Coastal Areas Of China Research Articles

Assessment of floating solar photovoltaic potential in China

Solar energy has expanded rapidly in recent years, and China is the largest market in terms of installed capacity. With the aim of achieving carbon neutrality by 2060, solar power will play an increasingly important role in China. However, like many other countries, the low energy density of solar photovoltaics is one of the major drawbacks of its further development. The emergence of floating photovoltaic systems (FPV) can not only break this threshold but also generate a series of cobenefits from a brand-new energy-land-water nexus perspective. Using a GIS-MCDA model, an evaporation model, combined with a cost-benefit analysis, this paper estimates the development potential of FPV in China, and its energy-land-water cobenefits are further analyzed. Moreover, to reveal the current land constraint for developing solar photovoltaics in China, the potential of traditional terrestrial solar photovoltaics has also been evaluated. The results show that the potential installed capacity of FPV in China can reach 705.2 GW–862.6 GW with an annual 1164.9 TWh to 1423.8 TWh of potential power output, and most potential FPV stations can obtain positive financial returns. The annual water evaporation reduction is approximately 5.8 km3. In the meantime, around 7117.3 km2 of the land could be conserved, which would alleviate the land constraint for terrestrial solar photovoltaic systems, especially in the highly urbanized eastern and southern coastal areas in China.

Red Tide Detection Method Based on Improved U-Net Model-Taking GOCI Data in East China Sea as an Example.

In the coastal areas of China, the eutrophication of seawater leads to the continuous occurrence of red tide, which has caused great damage to Marine fisheries and aquatic resources. Therefore, the detection and prediction of red tide have important research significance. The rapid development of optical remote sensing technology and deep-learning technology provides technical means for realizing large-scale and high-precision red tide detection. However, the difficulty of the accurate detection of red tide edges with complex boundaries limits the further improvement of red tide detection accuracy. In view of the above problems, this paper takes GOCI data in the East China Sea as an example and proposes an improved U-Net red tide detection method. In the improved U-Net method, NDVI was introduced to enhance the characteristic information of the red tide to improve the separability between the red tide and seawater. At the same time, the ECA channel attention mechanism was introduced to give different weights according to the influence of different bands on red tide detection, and the spectral characteristics of different channels were fully mined to further extract red tide characteristics. A shallow feature extraction module based on Atrous Spatial Pyramid Convolution (ASPC) was designed to improve the U-Net model. The red tide feature information in a multi-scale context was fused under multiple sampling rates to enhance the model's ability to extract features at different scales. The problem of limited accuracy improvement in red tide edge detection with complex boundaries is solved via the fusion of deep and shallow features and multi-scale spatial features. Compared with other methods, the method proposed in this paper achieves better results and can detect red tide edges with complex boundaries, and the accuracy, precision, recall, and F1-score are 95.90%, 97.15%, 91.53%, and 0.94, respectively. In addition, the red tide detection experiments in other regions with relatively concentrated distribution also prove that the method has good applicability.

Ecosystem vulnerability to extreme climate in coastal areas of China

Climate change has far-reaching impacts on ecosystems and the frequency and intensity of extreme global climate events have been increasing over the past century; therefore, assessing ecosystem vulnerability to extreme climate change is critical for sustainable and adaptive ecosystem management. As a climatically sensitive region, coastal China is currently experiencing significant environmental changes. To identify how extreme climate affects ecosystem vulnerability, we calculated and analyzed the spatiotemporal variation in extreme climates, net primary productivity (NPP), and spatial characteristics of ecosystem vulnerability to extreme climate change, and discussed the response characteristics of different ecosystems to extreme climate events based on meteorological data and NPP (1986–2015). The results demonstrated that (1) coastal China has become increasingly warmer over the last thirty decades but the precipitation trend is different in the north and south: precipitation increased in the south and decreased in the north. (2) NPP is rising overall, with the forest ecosystem growing the fastest, particularly since 2010. (3) The ecosystem vulnerability of coastal areas in China is mainly classified as mild or non-vulnerable. However, there were apparent differences in the vulnerability of different ecosystems, with dry land and shrub ecosystems having the highest mean vulnerability. (4) The effects of extreme climates on the vulnerability of different ecosystems and ecosystems in different habitats vary. Overall, rising extreme temperatures can significantly increase the ecosystem vulnerability in the coastal areas of China. The paddy field ecosystem was more influenced by extreme temperatures than other ecosystems, with the southern paddy field ecosystem more influenced than the northern paddy field ecosystem. Our study advances the understanding of vegetation dynamics and their driving mechanisms and provides support for scientifically informed ecological management practices in coastal China.

