and temperature in the YRB. The most accurate models for monthly mean temperature are CESM2-WACCM, NorESM2-LM, and ACCESS-CM2, and for precipitation are ACCESS-ESM1-5, CESM2-WACCM, and IPSL-CM6A-LR. Between 2023 and 2100, annual precipitation increases by 6.89, 5.31, 7.02, and 10.18 mm/10a under the ssp126, ssp245, ssp370, and ssp585 climate scenarios, respectively, with considerable variability in precipitation in the YRB. The annual temperature shows a significant upward trend, and the change rates under the different climate scenarios are, respectively, 0.1 °C/10a, 0.3 °C/10a, 0.5 °C/10a, and 0.7 °C/10a. The increase is positively correlated with emission intensity. Based on the EOF analysis, temperature and precipitation mainly exhibit a consistent regional trend from 2023 to 2100, with the primary modal EOF1 of precipitation for each scenario exhibiting a clear spatial distribution in the southeast–northwest. [ABSTRACT FROM AUTHOR]

Understanding runoff dynamics is vital for effective water management in climate-affected areas. This study focuses on the Dayekou basin in China's Qilian Mountains, known for their high climate variability. Using 25 years of data (1994–2018) on river runoff, precipitation, and temperature, statistical methods were applied to explore the annual variations and climate change impacts on these parameters. Results reveal a significant variability in the river runoff (132.27 to 225.03 mm), precipitation (340.19 to 433.29 mm), and average temperature (1.38 to 2.08 °C) over the period. Decadal rising rates average 17 mm for runoff, 17 mm for precipitation, and 0.25 °C for temperature, with the peak precipitation and runoff occurring in 1998–2000, 2008, and 2016. The annual runoff distribution also exhibited a unimodal pattern, peaking at 39.68 mm in July. The cumulative runoff during low periods constituted only 13.84% of the annual total, concentrated in the second half of the year, particularly during the June-October flood season. The correlation analysis underscored a strong relationship between river runoff and precipitation (correlation coefficient > 0.80), while the temperature correlation was weaker (correlation coefficient < 0.80). This 25-year analysis provides valuable insights into runoff variation, elucidating the interconnected effects of temperature and precipitation in the Dayekou basin, with substantial implications for sustainable development amid climate challenges. [ABSTRACT FROM AUTHOR]

Organic fertilizer is utilized to improve the organic carbon levels in arable soils, which is helpful for soil quality improvement and crop yield increase. However, the after-effect of organic fertilizer varies among regions with different temperature and precipitation conditions, and the extent of the impact remains unknown. This study aimed to investigate the impact of varying temperature and rainfall conditions on the accumulation of soil organic carbon after organic fertilizer application. A meta-analysis of 168 peer-reviewed studies published between 2005 and 2022 involving a total of 464 trials was conducted. The following was discovered: (1) In the major grain-producing areas of China, there was a significant positive correlation (p < 0.01) between latitude and soil organic carbon content. Meanwhile, temperature and precipitation had a significant negative correlation (p < 0.01) with soil organic carbon content. (2) The increase in temperature inhibited the increase in soil organic carbon storage. The improvement effect of organic fertilizer application in the low-temperature areas was significantly increased by 60.93% compared with the mid-temperature areas, and by 69.85% compared with the high-temperature areas. The average annual precipitation affected the after-effect of organic fertilizer as follows: 400–800 mm > 400 mm > more than 800 mm. (3) The influence of climatic conditions on the after-effect of organic fertilizer was more significant depending on the specific tillage practice. To increase organic fertilizer use efficiency and eliminate greenhouse gas emissions, liquid organic fertilizers with abundant trace nutrients and amino acids, which take advantage of releasing nutrients more swiftly and have a better fertilization effect, could be an alternative to traditional organic fertilizers. [ABSTRACT FROM AUTHOR]

Oscillations in global modes of variability (MoVs) form global teleconnections that affect regional climate variability and modify the potential for severe and damaging weather conditions. Understanding the link between certain MoVs and regional climate can improve the ability to more accurately predict environmental conditions that impact human life and health. In this study, we explore the connection between different MoVs, including the Arctic oscillation (AO), Eurasian teleconnection, Indian Ocean dipole (IOD), North Atlantic oscillation (NAO), and El Niño southern oscillation (Nino34), with winter and summer climates in the High Mountain Asia (HMA) region, including geopotential height at 250 hPa (z250), 2 m air temperature (T2M), total precipitation (PRECTOT), and fractional snow cover area (fSCA). Relationships are explored for the same monthly period between the MoVs and the climate variables, and a lagged correlation analysis is used to investigate whether any relationship exists at different time lags. We find that T2M has a negative correlation with the Eurasian teleconnection in the Inner Tibetan Plateau and central China in both winter and summer and a positive correlation in western China in summer. PRECTOT has a positive correlation with all MoVs in most regions in winter, especially with the IOD, and a negative correlation in summer, especially with the Eurasian teleconnection. Snow cover in winter is positively correlated with most indices throughout many regions in HMA, likely due to wintertime precipitation also being positively correlated with most indices. Generally, the AO and NAO show similar correlation patterns with all climate variables, especially in the winter, possibly due to their oscillations being so similar. Furthermore, the AO and NAO are shown to be less significant in explaining the variation in HMA climate compared to other MoVs such as the Eurasian teleconnection. Overall, our results identify different time windows and specific regions within HMA that exhibit high correlations between climate and MoVs, which might offer additional predictability of the MoVs as well as of climate and weather patterns in HMA and throughout the globe. [ABSTRACT FROM AUTHOR]

