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Characteristics of Extreme Climate Events over China

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A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology".

Deadline for manuscript submissions: closed (10 May 2024) | Viewed by 9383

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Special Issue Editor

Dr. Jie Wu

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Guest Editor

China Meteorological Administration Key Laboratory for Climate Prediction Studies, National Climate Center, Beijing 100081, China
Interests: subseasonal-to seasonal prediction; predictability; Madden–Julian oscillation; extreme event; Northeast cold vortex

Special Issue Information

Dear Colleagues,

In the context of global warming, increasing numbers of extreme climate events are occurring in China, with amplifying intensity and expanding influence. Extreme climate events, such as the super Meiyu in 2020, the persistent rainfall in North China in autumn 2021, and the record-breaking high temperature and drought in the Yangtze River Basin in 2022, have had a significant impact on agricultural production and social economy, and have even posed a large threat to people's lives and property. Therefore, it has become necessary to analyze the characteristics and understand the causes of these anomalous climates and extreme events over China. Documenting and explaining the most significant extreme climate events are vital to improve scientific understanding of the fast-evolving climate, and to provide the public and policymakers with timely, peer-reviewed, authoritative scientific information.

Therefore, the main objective of this Special Issue is to contribute to our understanding of extreme climate events over China and to provide science-based knowledge and novel approaches to predict extreme events in terms of subseasonal-to-seasonal timescales. We encourage authors to share their opinions, knowledge, and achievements regarding the characteristics, mechanisms, predictability, and prediction methods of extreme events and the influence of human activities and future projection. New methods of measurements and detection of extreme events, such as the use of satellite data or deep learning methods to identify and forecast extreme events, are also encouraged. In particular, the following topics are of great interest:

Multi-scale characteristics of extreme climate events;
Mechanisms of extreme climate events;
Predictability and prediction methods;
Trends of extreme climate events and their interaction with human activities;
Use of deep learning methods to identify and forecast extreme climate events.

Dr. Jie Wu
Guest Editor

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Keywords

extreme climate events
characteristics analysis
predictability
prediction methods
projection

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Published Papers (8 papers)

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Research

13 pages, 8386 KiB

Open AccessArticle

Nocturnal Extreme Rainfall over the Central Yungui Plateau under Cold and Warm Upper-Level Anomaly Backgrounds during Warm Seasons in 1980–2020

by Weihua Yuan and Zhi Li

Atmosphere 2024, 15(9), 1057; https://doi.org/10.3390/atmos15091057 - 1 Sep 2024

Viewed by 482

Abstract

The spatiotemporal and cloud features of the extreme rainfall under the warm and cold upper-level anomalies over the central Yungui Plateau (YGP) were investigated using the hourly rain gauge records, ERA5 reanalysis data, TRMM, and Fengyun satellite data, aiming to refine the understanding of different types of extreme rainfall. Extreme rainfall under an upper-level negative temperature anomaly (cold events) presents stronger convective cloud features when compared with the positive temperature anomaly (warm events). The maximum rainfall intensity and duration in cold events is much larger than that of warm events, while the brightness temperature of the cloud top is lower, and the ratio of convective rainfall is higher. In cold events, the middle-to-upper troposphere is dominated by a cold anomaly, and an unstable configuration with upper (lower) cold (warm) anomalies is observed around the central YGP. Although the upper-level temperature anomaly is positive, the anomalous divergence and convergence of southerly and northerly winds, as well as the strong moisture center and upward motions, are also found over the central YGP in warm events. The stronger atmospheric instability and higher convective energy under the upper-level cold anomalous circulation are closely associated with the rainfall features over the central YGP. The results indicate that the upper tropospheric temperature has significant influences on extreme rainfall, and thus more attention should be paid to the upper tropospheric temperature in future analyses. Full article

(This article belongs to the Special Issue Characteristics of Extreme Climate Events over China)

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16 pages, 9590 KiB

Open AccessArticle

The Evaluation of Rainfall Forecasting in a Global Navigation Satellite System-Assisted Numerical Weather Prediction Model

