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In this paper, recent research on terrestrial ecosystem predictability using the conditional nonlinear optimal parameter perturbation (CNOP-P) method is summarized. The main findings include the impacts of uncertainties in climate change on uncertainties in simulated terrestrial ecosystems, the identification of key physical parameters that lead to large uncertainties in terrestrial ecosystem modeling and prediction, and the evaluation of the simulation ability and prediction skill of terrestrial ecosystems by reducing key physical parameter errors. The study areas included the Inner Mongolia region, north–south transect of eastern China, and Qinghai–Tibet Plateau region. The periods of the studies were from 1961 to 1970 for the impacts of uncertainties in climate change on uncertainties in simulated terrestrial ecosystems, and from 1951 to 2000 for the identification of the most sensitive combinations of physical parameters. Climatic Research Unit (CRU) data were employed. The numerical results indicate the important role of nonlinear changes in climate variability due to the occurrences of extreme events characterized by CNOP-P in the abrupt grassland ecosystem equilibrium state and formation of carbon sinks in China. Second, the most sensitive combinations of physical parameters to the uncertainties in simulations and predictions of terrestrial ecosystems identified by the CNOP-P method were more sensitive than those obtained by traditional methods (e.g., one-at-a-time (OAT) and stochastic methods). Furthermore, the improvement extent of the simulation ability and prediction skill of terrestrial ecosystems by reducing the errors of the sensitive physical parameter combinations identified by the CNOP-P method was higher than that by the traditional methods. [ABSTRACT FROM AUTHOR]

Groundwater is a primary freshwater resource for human consumption and an essential source for industry and agriculture. Therefore, understanding its spatial and temporal trends and drivers is crucial for governments to take appropriate measures to manage water resources. This paper uses Gravity Recovery and Climate Experiment (GRACE) satellite data and the Global Land Data Assimilation System (GLDAS) to derive groundwater storage anomalies (GWSAs) and to analyze the spatial and temporal trends of GWSA in different regions of China (Xinjiang, Tibet, Inner Mongolia, North China Plain, South China, and Northeast China). It used groundwater-level observation data to verify the accuracy of GWSA estimates and analyzed the drivers of regional GWSA changes. The results showed that: (1) GWSA in South China increased at a rate of 4.79 mm/a from 2003 to 2016, and GWSA in other regions in China showed a decreasing trend. Among them, the decline rates of GWSA in Xinjiang, Tibet, Inner Mongolia, North China Plain, and Northeast China were −6.24 mm/a, −3.33 mm/a, −3.17 mm/a, −7.35 mm/a, and −0.75 mm/a, respectively. (2) The accuracy of the annual-scale GWSA estimates was improved after deducting gravity losses due to raw coal quality, and the correlation coefficient between GWSA and groundwater levels monitored by observation wells increased. (3) In Xinjiang, the annual water consumed by raw coal mining, industrial, and agricultural activities had a greater impact on GWSA than rainfall and temperature, so these human activities might be the main drivers of the continued GWSA decline in Xinjiang. Water consumption by raw coal mining and industry might be the main drivers of the continued decline in GWSA in Inner Mongolia and the North China Plain. The increase in groundwater storage in South China was mainly due to the recharge of rainfall. [ABSTRACT FROM AUTHOR]

To evaluate the detection performance of ozone lidars, the first comprehensive vertical ozone observation experiment in China was conducted at the Xilinhot National Climate Observatory in Inner Mongolia from August to December 2023. The ozone profiles and concentrations of four ozone lidars were systematically compared and assessed with ozone radiosonde measurements and ozone analyzer observations both at ground-based stations and on an Unmanned Aerial Vehicle. The results show that the relative deviations of four ozone lidars are less than 20% compared with ozone radiosonde measurements at a height between 150 and 400 m. Ozone lidars have better behavior between 400 m and 2000 m than the lower altitude, with the deviation within 10% and the correlation coefficient around 0.8. However, relative deviations of lidars increased with altitude above 2000 m. The surface ozone concentrations observed using ozone lidars agreed well with the ground-based ozone analyzer, especially during periods with ozone concentrations higher than 40 µg·m−3. The correlation coefficients for most models of ozone lidar are higher than 0.53. A further investigation of the influence of precipitation events on ozone lidar measurement has been conducted, which revealed that thick cloud layers, low cloud base, and an intensive precipitation event with large raindrop particles can result in high anomalies and reduce the inversion accuracy of the ozone lidar. During the experiment, four ozone lidars were assessed quantitatively according to the comprehensive performance, which could help to improve inversion algorithms and the system design of this promising technique. [ABSTRACT FROM AUTHOR]