Middle and eastern routes of the South-North Water Diversion Project (SNWDP) of China, which are approximately located within the area 28°-42°N and 110°-122°E, are being constructed. This paper investigates the past climatic variations on various time scales using instrumental and proxy data. It is found that annual mean surface air temperature has increased significantly during the past 50-100 years, and winter and spring temperatures in the northern part of the region have undergone the most significant changes. A much more significant increase occurs for annual mean minimum temperature and extreme low temperature than for annual mean maximum temperature and extreme high temperature. No significant trend in annual precipitation is found for the region as a whole for the last 50 and 100 years, although obvious decadal and spatial variation is detectable. A seesaw pattern of annual and summer precipitation variability between the north and the south of the region is evident. Over the last 100 years, the Haihe River basin has witnessed a significant negative trend of annual precipitation, but no similar trend is detected for the Yangtze and Huaihe River basins. Pan evaporation has significantly decreased since the mid-1960s in the region in spite of the fact that the trend appears to have ended in the early 1990s. The negative trend of pan evaporation is very significant in the plain area between the Yangtze and Yellow Rivers. There was a notable series of dry intervals lasting decades in the north of the region. The northern drought of the past 30 years is not the most severe in view of the past 500 years; however, the southern drought during the period from the 1960s to the 1980s may have been unprecedented. The dryness-wetness index (DWI) shows significant oscillations with periodicities of 9.5 and 20 years in the south and 10.5 and 25 years in the north. Longer periodicities in the DWI series include 160-170- and 70-80-yr oscillations in the north, and 100-150-yr oscillations in the south. The observed climate change could have implications for the construction and management of the SNWDP. The official approval and start of the hydro project was catalyzed by the severe multiyear drought of 1997-2003 in the north, and the operation and management of the project in the future will also be influenced by climate change-in particular by precipitation variability. This paper provides a preliminary discussion of the potential implications of observed climate change for the SNWDP. [ABSTRACT FROM AUTHOR]

The allocation of plant biomass above and below ground reflects their strategic resource utilization, crucial for understanding terrestrial carbon flux dynamics. In our comprehensive study, we analyzed biomass distribution patterns in 580 broadleaved and 345 coniferous forests across China from 2005 to 2020, aiming to discern spatial patterns and key drivers of belowground biomass proportion (BGBP) in these ecosystems. Our research revealed a consistent trend: BGBP decreases from northwest to southeast in both forest types. Importantly, coniferous forests exhibited significantly higher BGBP compared to broadleaved forests (p < 0.001). While precipitation and soil nutrients primarily influenced biomass allocation in broadleaved forests, temperature and soil composition played a pivotal role in coniferous forests. Surprisingly, leaf traits had a negligible impact on BGBP (p > 0.05). Climatic factors, such as temperature and rainfall, influenced biomass partitioning in both strata by altering soil nutrients, particularly soil pH. These findings provide valuable insights into understanding carbon sequestration dynamics in forest ecosystems and improving predictions of the future trajectory of this critical carbon cycle component. [ABSTRACT FROM AUTHOR]

Vegetation around the Daihai Lake, northern China, is very sensitive to climate changes. In this paper, pollen-based quantitative climate reconstructions using three methods [weighted averaging partial least squares method (WAPLS), modern analog technique (MAT), and pollen response surface method (PRS)] were conducted to obtain robust reconstructions of Holocene climate changes in the Daihai Lake area. The result obtained by the three methods all consistently show the annual precipitation to have been 50–100 mm lower in the early Holocene, 100–200 mm higher in the Mid-Holocene, and 50–100 mm lower again in the late Holocene than at present. The WAPLS and the MAT methods also show quasi-synchronous oscillations of the mean annual temperature (Ta); 1°–2°C lower in the Early Holocene and 1°–3°C higher in the Mid-Holocene than today. The time period from 6200 to 5100 cal yr BP was the wettest and the warmest interval, with an annual precipitation (Pa) greater than 550 mm and mean annual temperature Ta higher than 6.5°C. Several cold and dry events can be identified to occur about 8200, 6000, and 4400 cal yr BP, with an annual precipitation less than 400 mm and a mean annual temperature colder than 4.5°C, respectively. The mean temperature of the warmest month (Tw) as reconstructed using both WAPLS and MAT methods was relatively stable during the Holocene, fluctuating about ±2°C relative to the present level, but the PRS method suggests more varied Tw values in both amplitude and frequency. After 1500 cal yr BP, no consistent pattern can be observed from these three different analyses, probably because of the impact of intensified human disturbances on the natural vegetation. The fluctuations of annual precipitation (Pa) correspond to that observed in Dongge Cave in southern China. The differences might be linked to Indian monsoon and East Asia monsoon climates or caused by the different degree of dating precision, different temporal resolution, and different sensitive response of climate proxies to the climate variations. [ABSTRACT FROM AUTHOR]

This paper presents a large data set on carbon isotope composition (δ13C) of modern soils which were collected under the main vegetation communities along an altitude of 1250–5500 m above sea level in the Qinghai-Tibetan Plateau. The δ13C values of 198 samples range from -28.6 to -15.1‰ versus PDB and exhibit a clean relation to different vegetation communities from forest (-25.9 ± 1.2‰) to shrub (-24.7 ± 1.4‰), steppe (-23.1 ± 1.3‰), alpine meadow (-23.6 ± 0.7‰), alpine desert steppe (-21.3 ± 1.6‰), and alpine desert (-18.9 ± 2.5‰). We attributed the observed variability in δ13C values to that the mean annual precipitation (MAP) and the mean annual temperature (MAT) are the main factors controlling the distribution of vegetation types in the Tibetan Plateau, which causes the change in carbon isotope composition of modern soils at any given altitude. The result of both linear and nonlinear regression analyses also confirms that MAP and MAT are the major factors affecting the δ13C values of surface soils. In the absence of favorable moisture and temperature conditions, low pCO2 alone is not sufficient to cause the distinct changes in carbon isotope composition of modern soils in the Tibetan Plateau. This study provides some fundamental information on the carbon isotope composition of terrestrial carbon pools and bears some practical significance for the use of carbon isotope data to document vegetation changes and environmental conditions of the high plateau in the past. [ABSTRACT FROM AUTHOR]

