Projection of Future Extreme Precipitation in China Based on the CMIP6 from a Machine Learning Perspective

Yan, Yilin; Wang, Hao; Li, Guoping; Jin, Xin; Ge, Fei; Zeng, Qiangyu; Ren, Xinyue; Tan, Linyin

doi:10.3390/rs14164033

Cited by 18 publications

(11 citation statements)

References 62 publications

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“…For example, Xu et al (2019) used precipitation simulation from CMIP5 to investigate future precipitation extremes in China and reported that RX1day and RX5day show an increasing trend for the twenty‐first century under different scenarios, but the increase of RX1day is more obvious than RX5day. Yan et al (2022) found that RX5day is projected to increase in most areas of China with the largest relative changes in northwestern areas by the end of the 21st century (2076–2100) compared with the historical period (1990–2014), which is similar to our results for RX1day.…”

Section: Discussionsupporting

confidence: 91%

Long‐term evolution and non‐stationary behaviours of daily and subdaily precipitation extremes in China

Liu,

Chen,

Xiong

et al. 2024

Intl Journal of Climatology

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The rise of extreme precipitation events has attracted wide attention throughout the world. However, the analysis of precipitation extremes is not sufficient in the short period of instrumental observation and it is complicated by their non‐stationary behaviours. As a period dominated by natural forcing, the last millennium is helpful for understanding long‐term changes in precipitation extremes. Therefore, this study aimed to (1) investigate changes in daily and subdaily precipitation extremes in China from the last millennium to the end of the twenty‐first century, (2) detect the non‐stationarity of precipitation extremes and (3) compare design storms by using stationary and non‐stationary distributions. The annual maximum 1‐day precipitation (RX1day) and annual maximum 3‐hour precipitation (RX3hour) are used to quantify variations of precipitation extremes. The results show that the trend of RX1day was insignificant for the Medieval Climate Anomaly (MCA, 950–1250) and the Little Ice Age (LIA, 1500–1800). For the historical period (1850–2014), the trend of RX1day and RX3hour was insignificant in most subregions. In addition, the differences for RX1day between the historical period and the MCA/LIA were mostly in the range of −5% to 5%. For the future period (2015–2100), RX1day and RX3hour are projected to increase in almost all land grids compared with the historical period, and they show greater increases in western China than eastern China. The non‐stationarity of RX1day and RX3hour is mainly found under the high‐emission scenario. Moreover, stationary generalized extreme value (GEV) distribution underestimates 50‐year return levels for RX1day and RX3hour in most areas compared with non‐stationary GEV distribution under the high‐emission scenario. Overall, this study suggests that daily and subdaily extreme precipitation will intensify over China in the future. For design storms, non‐stationary methods need to be used for risk management and engineering design under the high‐emission scenario.

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Section: Discussionsupporting

confidence: 91%

Long‐term evolution and non‐stationary behaviours of daily and subdaily precipitation extremes in China

Liu,

Chen,

Xiong

et al. 2024

Intl Journal of Climatology

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“…Locate FY-4A's cloud retrieval in the SWV coordinate system. For the SWV life stage with a specific time step, the cloud search results of all FY-4A pixels in the region are analyzed, and the cloud occurrence frequency (COF) of each type of cloud is calculated, as shown in Equation (1).…”

Section: Data Analysis Methodsmentioning

confidence: 99%

“…Meteorologists have long been focused on understanding the formation, development, and flood disasters caused by this weather phenomenon. In recent years, in the context of global warming [1], extreme precipitation events triggered by the SWV have become more frequent, resulting in significant human and economic losses [2]. For example, from 7 to 11 July 2013, an extreme precipitation event in northern Sichuan registered a total precipitation of 415.9 mm, impacting 15 townships and 42,571 individuals [3].…”

Section: Introductionmentioning

confidence: 99%

Case Study on the Evolution and Precipitation Characteristics of Southwest Vortex in China: Insights from FY-4A and GPM Observations

Xiang,

Wang,

et al. 2023

Remote Sensing

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This research investigates Southwest Vortex (SWV) events in China’s Sichuan Basin using Fengyun-4A (FY-4A) and Global Precipitation Mission (GPM) observations. We selected representative cloud systems and precipitation cases, divided into developing, mature, and dissipating stages. Detailed analysis revealed critical characteristics of precipitation cloud systems at each stage. Our findings reveal that (1) during the SWV’s developing and mature stages, a high concentration of water particles and ice crystals stimulates precipitation. In contrast, the dissipating stage is marked by fewer mixed-phase and ice particles, reducing precipitation area and intensity. (2) Near-surface precipitation in all stages is predominantly liquid, with a bright band of around 5.5 km. At the same time, stratiform precipitation is dominant in each life stage. Stratiform precipitation remains dominant throughout the life stages of the SWV, with localized convective activity evident in the developing and mature stages. (3) Mature stage particles, characterized by a configuration of 1.0–1.2 mm Dm and 31–35 dBNW (dBNW = 10log10NW), contribute significantly to near-surface precipitation. The Cloud Top Height (CTH) serves as an indicator of convective intensity and assists in characterizing raindrop concentration. These findings considerably enhance routine observations, advance our understanding of SWV events, and propose a novel approach for conducting refined observational experiments.