Precise water management is essential for the efficient development of irrigated agricultural crops in the Hetao Irrigation Area of Inner Mongolia. Given the severe water scarcity in the region and the significant use of intercropping as a cropping method, the development of rational irrigation scheduling is crucial. The objective of this work was to combine the ISAREG model with wheat–sunflower intercropping crops in order to enhance the effectiveness of irrigation scheduling in intercropping systems. This was achieved by changing and verifying crucial parameters for simulating irrigation patterns in intercropping. We conducted an assessment of nine irrigation schedules for a wheat–sunflower intercropping system in order to provide a range of irrigation scenarios that effectively fulfill the water requirements of the system. In light of this, we suggested implementing restrictions on the dates and volumes of irrigation based on the demand for agricultural irrigation. This approach aimed to establish irrigation schedules that are highly efficient and tailored to the specific crops in the area. As a result, we achieved a water use efficiency rate of 100%, saved 28.78% of water resources, optimized crop irrigation schedules, and enhanced crop economics by 6.7%. This study presents a novel and efficient method to optimize agricultural irrigation schedules, boost agricultural water use efficiency, and maximize crop yields in order to promote sustainable agricultural development. [ABSTRACT FROM AUTHOR]

Near-surface PM2.5 estimates remain a global scientific research challenge due to their effect on human fitness and atmospheric environmental quality. However, practical near-surface PM2.5 estimates are impeded by the incomplete monitoring data. In this study, we propose the trigonometric polynomial fitting (TPF) method to estimate near-surface PM2.5 concentrations in south-central China during 2015. We employ 10-fold cross-validation (CV) to assess the reliability of TPF in estimating practical PM2.5 values. When compared to alternative methods such as the orthogonal polynomial fitting (OBF) method based on Chebyshev basis functions, Kriging interpolation, and radial basis function (RBF) interpolation, our results show that utilizing TPF31, with a maximum order of 3 in the x direction and a maximum order of 1 in the y direction, leads to superior efficiency through error minimization. TPF31 reduces MAE and RMSE by 1.93%, 24%, 6.96% and 3.6%, 23.07%, 10.43%, respectively, compared to the other three methods. In addition, the TPF31 method effectively reconstructs the spatial distribution of PM2.5 concentrations in the unevenly distributed observation stations of Inner Mongolia and the marginal regions of the study area. The reconstructed spatial distribution is remarkably smooth. Despite the non-uniform distribution of observation stations and the presence of missing data, the TPF31 method demonstrates exceptional effectiveness in accurately capturing the inherent physical attributes of spatial distribution. The theoretical and experimental results emphasize that the TPF method holds significant potential for accurately reconstructing the spatial distribution of PM2.5 in China. [ABSTRACT FROM AUTHOR]

To further promote dust control efforts in Chinese open-pit coal mines, this study focuses on the research of coal dust and rock dust produced by different explosions in the Haerwusu open-pit coal mine in China. By investigating the relationship between the physical and chemical characteristics of dust particles from explosions in open-pit mines and the wetting properties of dust, the main factors influencing the wetting properties of explosive dust are identified. This provides a theoretical basis for subsequent dust control work in open-pit coal mines. Simultaneously, to formulate more effective dust suppressants and reduce explosive dust pollution, this study conducts experiments on the surface tension, contact angles, and complex solution compatibility to select suitable surfactants. Ultimately, the effectiveness of the dust suppressants is evaluated through permeability experiments and indoor dust suppression experiments. The research findings are as follows: (1) The significant factors affecting the wetting properties of coal dust are the fixed carbon content and D50, while the significant factor affecting the wetting properties of rock dust is D50. (2) The formulated dust suppressants can increase the permeation height of coal dust by at least 10 times, increase moisture absorption by at least 4 times, and reduce the TSP concentration by at least 81.4%. [ABSTRACT FROM AUTHOR]

The ecological conservation and high-quality development of the Yellow River Basin (YRB) has been declared as a major national strategy of China. Surface water availability (precipitation minus evapotranspiration, PME) poses challenges to the sustainability of ecosystems of the YRB. Noteworthy is that the Mongolian section of the YRB (IMYRB) is a critical ecological barrier in Northern China. Soil moisture (SM) changes are highly sensitive to PME and important for regional ecological security. However, SM vs. PME interactions and relevant mechanisms within the IMYRB are poorly understood. We found significant decreases in SM and PME over the east IMYRB (r = 0.7, p < 0.05). During the wet (July, August, and September) and dry (April, May, and June) seasons, as well as the whole year, decreased SM drives increased PME through land-atmosphere interactions over more than 90% of the IMYRB. Reduction in SM decreased evapotranspiration over more than 80% of the IMYRB, increased surface temperature across more than 79% of the IMYRB, boosted atmospheric vertical ascent over more than 75% of the IMYRB, and enhanced moisture convergence and PME. This study highlights the land-atmosphere interactions over the IMYRB, implicating basin-scale impacts of climatic changes on water resources. [ABSTRACT FROM AUTHOR]