Based on monthly precipitation (P), temperature (T) data, and remote sensing images collected from March 2000 to February 2019, this article was constructed to reveal the synergistic effect between P and T for the NDVI in northern China qualitatively and quantitatively by using a one-variable linear regression, the coefficient of variation, multivariate correlation coefficients, and a geodetector. The results show that the NDVI in the study area decreased from 2000 to 2012, increased from 2013 to 2018, decreased in the west, and increased in the east of Northern China. Overall, the NDVI, P, and the average maximum temperature (Tmax) had the strongest multivariate correlations (approximately 43.4% of the total study area passed the 95% confidence level significance test), followed by the average temperature (Tave) and average minimum temperature (Tmin). The explanatory power of the synergistic effect between P and Tmax for the NDVI was the strongest, with the value of explanatory power varying from 0.41 to 0.81, followed by Tave and Tmin. Spatially, the explanatory power of the synergistic effect between P and T for the NDVI was strengthened overall in the study area from northwest to southeast. The annual change rate of the explanatory power showed that the overall explanatory power between P and T for the NDVI in the study area was weakened in the central area and strengthened in the east and the west. Specifically, the synergistic effect between P and T on the NDVI was weakened in both Shaanxi and Ningxia Huizu Zizhiqu, while the opposite occurred in Xinjiang Uygul Zizhiqu, Qinghai, and another five provinces in the eastern part of the study area. [ABSTRACT FROM AUTHOR]

Due to the rapid development of China's economy, the demand for wood is steadily increasing. Eucalyptus species have been introduced in large quantities because of their fast growth, strong adaptability, and wide utility. To understand the phenological changes in introduced Eucalyptus in its new range, we carried out a field investigation to examine leaf functional and chemical defense traits of three introduced species (E. saligna, E. grandis and E. robusta) over latitudinal and altitudinal gradients in southern China. We sampled multiple stands of each species, and measured the leaf physical characteristics (e.g., leaf width, leaf thickness, and specific leaf area [SLA]), leaf nitrogen (N) and phosphorus (P) content, and phenolic compounds. We found that many functional traits (e.g., leaf size and thickness) decreased at lower latitudes, especially in E. grandis, possibly to reduce heat and water loss under higher temperatures. In E. grandis, we found that leaf P was lower at higher latitudes and altitude, and phenolics increased with elevation, while in E. robusta, both leaf N and P decreased with altitude. These findings suggested that both species were more conservative in resource allocation, with E. grandis possessing enhanced chemical defenses in response to the conditions experienced at higher elevations. In addition, we found the tree populations at the northern range limit of E. robusta had lower SLA, suggesting a more conservative growth strategy, In contrast, small populations in the northern part of the ranges of E. grandis had higher SLA, indicating range expansion at the edge of the species' geographic distribution. Overall, it is particularly important to consider intraspecific trait differences across wide geographic areas when studying the spread of invasive species in the new range. [ABSTRACT FROM AUTHOR]

Given the differences in geomorphology, climate, hydrology, and human activities in various regions, lake chemometrics may also vary. However, the spatial distribution of lake chemistry and the factors affecting such pattern are still unclear. Here, we collected data for carbon, nitrogen, and phosphorus from published literature and databases in 224 lakes and calculated the trophic status index to represent the nutrient classification state of lakes. We found that lakes with high carbon concentrations were located in the Tibet-Qinghai Limnetic Region of western China, whereas lakes with high nitrogen and phosphorus concentrations were located in the Inner Mongolia-Xinjiang Limnetic Region and Northeast Limnetic Region of northern China. Areas with larger cropland and urban residential land (such as the junction of the three lake regions, i.e., the Northeast Limnetic Region, East Limnetic Region, and Inner Mongolia-Xinjiang Limnetic Region) tended to have lakes with high nitrogen and phosphorus concentrations. Our analysis suggested that spatial distribution of carbon, nitrogen, and phosphorus concentrations reflect the effect of climate, geomorphology, and land use in each lake region and nationwide. [ABSTRACT FROM AUTHOR]

Climate change is a global scientific problem, and its impact on the spatiotemporal variations of precipitation has been a crucial research topic. Although previous studies have used different methods to evaluate the precipitation characteristics of the Huaihe River Basin, the time series were short and the few stations could not fully and accurately represent the precipitation characteristics. In this study, daily temperature and precipitation data were collected from 233 meteorological stations in the Huaihe River Basin from 1960–2020. The Mann–Kendall test was used to analyze the trend and significance of interannual and interseasonal scale changes in temperature and precipitation in the Basin, respectively. The correlation between temperature and precipitation was analyzed using the Pearson correlation coefficient method. The spatial distribution of the significance of temperature and precipitation changes and the spatial distribution of the correlation between temperature and precipitation in the basin were plotted. The temperature in the basin tended to increase on interannual and interseasonal scales, with more noticeable changes in spring and winter. Precipitation showed an overall decreasing trend but an increasing trend in localized areas in the south. A decreasing trend in the interseasonal variation scale was observed in spring, an increasing trend in winter, a decreasing trend in the northeastern region in summer, an increasing trend in the southwestern region, and an increasing trend in the northern and southern parts in autumn were observed. The correlation between average temperature and precipitation on interannual and interseasonal scales was analyzed using Pearson's correlation coefficient method, and the annual average temperature and annual average precipitation in the Huaihe River basin were found to be negatively correlated, except for sporadic areas that showed extremely weakly positive correlations or no correlations. [ABSTRACT FROM AUTHOR]