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“…China's coastal regions are thought to be sensitive and vulnerable to climate change, which could result in considerable losses from climate-related disasters because of the country's enormous population Yan et al, 2022b). Despite the substantial expected increase in precipitation in the coastal area of China, the Palmer Drought Severity Index is projected to indicate drier conditions.…”

Section: Precipitation Projection 361 Mean Annual Precipitation Changementioning

confidence: 99%

Trend Analysis and Projection of Climate Variables Using the LARS-WG Model in Coastal Areas of China

Disasa,

Yan,

Wang

et al. 2024

Preprint

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The rising air temperature and shifting precipitation patterns threaten crop production and water distribution worldwide. The coastal region of China, specifically the Huaibei and Shandong Plains, is recognized as one of the most vulnerable areas among those impacted due to the complex interplay of land, sea, and atmospheric dynamics. The study utilized traditional trend analysis methods (Mann-Kendall and Sen's Slope) along with an innovative polygon trend analysis (IPTA) to predict the baseline arithmetic mean and standard deviation of the monthly precipitation trend. Moreover, the latest version of the Long Ashton Research Station Weather Generator (LARS-WG 7) model was used to predict average mean monthly precipitation and maximum and minimum temperatures for two future times: midterm 2050 (2041–2060) and long-term 2080 (2071–2090). The performance of each GCM incorporated in LARS-WG was evaluated independently and compared to a multi-model ensemble. All of the meteorological stations that were analyzed using the MK method (except for Suzhou, Dangshan, and Mengcheng) showed a significant decreasing trend in the arithmetic mean of monthly precipitation in March. However, for the majority of the remaining months, the study indicated a non-significant decreasing trend. In contrast, the IPTA method demonstrated a significant decreasing trend in most months, highlighting its superior ability to detect hidden trends compared to the MK method. The projections showed that mean annual precipitation is likely to increase at all meteorological stations in the Huaibei Plains and Shandong Plains during two periods: 2050 (2041–2060) and 2080 (2071–2090). A maximum increase in average mean annual precipitation is projected at the highest emission scenario (ssp585) as compared to the medium (ssp245) and low emission (ssp126) scenarios, and at the long-term period 2080 (2071-2090) as compared to the mid-term period 2050 (2041-2060). The mean annual precipitation in the Shandong Plain is projected to increase by 10.4%, 14.5%, and 14.8% under the ssp126, ssp245, and ssp585 scenarios, respectively. Similarly, in the Huaibei Plain, the projected increases are 10.9%, 13.6%, and 15.1% under the ssp126, ssp245, and ssp585 scenarios, respectively. The anticipated increase in mean precipitation per decade is expected to be 2.0% (= 1.96 mm/decade) in the Huaibei Plain and 1.31% (= 0.63 mm/decade) in the Shandong Plain. Both maximum and minimum temperatures are projected to increase persistently across all meteorological stations during two time periods: 2050 (2041–2060) and 2080 (2071–2090) under three different SSPs (ssp126, ssp245, and ssp585). The long-term period 2080 (2071–2090) is projected to experience the highest increase in both maximum and minimum temperatures, surpassing the increases observed in the midterm period 2050 (2041–2060). Among the different SSPs, the greatest increase in both maximum and minimum temperature was projected under the highest forcing emission scenario, SSP 585. With a persistent increase in air temperature and precipitation patterns fluctuating under a future climate scenario in the coastal area of China, climate change can influence all aspects of life, especially water resource distribution and agricultural water management. This study provides valuable insight for water resources planners and agricultural experts in the coastal region of China, as this area is a very vulnerable area to climate change and is also the main staple food-producing area in China.

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Projection of Future Extreme Precipitation in China Based on the CMIP6 from a Machine Learning Perspective

Cited by 18 publications

References 62 publications

Long‐term evolution and non‐stationary behaviours of daily and subdaily precipitation extremes in China

Long‐term evolution and non‐stationary behaviours of daily and subdaily precipitation extremes in China

Case Study on the Evolution and Precipitation Characteristics of Southwest Vortex in China: Insights from FY-4A and GPM Observations

Trend Analysis and Projection of Climate Variables Using the LARS-WG Model in Coastal Areas of China

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