Strong winds drive grassland fires in China

Wang, Zhou; Huang, Ru; Yao, Qichao; Zong, Xie; Tian, Xin; Zheng, Ben

doi:10.1088/1748-9326/aca921

Cited by 4 publications

(3 citation statements)

References 41 publications

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“…The changes in surface wind speed (SWS) have significant impacts on the ecological environment, social life, industrial and agricultural development. Strong winds are easily to trigger grass land fires and dust events over arid and semi-arid regions (Kurosaki et al 2011, Abram et al 2021, Wang et al 2023. Low SWS can readily lead to air pollution events in places with high emissions, compromising human health (Wang et al 2018, Han et al 2020.…”

Section: Introductionmentioning

confidence: 99%

Quantify uncertainty in historical simulation and future projection of surface wind speed over global land and ocean

Zhang,

Wang

2024

Environ. Res. Lett.

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Quantifying uncertainty in simulations of surface wind speed (SWS) has significant implications for its applications. Here, we examine the SWS changes from the 6th Coupled Model Intercomparison Project (CMIP6) model outputs, and analyzed the simulation uncertainties in CMIP6 both in the historical period and future projections. The results show that the both trend and interannual variability of SWS are underestimated in the CMIP6. The SWS over most of the Northern Hemisphere will reduce by 4-6% under the high emission scenario in the last 21st Century, whereas it will increase by 6-10% over South America and Southeastern Pacific. Over land, the majority of projection uncertainties is dominated by model uncertainty, followed by the internal variability and scenario uncertainty. Over ocean, the simulation uncertainty is greatly influenced by model uncertainty and internal variability, with the scenario uncertainty accounting for around 20% of total simulation uncertainty in the late 21st century.

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Section: Introductionmentioning

confidence: 99%

Quantify uncertainty in historical simulation and future projection of surface wind speed over global land and ocean

Zhang,

Wang

2024

Environ. Res. Lett.

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“…Among them, floating dust and blowing dust are weak dust weather, while dust storms and severe dust storms are strong dust weather [7,8]. Grassland fires and strong dust weather, as sudden-onset disaster phenomena, have substantial impacts on grassland ecosystems, biogeochemical cycles, human life and property, social stability, and economic development due to their high hazard level, wide range, and forecast difficulty [9][10][11][12][13]. Notably, the effects of grassland fires and dust events may be superimposed or mutually reinforcing, leading to additional severe cascading disasters.…”

Section: Introductionmentioning

confidence: 99%

“…For example, the occurrence of grassland fires destroys vegetation cover and leaves the ground bare [14,15], which facilitates the occurrence of dust events [16][17][18]. Furthermore, dust events are typically accompanied by strong winds, which could exacerbate fire formation and spread the smoke and sparks generated by the fires over greater distances, triggering new fires [13]. With the ensuing global climate change, extreme weather events are becoming more frequent [19,20].…”

Section: Introductionmentioning

confidence: 99%

Effect of Grassland Fires on Dust Storms in Dornod Aimag, Mongolia

Wen,

Yong,

Bao

et al. 2023

Remote Sensing

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Grassland fires and dust weather in Mongolia can trigger major cascading disasters. Grassland fires from autumn to the following spring can indirectly affect dust weather occurrence in the spring by affecting land surface vegetation cover. In this paper, we selected the aimag (province) of Dornod, Mongolia, a typical temperate grassland area, as the study area. The study aims to (1) analyze the spatiotemporal patterns of grassland fire and dust weather in the past 22 years, as well as the effect of grassland fire on dust weather and to (2) explore in depth the mechanisms of the effects of grassland fire on dust weather. To achieve these goals, we utilize high-resolution satellite burned-area data and Synop dust data. In general, grassland fire and dust weather occurrence clearly varied spatiotemporally across the study area. Grassland fires are typically more frequent in spring and autumn, and dust weather is mainly concentrated in spring. Cumulative grassland fires (both days and burned area) from autumn to the following spring affected the spring cumulative dust weather days significantly, especially the spring cumulative dust storm days. Analysis of the mechanism of the effect of grassland fire on dust storms showed that abundant summer precipitation resulted in higher vegetation cover and more accumulated fuel from autumn to April of the following spring. Consequently, the cumulative grassland fire days were higher, and the cumulative burned area was larger during the period, leading to a significant increase in cumulative dust storm days in May of the spring. In Mongolia, grassland fires are often caused by human factors. The findings of the present study could facilitate the crafting of measures to prevent and reduce grassland fires and indirectly minimize dust weather frequency to protect the ecological environment and promote sustainable development.

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Analysis of the Grassland Fires Effect on Dust Weather in Mongolia Based on Satellite-Derived Data

Wen,

Yong,

Bao

et al. 2023

Preprint

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As major natural disasters in grassland areas, fires and dust events seriously threaten human safety, property, and animal husbandry. Furthermore, these phenomena may be mutually reinforcing, which can lead to more severe cascading disasters. However, few studies have been on the mechanisms of grassland fire and dust events disaster chain. Therefore, we selected Dornod aimag (province), a typical temperate grassland, as the study area and analyzed the spatiotemporal variation patterns of grassland fires and dust weather, as well as the effect of grassland fires on dust weather based on MCD64A1 Burnt Area data and SYNOP dust data. The mechanism of grassland fires on dust weather was further investigated using the MOD13A3 vegetation index product and ERA5 wind speed, wind direction, and precipitation data. The results revealed that grassland fires and dust weather varied spatially across the study area. Furthermore, grassland fires occurred mainly in spring (April to May), summer (June), and autumn (October), while dust weather mainly occurred in spring (March to May). Moreover, autumn, winter, and spring cumulative grassland fires (both days and area) substantially affected the spring total dust weather days and dust storm days, particularly the spring cumulative dust storm days. Additionally, higher precipitation in the summer of 2014 resulted in higher vegetation coverage and more fuel in the autumn and winter of 2014, and even in the spring of 2015. As a result, the cumulative grassland fire days was higher, and the area was larger from September 2014 to April 2015, leading to a considerable increase in the cumulative dust storm days in May 2015. This study has important implications for disaster prevention and mitigation, ecological and environmental protection, and sustainable development in grasslands.

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Strong winds drive grassland fires in China

Cited by 4 publications

References 41 publications

Quantify uncertainty in historical simulation and future projection of surface wind speed over global land and ocean

Quantify uncertainty in historical simulation and future projection of surface wind speed over global land and ocean

Effect of Grassland Fires on Dust Storms in Dornod Aimag, Mongolia

Analysis of the Grassland Fires Effect on Dust Weather in Mongolia Based on Satellite-Derived Data

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