Aim: Amphibians require both terrestrial and aquatic environments to complete their life cycles. Thus, they are subject to complex selection pressures stemming from different environments, and these selection pressures are likely to vary geographically with variation in temperature and precipitation. Studies of genetic differentiation along geographical clines allow identification of footprints of these selection pressures. Location: China. Methods: To identify possible signatures of local adaptation to particular environmental conditions, we conducted a genome‐scan with 20,572 single‐nucleotide polymorphisms (SNPs) obtained with restriction site‐associated DNA sequencing of pooled samples from 10 Microhyla fissipes populations spanning a 1,398 km long latitudinal gradient in China. Results: The results revealed significant genetic differentiation among populations (FST =0.090). Numerous outlier SNPs associated with variation in both annual average temperature (n = 69) and precipitation (n = 248) were detected. Main conclusions: The degree and pattern of population differentiation in the SNPs supported the hypothesis that these SNPs have been subject to directional natural selection associated with temperature and precipitation and, hence, are reflective of geographically varying local adaptation. Hence, conservation and management plans for Microhyla fissipes should take into account this heterogeneity in genetic constitution in its populations. [ABSTRACT FROM AUTHOR]

The overall goal of this study was to examine the impacts of climate change on the mean and variance of rice yields in China by using historical climate and crop data. An econometric model was established to estimate Just–Pope stochastic production functions and identify the potential impacts of climate change on the mean and variance of rice yields by type, keeping other factors constant. Based on the estimated production functions, the contribution rate of climatic factors to rice yield was then assessed by conducting the growth accounting of yields over the past 30 years. The results showed that both the mean rice yield and the yield variability were influenced by changes in the mean climate conditions and climatic variance. In the future, the impacts of climate change on rice yields will depend on local regions' present climatic conditions. The results have implications for improving the adaptation capacity of rice production. [ABSTRACT FROM AUTHOR]

1. It is increasingly being recognized that tree species diversity has positive effects on forest ecosystem carbon (C) stock. However, at broad spatial scales, this relationship may depend on climate conditions and species mycorrhizal associations. 2. Here, observations from 667 forest plots in subtropical China were used to investigate the effects of species diversity, mean annual precipitation (MAP), mean annual temperature (MAT) and mycorrhizal type (arbuscular or ectomycorrhizal) on the forest C stock and its components (tree C stock, shrub layer C stock, herb layer C stock, litter layer C stock, root C stock and soil C stock). 3. We found positive effect of tree species diversity on total forest C stock. MAP had positive effects on total forest C stock and its components, while MAT had consistently negative effects on total forest C stock and most of its components. Different levels of MAP and MAT did modulate the strength of effect of species diversity on forest C stock and its components. In addition, species diversity, MAT and MAP showed a significant positive relationship with arbuscular mycorrhiza-associated tree C stock but had no or negative relationship with ectomycorrhiza-associated tree C stock. 4. Synthesis. Our results indicate that maintaining high level of species diversity may support the buffering of negative effects resulting from climate warming. Furthermore, under climate warming the specific C stock of AM trees can increase, which can potentially promote forest C stock. Taken together, our study suggests that afforestation policies should consider not only tree species diversity to increase forest C stock but also the effects of different tree mycorrhizal types. [ABSTRACT FROM AUTHOR]

Climate change alters hydrological processes in cold regions. However, the mechanisms of runoff component variation remain obscure. We implemented a WEP-N model to estimate monthly runoff in the Songhua River Basin (SRB) between 1956 and 2018. All flow simulations were accurate (NSE > 0.75 and RE < 5%). The annual runoff was attenuated in 1998, and the hydrological series (1956–2018) was divided into base and change periods in that year. Relative to the BS (base scenario), annual production flow reduction was −28.2% under climate change and water use. A multifactor attribution analysis showed that climate change and water use contributed 77.0% and 23.0% to annual runoff reduction, respectively. Decreases in annual surface and base flow explained 62.1% and 35.7% of annual production flow reduction, respectively. The base flow increased by 8.5% and 6.5% during the freezing and thawing periods, respectively. Relative to the BS, groundwater recharge increased by 9.2% and 4.1% during the freezing and thawing periods, respectively, under climate change conditions. Climate change was the dominant factor attenuating production flow. The change in production flow occurred mainly during the non-freeze-thaw period. The decrease in total production flow in the SRB was caused mainly by the decrease in the surface flow, where the reduction in base flow accounted for a relatively small proportion. Production flow attenuation aggravated water shortages. The utilization rate of groundwater resources is far below the internationally recognized alarm line. Therefore, attention should be directed towards certain areas of the SRB and other regions with minimal groundwater exploitation. [ABSTRACT FROM AUTHOR]