The dust event from 12 January to 17 January 2021 ("1.12 event") is the first dust process in 2021 and the earliest dust event in the last two decades. The dust event from 14 to 18 March 2021 ("3.15 event") was the strongest dust storm in the past decade. Distribution, transport, and impact on urban air quality of these two typical dust events were studied using multi-source satellite data, a HYSPLIT trajectory model, and a 3D concentration-weighted trajectory model. Results show that both dust events affected a wide range of areas, covering Northwest, North, Northeast, East, and Central-South China. A strong dust belt spanning Northwest, North, and Northeast China was formed in northern China on 15 March 2021. The distribution heights of the 1.12 and 3.15 events were 0–5 km and 0–10 km, respectively. Dust from western Inner Mongolia and southern Mongolia dominated the 1.12 event, while dust from southern Mongolia dominated the 3.15 event. Both of these dust sources had eastward and southeastward transport paths. The majority of the dust was near-ground in downstream cities from an altitude of 0–3 km. Most cities were affected by the dust backflow. The 1.12 event generated more severe particulate pollution in southern China than the 3.15 event. During high-value dust days, ozone pollution levels decreased at the majority of stations. Dust weather with low dust rising heights and dust backflow phenomena should be taken seriously in urban dust pollution forecasting and warning work. International collaboration is needed to improve China's desertification control. [ABSTRACT FROM AUTHOR]

With global warming, previous studies have found nonuniformity responses of precipitation because of regional differences. However, climate change affects the mean, extreme, and data structure of precipitation. Quantile regression, which can reflect every part of the trends of data, was used to detect responses of each part of precipitation in China. The V2.0 dataset of daily precipitation grid data (0.5° × 0.5°) from 1961 to 2020 in China was used as practical observation data. Daily precipitation in 2015–2100 from the China Model BCC-CSM2-MR of scenarios SSP2-4.5 and SSP5-8.5 were chosen as future climate changes with moderate and high radiative forcing, respectively. On the basis of the sign consistency of the slope coefficients with quantile regression, the results of quantiles q = 0.3, 0.5, 0.7 and 0.9 were selected to represent low, median, high and flood precipitation, respectively. Precipitation in four seasons was separately analyzed to observe seasonal characteristics in China. For the observation data, precipitation had obviously different responses in the low and high percentiles and was present in mainly spring and summer. In spring, in the middle and lower Yangtze Plains, the low and median precipitation increased, whereas the high and flood precipitation significantly decreased. In summer, Heilongjiang Province and northern Inner Mongolia showed decreasing trends in the low quantile and increasing trends in the high quantile, indicating a completely opposite trend adjustment. These regions deserve more attention. However, obviously different responses in low and high percentiles were not so evident in future climate changes. Self-consistency in model data may weaken the heteroscedastic characteristics of precipitation. [ABSTRACT FROM AUTHOR]

Sand and dust storms (SDSs) cause major disasters in northern China. They have serious impacts on human health, daily life, and industrial and agricultural production, in addition to threatening the regional ecological environment and social economy. Based on meteorological observational data and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 dataset for spring 2000–2021, we used the Lamb–Jenkinson circulation classification method to classify the three major areas influencing SDSs in northern China. We also used the k-means clustering method to classify the overall circulation pattern in northern China. Our results show that the circulation types favoring SDSs in the southern basin of Xinjiang are southwesterly winds (SW), cyclones (C), and anticyclones (A). The circulation types favoring SDSs in western Inner Mongolia and southern Mongolia are northwesterly winds (NW), northerly winds (N), cyclones (C), and anticyclones (A). The circulation types favoring SDSs in central Inner Mongolia are northwesterly winds (NW), northerly winds (N), southwesterly winds (SW), and anticyclones (A). The 500 hPa and surface circulation patterns in China can be divided into nine types. Among them, five dominant circulation patterns favor strong SDSs: a cold high-pressure region and cold front (T1), a Mongolian cyclone (T2), a mixed type of Mongolian cyclone and cold front (T3), a thermal depression and cold front (T5), and a cold front (T8). During 2000–2004, the T8 circulation pattern occurred most frequently as the main influencing circulation. From 2005 to 2010, the T3 and T8 circulation patterns dominated. Circulation patterns T1 and T3 dominated during 2011–2015 and 2016–2020, respectively. We analyzed the main circulation patterns for four SDS events occurring in 2021 by combining the Lamb–Jenkinson and k-means methods. The SDS events in 2021 were closest to the T3 circulation pattern and were mainly influenced by Mongolian cyclones and surface cold fronts. The main propagation paths were westerly and northwesterly. [ABSTRACT FROM AUTHOR]