A comparative study on the measurement of sustainable development of marine fisheries in China

Since 1989, China has been the largest aquatic producer in the world. The marine ecological environment is the “price” for the rapid development of fisheries economy, therefore, the sustainable development of fisheries industry is of great concern at home and abroad. This paper carried out a scientific evaluation of typical coastal provinces and cities by constructing an evaluation indicator system and clarifies the regional differences in the sustainable development capacity of China's marine fisheries industry for the first time. The results showed that since the second decade of the 21st century, the sustainability of marine fishery industry has been rising with fluctuation, among which, Shandong Province and Fujian Province have obvious advantages in sustainable development, while Tianjin, Hebei Province, and Shanghai still have large room for improvement. Resource environment and scientific and technological management factors have a significant impact on the sustainable development of China's marine fisheries, while economic and social factors have relatively little influence. Suggestions are put forward to improve the sustainable development level of marine fisheries in China's coastal areas, such as biological resources protection, fishery technology promotion and fishery industrial structure optimization.

Increasing compound hazard of landfalling tropical cyclones in China during 1980–2020

AbstractIdentifying the geographical regions where tropical cyclone (TC) activities are changing most is critical for policymakers to develop long‐term strategies for coastal disaster prevention. However, the key concerns for assessing the variation trends of the regional hazard caused by landfalling TCs are limited by data availability in the spatio‐temporal coverage and homogeneity. In this study, based on the high spatio‐temporal resolution ERA5 reanalysis data and a quasi‐Lagrangian approach, we investigate the long‐term variation trend of the compound hazard resulting from wind and precipitation during the landfall of the TCs in the coastal areas of China from 1980 to 2020. Two hotspot areas of TCs hazards are identified, one in the Taiwan Strait and surrounding areas, and the other in the Hainan Island and the northern South China Sea. The observed compound hazard in the former hotspot area shows a noticeable increasing trend over the past 40 years at a rate of 5% per year, while the latter hotspot area displays a robust decreasing trend. This variation pattern of the hazard trend is mainly attributed to the increased frequency of intense TCs (typhoon intensity grade and above) and the northward movement of TC track in China. The number of intense landfalling TCs in southeastern China nearly tripled in 2000–2019 compared to those in 1980–1999. The widespread increase in the compound hazard also suggests a rise in the disaster risk for the middle‐ and high‐latitude coastal regions of China, which require an immediate development and execution of advanced prevention strategies.

Design and spatial pattern optimization for a sponge city using factor analysis and geographical statistics to restore urban resilience: A case study in a coastal area of China

Abstract The sponge city is a new concept of stormwater management for ecological city construction, which aims to restore water-cycle processes and reduce runoff. Cities in coastal districts are suffering from serious instability due to high population density, urbanization, and land-use changes. However, previous research contains few evaluations of balancing urban ecological indicators of sponge city performance, including geographical, environmental, economic, and social factors, and their effect on resilience at a macro level to develop low-impact development schemes. In this study, we developed an integrated framework using factor analysis, geographical statistics, multi-objective analysis, and remote sensing methods to extract the factors influencing sponge city resilience and to establish spatial pattern schemes. The results indicated that the urbanization degree and plant adaptability had the greatest impact on sponge city performance, with weights of 45 and 27%, respectively. Sponge city spatial pattern schemes performed the best in the combination scenario of 14.8–46.8% green roofs (by area ratio) supported by grooves and rain barrels +10% herbaceous basins divided into units by ecological tree pools +10% permeable pavements and sidewalks. This scenario balanced facilities and cost to optimize the spatial pattern, which improved sponge city adaptability and urban ecological conditions.

Joint decision of green technology adoption and sailing pattern for a coastal ship under ECAs

In order to comply with the latest Emission Control Areas (ECAs) regulations, ships must use expensive low-sulphur fuel oil or relatively cheap high-sulphur fuel oil (HFO) with desulphurization equipment. This study investigates the choice of green fuel and green technology for a coastal container ship with endogenous decision of sailing pattern. The sufficient and necessary conditions for a ship to adopt scrubber installation (SI) strategy are derived, which is dependent on factors including the equivalent sailing distance, the fuel price ratio, and scrubber parameters. The case study based on the China's coastal area is conducted. Numerical examples show that the introduction of scrubber technology on coastal vessels will reduce their evasion behavior. However, the increased sulphur reduction efficiency of scrubbers increases the evasion strategies of ships, which will increase the total emissions in coastal areas. The numerical example shows that introduction the scrubber technology to the coastal ships will reduce their evasion behavior. However, the scrubber investment will increase ships' sailing speed, increasing emissions within ECA. Therefore, governments can subsidize high abatement efficiencies of the scrubber to reduce actual ship emissions.