by Hongwu Guo, Yongjie Ma, Zufeng Li, Qingzhi Zhao and Yuan Zhai

Atmosphere 2024, 15(8), 992; https://doi.org/10.3390/atmos15080992 - 17 Aug 2024

Viewed by 1059

Abstract

Accurate water vapor information is crucial for improving the quality of numerical weather forecasting. Previous studies have incorporated tropospheric water vapor data obtained from a global navigation satellite system (GNSS) into numerical weather models to enhance the accuracy and reliability of rainfall forecasts. However, research on evaluating forecast accuracy for different rainfall levels and the development of corresponding forecasting platforms is lacking. This study develops and establishes a rainfall forecasting platform supported by the GNSS-assisted weather research and forecasting (WRF) model, quantitatively assessing the effect of GNSS precipitable water vapor (PWV) on the accuracy of WRF model forecasts for light rain (LR), moderate rain (MR), heavy rain (HR), and torrential rain (TR). Three schemes are designed and tested using data from seven ground meteorological stations in Xi’an City, China, in 2021. The results show that assimilating GNSS PWV significantly improves the forecast accuracy of the WRF model for different rainfall levels, with the root mean square error (RMSE) improvement rates of 8%, 15%, 19%, and 25% for LR, MR, HR, and TR, respectively. Additionally, the RMSE of rainfall forecasts demonstrates a decreasing trend with increasing magnitudes of assimilated PWV, particularly effective in the range of [50, 55) mm where the lowest RMSE is 3.58 mm. Moreover, GNSS-assisted numerical weather model shows improvements in statistical forecasting indexes such as probability of detection (POD), false alarm rate (FAR), threat score (TS), and equitable threat score (ETS) across all rainfall intensities, with notable improvements in the forecasts of HR and TR. These results confirm the high precision, visualization capabilities, and robustness of the developed rainfall forecasting platform. Full article

(This article belongs to the Special Issue Characteristics of Extreme Climate Events over China)

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17 pages, 3601 KiB

Open AccessArticle

Simulation and Diagnosis of Physical Precipitation Process of Local Severe Convective Rainstorm in Ningbo

by Tingting Lu, Yeyi Ding, Zan Liu, Fan Wu, Guoqiang Xue, Chengming Zhang and Yuan Fu

Atmosphere 2024, 15(6), 658; https://doi.org/10.3390/atmos15060658 - 30 May 2024

Viewed by 581

Abstract

On 31 July 2021, Ningbo, an eastern coast city in China, experienced a severe convective rainstorm, characterized by intense short-duration precipitation extremes with a maximum rainfall rate of 130 mm h⁻¹. In this research, we first analyzed this rainstorm using Doppler radar and precipitation observation and then conducted high-resolution simulation for it. A three-dimensional precipitation diagnostic equation is introduced to quantitatively analyze the microphysical processes during the rainstorm. It is shown that this rainstorm was triggered and developed locally in central Ningbo under favorable large-scale quasi-geostrophic conditions and local conditions. In the early stage, the precipitation increase is mainly driven by the strong convergence of water vapor, and a noticeable increase in both the intensity and spatial extent of uplift promotes the upward transportation of water vapor. As the water vapor flux and associated convergence weaken in the later stage, the precipitation reduces accordingly. Cloud microphysical processes are also important in the entire precipitation process. The early stage updraft supports the escalations in raindrops, with the notable fluctuations in raindrop concentrations directly linked to variations in ground precipitation intensity. The behavior of graupel particles is intricately connected to their melting as they fall below the zero-degree layer. Although cloud water and snow exhibit changes during this period, the magnitudes of these adjustments are considerably less pronounced than those in raindrops and graupels, highlighting the differentiated response of various condensates to the convective dynamics. These results can help deepen the understanding of local severe rainstorms and provide valuable scientific references for practical forecasting. Full article

(This article belongs to the Special Issue Characteristics of Extreme Climate Events over China)

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16 pages, 7351 KiB

Open AccessEditor’s ChoiceArticle

Study of the Spatiotemporal Distribution Characteristics of Rainfall Using Hybrid Dimensionality Reduction-Clustering Model: A Case Study of Kunming City, China

by Weijie Lin, Yuanyuan Liu, Na Li, Jing Wang, Nianqiang Zhang, Yanyan Wang, Mingyang Wang, Hancheng Ren and Min Li