Drought is one of the major environmental stressors; drought is increasingly threatening the living environment of mankind. The standardized precipitation evapotranspiration index (SPEI) with a 12-month timescale was adopted to monitor dry–wet status over China from 1951 to 2021. The modified Mann–Kendall (MMK) and Pettitt tests were used to assess the temporal trend and nonlinear behavior of annual drought variability. The analysis focuses on the spatio-temporal structure of the dry–wet transition and its general connections with climate change processes. In addition, the seasonal autoregressive integrated moving average (SARIMA) model was applied to forecast the dry–wet behavior in the next year (2022) at 160 stations, and the hotspot areas for extreme dryness–wetness in China were identified in the near term. The results indicate that the dry–wet climate in China overall exhibits interannual variability characterized by intensified drought. The climate in the Northeast China (NEC), North China (NC), Northwest China (NWC), and Southwest China (SWC) has experienced a significant (p < 0.05) drying trend; however, the dry–wet changes in the East China (EC) and South Central China (SCC) are highly spatially heterogeneous. The significant uptrend in precipitation is mainly concentrated to the west of 100° E; the rising magnitude of precipitation is higher in Eastern China near 30° N, with a changing rate of 20–40 mm/decade. Each of the sub-regions has experienced significant (p < 0.01) warming over the past 71 years. Geographically, the increase in temperature north of 30° N is noticeably higher than that south of 30° N, with trend magnitudes of 0.30–0.50 °C/decade and 0.15–0.30 °C/decade, respectively. The response of the northern part of Eastern China to the warming trend had already emerged as early as the 1980s; these responses were earlier and more intense than those south of 40° N latitude (1990s). The drying trends are statistically significant in the northern and southern regions, bounded by 30° N, with trend magnitudes of −0.30–−0.20/decade and −0.20–−0.10/decade, respectively. The northern and southwestern parts of China have experienced a significant (p < 0.05) increase in the drought level since the 1950s, which is closely related to significant warming in recent decades. This study reveals the consistency of the spatial distribution of variations in precipitation and the SPEI along 30° N latitude. A weak uptrend in the SPEI, i.e., an increase in wetness, is shown in Eastern China surrounding 30° N, with a changing rate of 0.003–0.10/decade; this is closely associated with increasing precipitation in the area. Drought forecasting indicates that recent drying areas are located in NWC, the western part of NC, the western part of SWC, and the southern part of SCC. The climate is expected to show wetting characteristics in NEC, the southeastern part of NC, and the eastern part of EC. The dry–wet conditions spanning the area between 30–40° N and 100–110° E exhibit a greater spatial variability. The region between 20–50° N and 80–105° E will continue to face intense challenges from drought in the near future. This study provides compelling evidence for the temporal variability of meteorological drought in different sub-regions of China. The findings may contribute to understanding the spatio-temporal effect of historical climate change on dry–wet variation in the region since the 1950s, particularly in the context of global warming. [ABSTRACT FROM AUTHOR]

Historical records truthfully document human life and environment associated with climate changes. We quantify official historical records of China dating back last 2000 years to examine the disasters due to anomalous temperatures of cold or hot, irregular precipitations of wet or dry, and floods in inland/coastal or Northern/Southern areas in four seasons that possibly linked to solar activities during 1-1825 CE (Common Era). It is found that the proportion of disaster years is positively associated with the time periods, and therefore, both the cases with high and low solar activity (HSA and LSA) leading are under study. Statistical results show that extreme cold weather occurs particularly in the Winter and Spring during LSA periods. Irregularities precipitations, including heavy rain/hail/snow and severe drought are significantly frequent during LSA periods, while floods on inland and coastal river basins tend to occur more frequently in LSA and HSA periods, respectively. The disasters owing to irregularities precipitations and floods frequently happen in Summer and Autumn, which suggests that the irregular precipitations could cause the floods. All the disasters occur significantly in the Northern China, which suggests the climate boundary of the Qinling–Huaihe Line along at about 33°N being essential. In total, all the disasters due to the anomalously cold temperatures, irregular precipitations, and floods tend to occur during the LSA periods. [ABSTRACT FROM AUTHOR]

This paper explored the projected changes in precipitation, maximum temperature (T max), and minimum temperature (T min) over the Yangtze River Basin (YRB) based on 23 Global climate models (GCMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6). The Empirical Quantile Mapping (EQM) approach was firstly applied to correct the biases in the GCMs. Next, the future changes were investigated by analyzing the multi-model ensemble (MME) of the bias-corrected dataset during 2025–2044 (near-term), 2045–2064 (mid-term), and 2081–2100 (long-term) periods, with reference to the baseline period 1995–2014, under three integrated scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) of the Shared Socioeconomic Pathways (SSPs) and the Representative Concentration Pathways (RCPs). Results show that: (1) the biases in CMIP6 GCMs can be effectively corrected by EQM, and the MME performs better than individual models for each climatic variable. (2) Precipitation over the YRB from 2025 to 2100 is projected to increase at the rate of 9.66 mm/decade, 13.45 mm/decade, and 21.01 mm/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, the annual precipitation is projected to increase by 10.41%, 10.66% and 15.80%, under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (3) T max (T min) over the YRB is projected to increase by 0.09 (0.07) °C/decade, 0.29 (0.27) °C/decade, and 0.66 (0.64) °C/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, T max (T min) averaged over the YRB is projected to increase by 1.75 (1.50) °C, 2.72 (2.54) °C and 5.04 (4.85) °C under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (4) Uncertainties in the projected precipitation and temperature over the YRB were reduced based on MME. But further researches, such as selecting the superior models with respect to the regional climate of the YRB from the CMIP6 and using the ensemble methods that assign weight based on the performance of each model, are still needed to provide more reliable climate projections. • Projected changes were explored by 23 CMIP6 GCMs under the three SSP-RCP scenarios. • Biases in the GCMs were corrected by Empirical Quantile Mapping (EQM) method. • Multi-model ensemble (MME) was used to reduce the uncertainties. [ABSTRACT FROM AUTHOR]