Impact and pathway of halogens on atmospheric oxidants in coastal city clusters in the Yangtze River Delta region in China

Halogens (chlorine, bromine, and iodine) are known to profoundly influence atmospheric oxidants (hydroxyl radical (OH), hydroperoxyl radical (HO2), ozone (O3), and nitrate radical (NO3)) in the troposphere and subsequently affecting air quality. However, their impact on atmospheric oxidation and air pollution in coastal areas in China is poorly characterized. In this study, we use the WRF-CMAQ (Weather Research and Forecasting-Community Multiscale Air Quality) model with full halogen chemistry and process analysis to assess the influences and pathways of halogens on atmospheric oxidants in the Yangtze River Delta (YRD) region, a typical coastal city cluster in China. Halogens cause the annual OH radical increase by up to 16.4% and NO3 decrease by up to 45.3%. O3 increases by 2.0% in the YRD but decreases by 3.3% in marine environment. Halogen induced changes in atmospheric oxidants lead to a general increase of atmospheric oxidation capacity by 5.1% (maximum 48.4%). The production rate of OH (POH) in the YRD is enhanced by anthropogenic chlorine through both increased HO2 pathway and hypohalous acid photolysis pathway, while POH over ocean is enhanced by oceanic halogens through converting HO2 into hypohalous acid. Anthropogenic chlorine enhances both O3 and NO3 production (PNO3) rates through influencing their precursors while oceanic halogens reduce PNO3 and directly destroy ozone. Iodine contributed most (on average of 91% in oceanic halogens) in reducing production rates of oxidants. Thus, halogen emissions and potential effects of halogens on air quality need to be considered in air quality policies and regulations in the YRD region.

Effects of climate change and land use/cover changes on carbon sequestration in forest ecosystems in the coastal area of China

IntroductionClimate change and land use/cover changes (LUCC) greatly influenced terrestrial carbon sequestration.MethodsThis study evaluated the effects of climate change and LUCC on the carbon sequestration of forest ecosystems from 1991 to 2020 in the coastal area of China using a process-based global vegetation dynamic model (IBIS).Results and discussionThe results showed that temperature had an increasing trend, with a rate of 0.02 °C yr−1; 20.00% of the forest coverage shifted spatially but there was only a 0.31% increase in total area. The carbon sequestration amounts by plants (net primary productivity, NPP) and the net carbon budget (net ecosystem productivity, NEP) in the coastal area of China in 2020 were 666.49 and 58.45 Tg C yr−1, respectively, which increased by 18.31% and 2509.30%, respectively, compared to the values in 1991. The increased forest ecosystem NPP and NEP were mainly due to climate change, while forest cover changes increased NPP by only 0.06% and NEP by 9.75% with a strong regional difference. The NPP showed a significant increasing trend, with a rate of 3.01 Tg C yr−1, which was positively correlated with temperature (0.43, p < 0.01) and precipitation (0.42, p < 0.01). However, the NEP largely varied during 1991-2020 and did not show a significant correlation with precipitation or temperature. These results provide scientific guidance for the government to enact environmental protection and low-carbon land use planning policies.

Coupled patterns of natural and anthropogenic resources in typical ecosystems in coastal areas of China