Atmosphere 2024, 15(5), 534; https://doi.org/10.3390/atmos15050534 - 26 Apr 2024

Viewed by 965

Abstract

In recent years, the frequency and intensity of global extreme weather events have gradually increased, leading to significant changes in urban rainfall patterns. The uneven distribution of rainfall has caused varying degrees of water security issues in different regions. Accurately grasping the spatiotemporal distribution patterns of rainfall is crucial for understanding the hydrological cycle and predicting the availability of water resources. This study collected rainfall data every five minutes from 62 rain gauge stations in the main urban area of Kunming City from 2019 to 2021, constructing an unsupervised hybrid dimensionality reduction-clustering (HDRC) model. The model employs the Locally Linear Embedding (LLE) algorithm from manifold learning for dimensionality reduction of the data samples and uses the dynamic clustering K-Means algorithm for cluster analysis. The results show that the model categorizes the rainfall in the Kunming area into three types: The first type has its rainfall center distributed on the north shore of Dian Lake and the southern part of Kunming’s main urban area, with spatial dynamics showing the rainfall distribution gradually developing from the Dian Lake water body towards the land. The second type’s rainfall center is located in the northern mountainous area of Kunming, with a smaller spatial dynamic change trend. The water vapor has a relatively fixed and concentrated rainfall center due to the orographic uplift effect of the mountains. The third type’s rainfall center is located in the main urban area of Kunming, with this type of rainfall showing smaller variations in all indicators, mainly occurring in May and September when the temperature is lower, related to the urban heat island effect. This research provides a general workflow for spatial rainfall classification, capable of mining the spatiotemporal distribution patterns of regional rainfall based on extensive data and generating typical samples of rainfall types. Full article

(This article belongs to the Special Issue Characteristics of Extreme Climate Events over China)

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26 pages, 9167 KiB

Open AccessArticle

Spatiotemporal Analysis of Hydrometeorological Factors in the Source Region of the Dongting Lake Basin, China

by Shanshan Li, Changbo Jiang, Yuan Ma and Chuannan Li

Atmosphere 2023, 14(12), 1793; https://doi.org/10.3390/atmos14121793 - 6 Dec 2023

Cited by 1 | Viewed by 1320

Abstract

The Dongting Lake basin, located in the middle Yangtze River region, has long been under the threat of climate change. However, there has been a lack of comprehensive analysis and research on the long-term trends and interactions among hydrometeorological factors within the region. To address this gap, this study collected data from 31 meteorological stations in the region and employed statistical analysis methods, including the non-parametric Mann–Kendall test, Sen’s slope test, and cross-wavelet analysis. The results revealed significant increases in temperatures, especially in the spring season, while summer, winter, and annual rainfall also exhibited a significant increase. However, spring and autumn rainfall showed a non-significant decrease, and there was a clear decreasing trend in annual streamflow. Interestingly, evaporation demonstrated a significant increasing trend. The annual average temperature and annual runoff exhibited approximately negative correlations in the 6–10-year resonance period and positive correlations in the 4–6-year resonance period. There are significant positive resonance periods in the relationship between annual precipitation and annual runoff within the range of 0–12 years, indicating that precipitation has a substantial impact and serves as the primary source of runoff. Furthermore, there was a transition between “abundance” and “dry” periods in the annual runoff around 4 a, occurring before and after 1973 and 2005. The change points in annual precipitation and runoff were identified as 1993 and 1983. Full article

(This article belongs to the Special Issue Characteristics of Extreme Climate Events over China)

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30 pages, 16190 KiB

Open AccessArticle

Spatiotemporal Characteristics of Hourly-Scale Extreme Precipitation in the Sichuan Basin and Its Impact on Normalized Difference Vegetation Index Values

by Ying Xiang, Zhongliang Li, Yixiao Wu, Keqing Wang and Jie Yang

Atmosphere 2023, 14(12), 1719; https://doi.org/10.3390/atmos14121719 - 22 Nov 2023

Cited by 1 | Viewed by 1494

Abstract

This study harnesses ground observation data collected between 1980 and 2021 and ERA5 hourly data to thoroughly implement trend and correlation analysis techniques to explore the spatiotemporal dynamic characteristics of daily and hourly extreme precipitation in the Sichuan Basin. The investigation delineates these characteristics and probes into the potential triggers of extreme hourly rainstorms. The findings unveil the following: (1) A general increase in extreme rainfall volume, contribution rate, intensity, and dispersion, along with a decline in frequency and proportion of rainstorm areas, indicating the concentration of daily-scale severe rainstorms. The basin’s edge receives more precipitation than the bottom, exhibiting latitudinal variations. (2) The northernmost mountainous regions have less frequent, less intense rainstorms influenced by terrain, whereas the northeastern region experiences more frequent, dispersed rainstorms. (3) Extreme hourly rainstorms predominantly occur at night, with rainfall amount, intensity, and frequency declining at 21:00 compared to 19:00. (4) Summer experiences the highest risk of extreme rainstorms, with annual and monthly datasets displaying a rising trend in the frequency, dispersion, and intensity of intense hourly rainstorms. (5) Peak values of extreme hourly rainstorms are growing, with two distinct periods for their frequency: 1:00–9:00 and 10:00–24:00, with an increase in the former and a decrease in the latter. (6) Normalized difference vegetation index (NDVI) values ascend from southwest to northeast within the basin on a ten-day scale, correlating with the distribution of hourly extreme precipitation. Full article