Abstract: The distribution of schistosomiasis has obvious regional characteristics. As the only intermediate host of schistosomiasis, Oncomelania''s breeding and distribution influence the prevalence and transmission of schistosomiasis directly. The cercaria of Schistosoma has a significant seasonal variation in Poyang Lake. This paper selects molluscicidal Oncomelania statistics, temperature, and precipitation of eight epidemics of schistosomiases in Poyang Lake. It constructs schistosomiasis transmission index prediction model of Poyang Lake to predict the propagation of Schistosomiasis. It analyzes the spatial variation of Oncomelania islet making use of Theil coefficient. Then, it analyzes the epidemic of Schistosomiasis spatial and temporal distribution features making use of GIS, Excel and SPSS in Poyang Lake based on climate changes. The results have shown that, the rapid increase of population in epidemic is not only related to the change of temperature and precipitation in each county, but also related to temperature positively and precipitation inversely in Poyang Lake. The transmission of Schistosomiasis is not only of great differences in time but also in scale with large district and spatial variation in Poyang Lake Region. Appropriate habitat of Oncomelania and schistosoma has been moving northward, which maybe result in the transmission of schistosomiasis moving northward. Further impacts on the epidemic situation of schistosomiasis spread in Poyang Lake Region. [Copyright &y& Elsevier]

Abstract: This paper introduces a new model for regional climate simulation-Star model, and explains the scheme, the usage and the application of the Star model. Taking the “Temperature of 2m” and “Precipitation” as the characteristic variables of climate, the model is calculated and tested by taking Huailai climate station of China as practical example. [Copyright &y& Elsevier]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A Met Office Hadley Centre regional climate model, HadRM3P, is used to dynamically downscale the NOAA Twentieth Century Reanalysis, version 2c (20CRv2c), to generate a fine-resolution reconstruction of China's climate from 1851 to 2010. The downscaled dataset has a small warm and seasonal wet bias (1.4°C; 0.9 mm day−1) relative to recent observations but otherwise represents spatial and temporal trends realistically. Analysis focused on temperature and precipitation shows that downscaling 20CRv2c is found to improve its representation of China's climatological annual cycle, particularly over areas with sparse observational coverage such as the Tibetan Plateau. The downscaled dataset better represents the interannual variability and trends in observed temperature since 1901 and suggests that China has experienced a significant and sustained increase in temperature of 0.05°C (10 yr)−1 since the 1850s. Chinese precipitation trends have not changed significantly in the recent past or over the past 160 years. This analysis serves as an initial yet imperative step toward improving in-depth understanding of the characteristics and multidecadal drivers of high-impact events over China such as heat waves, droughts, and extreme precipitation. [ABSTRACT FROM AUTHOR]

Qinling Mountains is the north–south boundary of China's geography; the vegetation changes are of great significance to the survival of wildlife and the protection of species habitats. Based on Landsat products in the Google Earth Engine (GEE) platform, Pearson's correlation coefficient method, and classification and regression models, this study analyzed the changes in NDVI (Normalized Difference Vegetation Index) in the Qinling Mountains in the past 38 years and the sensitivity of its driving factors. Finally, residual analysis method and accumulate slope change rate are used to identify the impact of human activities and climate change on NDVI. The research results show the following: (1) The NDVI value in most areas of Qinling Mountains is at a medium-to-high level, and 99.76% of the areas correspond to an increasing trend of NDVI, and the significantly increased area accounts for more than 20%. (2) From 1981 to 2019, the NDVI of the Qinling Mountains increased from 0.63 to 0.78, showing an overall upward trend, and it increased significantly after 2006. (3) Sensitivity analysis results show that the western high-altitude area of Qinling Mountain area dominated by grassland is mainly affected by precipitation. The central and southeastern parts of the Qinling Mountains are significantly affected by temperature, and they are mainly distributed in areas dominated by forest. (4) The contribution rates of climate change and human activities to NDVI are 36.04% and 63.96%, respectively. Among them, the positive impact of human activities on the NDVI of the Qinling Mountains accounted for 99.85% of the area. The area with significant positive effect accounted for 36.49%. The significant negative effect area accounts for only 0.006%, mainly distributed in urban areas and coal mining areas. [ABSTRACT FROM AUTHOR]

An overview of basic research on climate change in recent years in China is presented. In the past 100 years in China, average annual mean surface air temperature (SAT) has increased at a rate ranging from 0.03°C (10 yr) to 0.12°C (10 yr). This warming is more evident in northern China and is more significant in winter and spring. In the past 50 years in China, at least 27% of the average annual warming has been caused by urbanization. Overall, no significant trends have been detected in annual and/or summer precipitation in China on a whole for the past 100 years or 50 years. Both increases and decreases in frequencies of major extreme climate events have been observed for the past 50 years. The frequencies of extreme temperature events have generally displayed a consistent pattern of change across the country, while the frequencies of extreme precipitation events have shown only regionally and seasonally significant trends. The frequency of tropical cyclone landfall decreased slightly, but the frequency of sand/dust storms decreased significantly. Proxy records indicate that the annual mean SAT in the past a few decades is the highest in the past 400-500 years in China, but it may not have exceeded the highest level of the Medieval Warm Period (1000-1300 AD). Proxy records also indicate that droughts and floods in eastern China have been characterized by continuously abnormal rainfall periods, with the frequencies of extreme droughts and floods in the 20th century most likely being near the average levels of the past 2000 years. The attribution studies suggest that increasing greenhouse gas (GHG) concentrations in the atmosphere are likely to be a main factor for the observed surface warming nationwide. The Yangtze River and Huaihe River basins underwent a cooling trend in summer over the past 50 years, which might have been caused by increased aerosol concentrations and cloud cover. However, natural climate variability might have been a main driver for the mean and extreme precipitation variations observed over the past century. Climate models generally perform well in simulating the variations of annual mean SAT in China. They have also been used to project future changes in SAT under varied GHG emission scenarios. Large uncertainties have remained in these model-based projections, however, especially for the projected trends of regional precipitation and extreme climate events. [ABSTRACT FROM AUTHOR]