The coastal area of Yancheng, China, is one of the hotspots for ecological research. Under the coupling of human and natural ecosystems, the region has gradually evolved into a coexistence of aquatic, agricultural and mudflat ecosystems. What are the patterns of natural and artificial resource inputs and patterns of change in ecosystems? How can ecological flows be analyzed at a uniform scale? Here, we selected six typical local ecosystems, namely, rice‒wheat for enterprises (RWE), rice‒wheat for smallholder households (RWS), chrysanthemum‒wheat (CW), fish polyculture (FP), juvenile crab farming (JF) and clam polyculture (CP), and analyzed their energy flow flux and sustainability based on emergy theory. The results showed that anthropogenic resource inputs were higher than natural resource inputs in all ecosystems, and the inputs of aquatic ecosystems were greater than those of agroecosystems. The greatest total input was 2.0 E+17 seJ/ha/yr for FP, and the lowest was 1.9 E+16 seJ/ha/yr for RWE. The proportions of renewable and artificial inputs for RWE, RWS, CW, FP, JF and CP were 32.8% vs. 96.1%, 40.3% vs. 96.5%, 34.7% vs. 97.0%, 32.6% vs. 99.4%, 55.1% vs. 98.5%, and 62.5% vs. 98.6%, respectively. The highest input to agroecosystems was nitrogen fertilizer, while in JF and CP, it was water, and feed (63.3%) accounted for the highest percentage of input in FP. JF and CP had lower environmental loads and higher sustainability than other ecosystems, but this still represents a high input compared to agroecosystems. Human-led resource coupling profoundly affects ecosystem sustainability, and various thresholds of energy use and ecological sustainability need to be studied in depth. Continuous exploration of methods and mechanisms for the maintenance and evolution of ecosystems with low total inputs and low inputs of non-renewable resources can contribute to high-quality sustainable development of an area or region.

Deep Learning in Chinese Text Information Extraction Model for Coastal Biodiversity

In the coastal areas of China, scientists have collected nearly 500 species of coastal plants and seaweeds. The collected information includes species description, morphological characteristics, habitat distribution and resource value of plants in China. By effectively extracting Chinese text information, this article establishes a Chinese text information extraction model based on DL. This article is based on short-term and short-term memory artificial neural networks for short text classification. In addition, this article also integrates the L-MFCNN models of MFCNN for short text classification. Comparing the two methods with traditional text recognition algorithms, information extraction based on syntax analysis and deep learning, the results show that, compared with the comparison method, the recognition accuracy of Chinese text information of this neural network model can reach 96.69%. Through model training and parameter adjustment, Chinese text information of coastal biodiversity can be quickly extracted, and species categories or names can be identified.

Bayesian phylodynamic analysis reveals the evolutionary history and the dispersal patterns of citrus tristeza virus in China based on the p25 gene

BackgroundCitrus tristeza virus (CTV) is one of the most serious threats to the citrus industry, and is present in both wild and cultivated citrus. The origin and dispersal patterns of CTV is still poorly understood in China.MethodsIn this study, 524 CTV suspected citrus samples from China were collected, including 354 cultivated citrus samples and 174 wild citrus samples. Finally, 126 CTV coat protein sequences were obtained with time-stamped from 10 citrus origins in China. Bayesian phylodynamic inference were performed for CTV origin and dispersal patterns study in China.ResultWe found that CTV was mainly distributed in southern and coastal areas of China. The substitution rate of CTV was 4.70 × 10− 4 subs/site/year (95% credibility interval: 1.10 × 10− 4 subs/site/year ~ 9.10 × 10− 4 subs/site/year), with a slight increasing trend in CTV populations between 1990 and 2006. The CTV isolates in China shared a most common recent ancestor around 1875 (95% credibility interval: 1676.57 ~ 1961.02). The CTV in China was originated from wild citrus in Hunan and Jiangxi, and then spread from the wild citrus to cultivated citrus in the growing regions of Sichuan, Chongqing, Hubei, Fujian, Zhejiang, Guangxi and Guangdong provinces.ConclusionsThis study has proved that CTV in China was originated from wild citrus in Hunan and Jiangxi. The spatial-temporal distribution and dispersal patterns has uncovered the population and pandemic history of CTV, providing hints toward a better understanding of the spread and origin of CTV in China.

Groundwater Vulnerability Assessment and Protection Strategy in the Coastal Area of China: A GIS-Based DRASTIC Model Approach

Groundwater vulnerability reflects the risk level of groundwater contamination and its self-repairing ability, as well as its sustainability for use. Therefore, it provides significant scientific support for implementing measures to prevent groundwater contamination, especially in coastal areas. In this study, considering the lithology of vadose in valley plains and the extent of karst subsidence areas, a GIS-based DRASTIC model was employed to assess groundwater vulnerability in Tangshan City, a coastal area in China. The assessment results were presented and mapped using GIS, based on a comprehensive evaluation of seven parameters, including “Depth of groundwater, Vertical net recharge, Aquifer thickness, Soil media, Topography, Impact of vadose zone, and Hydraulic conductivity”. The identified groundwater vulnerability zones included the highest, higher, moderate, low vulnerability those four zones, which accounted for 4%, 53%, 25%, and 18%, respectively. In addition, according to the results of field investigation, the karst subsidence area and the mined-out coastal area were directly classified as the highest vulnerable areas and covered 1.463 km2; more attention is required here in subsequent groundwater protection processes and strategies. Finally, the groundwater pollution index was used to validate the groundwater vulnerability distribution results, and these two were in high agreement, with an R2 coefficient of 0.961. The study is crucial for the rational utilization and protection of water resources in Tangshan City.