(This article belongs to the Special Issue Characteristics of Extreme Climate Events over China)

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18 pages, 4460 KiB

Open AccessArticle

The Frequency of Extreme Cold Events in North China and Their Relationship with Sea Surface Temperature Anomalies

by Na Yang, Liping Li, Yike Ren, Wenjie Ni and Lu Liu

Atmosphere 2023, 14(11), 1699; https://doi.org/10.3390/atmos14111699 - 17 Nov 2023

Cited by 1 | Viewed by 1504

Abstract

This study investigated the interdecadal characteristics of the frequency of the winter single station extreme cold events (SSECEs) in North China and their relationship with sea surface temperature (SST). The results showed the following: (a) The SSECEs occurred frequently before 1991, but less thereafter, with an increase after 2018. The first two interdecadal modes of the SSECE frequency were east–west inverse and “n” patterns. (b) The interdecadal abrupt change of the “n” pattern occurred around 1997/1998. Before 1997/1998, the synergistic effects between the positive Interdecadal Pacific Oscillation (+IPO) and the negative North Atlantic Multidecadal Oscillation (−AMO) triggered the “two troughs and one ridge” anomalous circulation in Eurasia. The Rossby wave energy propagated downstream from the Atlantic, strengthening the Lake Baikal ridge. Furthermore, the Siberian High (SH) became weaker in the north and stronger in the south. With the favorable jet conditions, the cold air invaded North China along the northerly airflow in front of the Lake Baikal ridge, resulting in the frequent SSECE occurrence in central North China. Afterwards, the opposite occurred. (c) The cooperation of SST anomalies (SSTAs) led to the east–west inverse anomaly of the SSECE frequency. Before 1991, the high SSTAs in the central North Atlantic and low SSTAs in the equatorial Indian Ocean and the southwest Pacific triggered “+”, “−”, “+”, and “−” wave trains at mid-latitudes from the Atlantic to the North Pacific. The Rossby wave energy propagated eastward from the Atlantic, resulting in the SH and Urals ridge strengthening, and the Aleutian Low and East Asian trough deepening. The northwestern airflow in front of the Urals ridge guided the cold air into North China, leading to frequent SSECEs in central and eastern North China before 1991. The opposite occurred between 1992 and 2018. Full article

(This article belongs to the Special Issue Characteristics of Extreme Climate Events over China)

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17 pages, 8491 KiB

Open AccessArticle

Predictive Study on Extreme Precipitation Trends in Henan and Their Impact on Population Exposure

by Zongming Wang, Yuyan Wu, Shiping Xi and Xuerong Sun

Atmosphere 2023, 14(10), 1484; https://doi.org/10.3390/atmos14101484 - 25 Sep 2023

Cited by 1 | Viewed by 1269

Abstract

This study employs precipitation data sets from historical trials on 20 CMIP6 global climate models and four shared socioeconomic pathway scenario trials (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) to predict trends in extreme precipitation changes in Henan Province quantitatively, while ascertaining the risk of population exposure to extreme precipitation in this area. The capacity of the CMIP6 models to simulate extreme precipitation indices from 1985 to 2014 is assessed using CN05.1 daily precipitation observational data. The correlation coefficients of the multi-model ensemble median’s simulation of the extreme precipitation indices are approximately 0.8, with a standard deviation ratio closer to 1 compared with the single models, demonstrating superior modeling ability. Analyses using the multi-model ensemble median demonstrate an overall increase in the total amount, frequency, and intensity of extreme precipitation in Henan throughout this century, particularly in its southern regions; in the mid-century high-emission scenario (SSP5-8.5), the maximum increase in annual total precipitation exceeds 150 mm, and it can be over 250 mm in the late-century period. For the entire province, the maximum five-day precipitation increase relative to the historical period is nearly 25 mm in the late-century SSP5-8.5 scenario. The spatiotemporal concentration of precipitation will significantly increase, heightening the risk of flood disasters. Comparative analysis reveals that, under the same population prediction, the total population exposure will be higher in high radiative forcing scenarios than in low radiative forcing scenarios, especially in Kaifeng City, where the total population exposure in SSP1 and SSP5-8.5 exceeds that in SSP1-2.6 by 2 million person-days. However, in the same radiative forcing scenario, the total population exposure in the development pathway dominated by traditional fossil fuels (SSP5) will not be significantly higher than that in the sustainable development pathway (SSP1), indicating that population activity in this century will not be the main contributor to changes in total exposure. Overall, for Henan, in the same population forecast scenario, population exposure to extreme precipitation will gradually rise with global warming. Full article

(This article belongs to the Special Issue Characteristics of Extreme Climate Events over China)

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