To understand agro-climatic suitability for spring soybean growth in north China, an integrated crop-response-function method was developed. This method includes crop-response functions for temperature, precipitation, and sunshine and is assessed by a weighting method based on the coefficient of determination. The results show that the most suitable area (S1) for spring soybean growth occupied approximately 21.35%% of the total area of north China. Among three types of spring soybeans of early maturity, middle maturity, and late maturity, middle maturity was the most suitable variety to grow in the study area, covering nearly 1.133 ×× 106 km2 or about 99.75%% of the total area of S1. As a result of this study, the authors suggest that breeders pay more attention to middle-maturity cultivars in north China. The findings from this study may provide useful information for policy makers issuing guidelines for agricultural production. [ABSTRACT FROM AUTHOR]

The time-frequency characteristics of the variations of temperature and precipitation over the city of Changchun in northeast China and their associations with large-scale atmospheric and oceanic conditions are analyzed. It is found that the variations of the regional climate are characterized by strong semiannual signals. For precipitation, the amplitude of semiannual signal is about half of that of the annual cycle. The relationships of the Changchun temperature and precipitation with local winds and large-scale patterns of atmospheric circulation and sea surface temperature are also strongest on annual and semiannual time scales. These strong semiannual signals are potentially helpful for improving the prediction of the regional climate. On the annual time scale, the northeast China climate is affected by both the thermal contrast between the Asian continent and the tropical Indo-Pacific Oceans and that between the continent and the extratropical North Pacific. These effects are manifested by the cyclonic (anticyclonic) pattern over the Asian continent (North Pacific) and the strong southerly flow over East Asia and northwestern Pacific associated with increases in temperature and precipitation. On the semiannual time scale, the northeast China climate is mainly related to the large-scale circulation pattern centered over the North Pacific, with its western portion over northeast China, North and South Korea, and Japan. While temperature signals are related to extratropical atmospheric process more apparently, both extratropical and tropical influences are seen in the semiannual variation of precipitation. There exist strong relationships between Changchun temperature and precipitation and the North Pacific Oscillation (NPO) in the frequency band up to 7 months. Temperature increases and precipitation decreases when NPO is positive. The relationships were weak before 1980 but became stronger afterward, associated with the strengthening of the East Asian trough. [ABSTRACT FROM AUTHOR]

Data on field biomass measurements in temperate grasslands of northern China (141 samples from 74 sites) were obtained from 23 Chinese journals, reports and books. Net primary productivity (NPP) of grasslands was estimated using three algorithms (peak live biomass, peak standing crop and maximum minus minimum live biomass), respectively, based on availability of biomass data in sites. 135 samples which have aboveground biomass (AGB) measurements, have peak AGB ranges from 20 to 2021 g m–2 (mean = 325.3) and the aboveground NPP (ANPP) ranges from 15 to 1647.1 g m–2 per year (mean = 295.7). 72 samples which have belowground biomass (BGB) measurements, have peak BGB ranges from 226.5 to 12827.5 g m–2 (mean = 3116) and the belowground NPP (BNPP) ranges from 15.8 to 12827.5 g m–2 per year (mean = 2425.6). In total 66 samples have the total NPP (TNPP), ranging from 55.3 to 13347.8 g m–2 per year (mean = 2980.3). Mean peak biomass and NPP varied from different geographical sampling locations, but they had a general rough regularity in ten grasslands. Meadow, mountain and alpine grasslands had high biomass and NPP (sometimes including saline grassland). Forested steppe, saline grassland and desert had median values. Meadowed and typical steppes had low biomass and NPP (sometimes including desert). The lowest biomass and NPP occurred in deserted steppe and stepped desert. Grassland ANPP has significant positive relationships with annual and summer precipitation as well as summer temperature (all p<0.01). However, grassland BNPP and TNPP have more significant negative relationships with summer temperature (p<0.01) than with annual temperature (p<0.05). The analysis of climate – productivity correlations implied that aboveground productivity is more controlled by rainfall, whereas belowground and total productivity is more influenced by temperature in the temperate grasslands of northern China. The present study might underestimate grassland NPP in northern China due to limitation of biomass measurements. Data on relative long-term aboveground and belowground biomass dynamics, as well as data of standing dead matter, litterfall, decomposition and turnover, are required if grassland NPP is to be more accurately estimated and the role of temperate grasslands in the regional to global carbon cycles is to be fully appreciated. [ABSTRACT FROM AUTHOR]

Vegetation fluctuation is sensitive to climate change, and this response exhibits a time lag. Traditionally, scholars estimated this lag effect by considering the immediate prior lag (e.g., where vegetation in the current month is impacted by the climate in a certain prior month) or the lag accumulation (e.g., where vegetation in the current month is impacted by the last several months). The essence of these two methods is that vegetation growth is impacted by climate conditions in the prior period or several consecutive previous periods, which fails to consider the different impacts coming from each of those prior periods. Therefore, this study proposed a new approach, the weighted time-lag method, in detecting the lag effect of climate conditions coming from different prior periods. Essentially, the new method is a generalized extension of the lag-accumulation method. However, the new method detects how many prior periods need to be considered and, most importantly, the differentiated climate impact on vegetation growth in each of the determined prior periods. We tested the performance of the new method in the Loess Plateau by comparing various lag detection methods by using the linear model between the climate factors and the normalized difference vegetation index (NDVI). The case study confirmed four main findings: (1) the response of vegetation growth exhibits time lag to both precipitation and temperature; (2) there are apparent differences in the time lag effect detected by various methods, but the weighted time-lag method produced the highest determination coefficient (R2) in the linear model and provided the most specific lag pattern over the determined prior periods; (3) the vegetation growth is most sensitive to climate factors in the current month and the last month in the Loess Plateau but reflects a varied of responses to other prior months; and (4) the impact of temperature on vegetation growth is higher than that of precipitation. The new method provides a much more precise detection of the lag effect of climate change on vegetation growth and makes a smart decision about soil conservation and ecological restoration after severe climate events, such as long-lasting drought or flooding. [ABSTRACT FROM AUTHOR]