Indirect and Direct Impacts of Typhoon In-Fa (2021) on Heavy Precipitation in Inland and Coastal Areas of China: Synoptic-Scale Environments and Return Period Analysis

Abstract In July 2021, Typhoon In-Fa (TIF) triggered a significant indirect heavy precipitation event (HPE) in central China and a direct HPE in eastern China. Both these events led to severe disasters. However, the synoptic-scale conditions and the impacts of these HPEs on future estimations of return periods remain poorly understood. Here, we find that the remote HPE that occurred ∼2200 km ahead of TIF over central China was a predecessor rain event (PRE). The PRE unfolded under the equatorward entrance of the upper-level westerly jet. This event, which encouraged divergent and adiabatic outflow in the upper level, subsequently intensified the strength of the upper-level westerly jet. In contrast, the direct HPE in eastern China was due primarily to the long duration and slow movement of TIF. The direct HPE occurred in areas situated less than 200 km from TIF’s center and to the left of TIF’s propagation trajectory. Anomaly analyses reveal favorable thermodynamic and dynamic conditions and abundant atmospheric moisture that sustained TIF’s intensity. A saddle-shaped pressure field in the north of eastern China and peripheral weak steering flow impeded TIF’s movement northward. Hydrologically, the inclusion of these two HPEs in the historical record leads to a decrease in the estimated return periods of similar HPEs. Our findings highlight the potential difficulties that HPEs could introduce for the design of hydraulic engineering infrastructure as well as for the disaster mitigation measures required to alleviate future risk, particularly in central China.

Does marine ecological compensation policy have improved marine carbon emission efficiency? Evidence from coastal areas in China.

The marine ecological compensation (MEC) policy is a scheme for protecting and restoring marine ecology. The previous studies have verified that the policy has improved the marine environment, ignoring the comprehensive performance of the economy and environment. Is the MEC policy actually effective for reducing marine carbon emission considering resource input and economy output? To address the question, this paper evaluates the impact of MEC policy on marine carbon emission efficiency by introducing the multi-stage difference-in-difference with propensity score matching. The results show that the MEC policy significantly improves marine carbon emission efficiency, and the positive effects dynamically enhance over time. Low-carbon technology innovation is confirmed to play a mediating role by which the MEC policy improves marine carbon emission efficiency. Therefore, gradually popularizing the MEC policy and accelerating low-carbon technology innovation are crucial measures to improve marine carbon emission efficiency and achieve sustainable marine development.

Risk assessment for yachting tourism in China using dynamic Bayesian networks.

Scientific evaluation of yachting tourism safety risks (YTSRs) is crucial to reducing accidents in this sector. This paper is based on the data of 115 yachting tourism accidents in China's coastal areas from 2008 to 2021. A fishbone diagram and the analytic hierarchy process (AHP) were used to identify the risk factors of yachting tourism from four aspects human, yachting, environmental, and management risk and to construct an evaluation index system. To perform dynamic evaluation, a dynamic evaluation model of YTSRs was built using dynamic Bayesian networks (DBN). The results indicate that human factors, such as the unsafe behavior of yachtsmen and tourists, are the primary risk factors; the risk is higher in summer than in winter, and the Pearl River Delta region has a greater risk of yachting tourism. It is suggested to improve the normal safety risk prevention and control system of yachting tourism, to advocate for multi-subject coordination and co-governance, and to improve the insurance service system so as to provide a guarantee for the safe and healthy development of yachting tourism in China. The findings provide theoretical and practical guidance for marine and coastal tourism safety management, as well as the prevention and control of YTSRs.