The lack of meteorological observation data limits the hydro-climatic analysis and modeling, especially for the ungauged or data-limited regions, while satellite and reanalysis products can provide potential data sources in these regions. In this study, three daily products, including two satellite products (Tropic Rainfall Measuring Mission Multi-Satellite Precipitation Analysis, TMPA 3B42 and 3B42RT) and one reanalysis product (China Meteorological Assimilation Driving Datasets for the SWAT Model, CMADS), were used to assess the capacity of hydro-climatic simulation based on the statistical method and hydrological model in Ganjiang River Basin (GRB), a humid basin of southern China. CAMDS, TMPA 3B42 and 3B42RT precipitation were evaluated against ground-based observation based on multiple statistical metrics at different temporal scales. The similar evaluation was carried out for CMADS temperature. Then, eight scenarios were constructed into calibrating the Soil and Water Assessment Tool (SWAT) model and simulating streamflow, to assess their capacity in hydrological simulation. The results showed that CMADS data performed better in precipitation estimation than TMPA 3B42 and 3B42RT at daily and monthly scales, while worse at the annual scale. In addition, CMADS can capture the spatial distribution of precipitation well. Moreover, the CMADS daily temperature data agreed well with observations at meteorological stations. For hydrological simulations, streamflow simulation results driven by eight input scenarios obtained acceptable performance according to model evaluation criteria. Compared with the simulation results, the models driven by ground-based observation precipitation obtained the most accurate streamflow simulation results, followed by CMADS, TMPA 3B42 and 3B42RT precipitation. Besides, CMADS temperature can capture the spatial distribution characteristics well and improve the streamflow simulations. This study provides valuable insights for hydro-climatic application of satellite and reanalysis meteorological products in the ungauged or data-limited regions. [ABSTRACT FROM AUTHOR]

Freshwater fishes are threatened by increasing environmental changes and human disturbances. The Min River, the largest river in Southeastern China, contains unique fish fauna for the Oriental realm. Due to environmental changes brought by forty years of economic growth, fish numbers have dramatically declined. The average taxonomic distinctness in the 1970s was significantly higher than that in 2015, while no significant differences were found in the variation in taxonomic distinctness between the two periods. Due to the river network and habitat diversity, fish fauna composition showed significant spatial differences but lower variation than the decadal variation. Precipitation was determined to be the most influential factor in determining the spatial pattern of fish fauna, followed by temperature. Species introduced for aquaculture have invaded the endemic fish community after escape and should be reconsidered in the trade-offs between economic development and ecological protection. [ABSTRACT FROM AUTHOR]

Since other factors (soil properties, topography, etc.) under natural conditions are relatively invariant over one or two decades, climate variables (precipitation and temperature) and human activities are the two fundamental factors driving vegetation changes in global or large-scale areas. However, the combined effects of either single climatic factor and human activities on vegetation changes and the role of human activities itself in a specific region has not been fully discussed. In this study, the Hexi region, a typical dryland consisting of three inland river basins in northwest China was selected as a case area. A new classification framework combining Pearson correlation analysis and residual trend approach was proposed to assess their individual and conjoint contributions of climate variables and human activities in areas of significant vegetation changes. Our results indicated that most of vegetation covered areas in the Hexi region experienced significant changes during the period 2001−2017, and vegetation improvements were widespread except the interior of oases; significant changes in vegetation caused by human activities, precipitation, the interactions of precipitation and human activities, temperature, the interactions of temperature and human activities, the interactions of temperature and precipitation, and the interactions of the three factors accounted for 50.46%, 16.39%, 19.90%, 4.33%, 2.32%, 2.11%, and 4.49% of the total change areas, respectively. Generally, the influence of temperature was relatively weaker than that of precipitation, and the contributions of the interactions of climate variables and human activities on vegetation changes were greater than that of climate contributions alone. Moreover, the results of various investigations, according to the trends and the time of vegetation changes, indicate that decreasing trends of the normalized difference vegetation index (NDVI) in the Hexi region were chiefly attributed to the adjustments of agricultural planting structure while the comprehensive treatment programs implemented in river basins supported a large proportion of vegetation improvements. [ABSTRACT FROM AUTHOR]

Since there are many destructive effects caused by extreme climate events in the Yellow River, it is of great theoretical and practical significance to explore the variations of climatic extremes in this key basin. We used a meteorological dataset from 66 stations within the Yellow River basin (YRB) for the period 1960–2017 to calculate magnitude and frequency of precipitation/temperature extremes. We also analyzed the relationships between the main large-scale atmospheric circulation patterns (ACPs) and precipitation/temperature extremes. The trends in precipitation extremes were nonsignificant, only a few stations were characterized by significantly increasing or decreasing anomalies; this indicates the precipitation intensity may have been strengthened, and the extreme rainfall duration appears to have been reduced during 1960–2017. The trends of magnitudes for "cold" extremes were larger than those for "warm" extremes, changes of trends in frost days were higher than those for summer days, and the trends in increasing warm nights were higher than those of warm days. The influence of the El Niño–Southern Oscillation (ENSO) and Arctic Oscillation (AO) on temperature extremes outweighed the influence of the North Atlantic Oscillation (NAO), Indian Ocean Dipole (IOD), and Pacific Decadal Oscillation (PDO) for the other extreme climate indices. The YRB might be at risk of increased extreme high temperature events, and more attention should be paid to this higher risk of extreme climatic events. [ABSTRACT FROM AUTHOR]