Investigating mangrove canopy phenology in coastal areas of China using time series Sentinel-1/2 images

Mangrove forests with high vegetation productivity play crucial roles in the coastal blue carbon ecosystem. Accurate monitoring of mangrove canopy phenology is essential to improve the survival rate of restoration plantings and maintain the health and sustainability of mangrove ecosystems. Remote sensing technology has been commonly used for monitoring vegetation phenology, while there remain knowledge gaps in exploring the remotely-sensed phenology of mangrove forests in coastal China. In this study, we investigated the phenological characteristics of two typical mangrove sites in coastal China using remote sensing indices based on Sentinel-1 and Sentinel-2 time series during 2016–2020, compared the performances of mangrove phenology detection across different remote sensing indices and spatial scales, and explored the influences of environmental factors based on meteorological data. The results demonstrated that enhanced vegetation index (EVI), red-edge band index (NDRE2), phenology index (NDPI), and radar vegetation index (RVI) were efficient in characterizing mangrove phenological trajectories. Sentinel-2 data can precisely describe the phenological characteristics of mangroves and has the highest correlation with ground-observed phenology data (r = −0.581), when compared to Landsat-8 and MODIS data. The meteorological factors of precipitation, humidity, and wind speed mainly led to the differences in mangrove phenology across the two study sites. This finding can improve our understanding of the phenological characteristics of mangrove forests in coastal China, which facilitates local governments to develop appropriate mangrove restoration and management policies.

Spatial distribution and potential ecological risk assessment of heavy metals in the sediments of fishing ports along the coasts of the Yellow Sea and Bohai Sea

More than 1,154 fishing ports are widely distributed in China's coastal areas. To date, however, few studies on the pollution and ecological risks of heavy metals in these fishing ports have been reported. In this study, the heavy metals of 148 sediment samples collected from 37 fishing ports along the coasts of the Yellow Sea and Bohai Sea were detected. The results showed that the average contents of Cu, Pb, Zn, and Cd were 53.58 ± 44.53, 27.90 ± 18.10, 143.52 ± 74.72 and 0.28 ± 0.15 mg/kg, respectively. Based on the geoaccumulation index (Igeo) and the potential ecological risk index (RI), we found that fishing ports were the most severely polluted by Cu, but Cd had the highest ecological risk, and most of fishing ports were in moderate potential ecological risk. The positive correlation between heavy metals and total organic carbon indicated that heavy metals in fishing ports were mainly affected by anthropogenic activities.

Spatial evolution of global petrochemical risk and the influence by industrialization.

The petrochemical industry is an integral contributor to the global economy and plays a critical role in improving the lives of people worldwide. However, its development has also led to frequent accidents, and the evolution and global impact of these risks have not been adequately assessed. This study is aimed at quantitatively analyzing the current state of petrochemical risk and its impact on industrial development in 58 coastal countries (regions) worldwide by identifying petrochemical risk impact indicators and constructing threshold regression models. We showed that the global petrochemical risk has been unevenly decreasing in recent years. In some countries (regions), the petrochemical risk remains unchanged or is increasing; in particular, coastal provinces of China need to address this issue. Moreover, when industrialization and economic development levels are < 53.6 and 34,918.4 USD/person, respectively, petrochemical accidents negatively affect industrial development; however, above these thresholds, they do not impact industrial development. Coastal areas of China and some developing countries are far below these thresholds. Therefore, the risk from petrochemicals remains a critical factor affecting industrial development in countries with low industrialization levels.

Changes in Temperature‐Precipitation Compound Extreme Events in China During the Past 119 Years

AbstractThis study analyzes the change characteristics of compound extreme events (CEEs) of temperature and precipitation (including warm‐wet, warm‐dry, cold‐wet and cold‐dry) in China on interannual and interdecadal scales between 1901 and 2019. The results demonstrate a long‐term increasing trend and interdecadal oscillations in CEEs total frequency. However, the frequency of each type of CEEs changes in a different manner compared with total CEEs frequency. There are fewer CEEs but increasing warm‐dry during 1901–1950. The period 1951–1995 are characterized by frequent cold CEEs (cold‐wet and cold‐dry), cold‐wet are largely distributed in most areas except for northeast and coastal areas of China, while cold‐dry are distributed in most areas except for the northwest regions of China. There are frequent warm CEEs (warm‐wet and warm‐dry) and fewer cold CEEs during 1996–2019. Warm‐wet frequently occurs in the Tibetan Plateau and northwest China, and warm‐dry mainly concentrates in southwest and northern China during this period. The frequency of warm‐dry and cold‐wet were higher than that of warm‐wet and cold‐dry over the past 119 years, whereas warm‐wet increased fastest in the northwest region after 1996, consistent with the warming and wetting characteristics in the northwest region of China. Further study show that long‐term change and low frequency oscillations have the greatest impact on CEEs among different time scale factors. Furthermore, the temperature rise caused by climate change affects the interdecadal characteristics of CEEs in China through the changes of circulation fields such as East Asian trough and subtropical high and the configuration between them.