Significant Association Between Arctic Oscillation and Winter Wildfires in Southern China

Meng Meng; Daoyi Gong; Yunfei Lan; Qichao Yao; Lamei Shi; Zhou Wang

doi:10.1007/s13753-024-00589-z

Volume 15 Issue 5

Oct. 2024

Turn off MathJax

Article Contents

Article Navigation > International Journal of Disaster Risk Science > 2024 > 15(5): 820-830

Meng Meng, Daoyi Gong, Yunfei Lan, Qichao Yao, Lamei Shi, Zhou Wang. Significant Association Between Arctic Oscillation and Winter Wildfires in Southern China[J]. International Journal of Disaster Risk Science, 2024, 15(5): 820-830. doi: 10.1007/s13753-024-00589-z

Citation:

Meng Meng, Daoyi Gong, Yunfei Lan, Qichao Yao, Lamei Shi, Zhou Wang. Significant Association Between Arctic Oscillation and Winter Wildfires in Southern China[J]. International Journal of Disaster Risk Science, 2024, 15(5): 820-830. doi: 10.1007/s13753-024-00589-z

Citation:

PDF

Significant Association Between Arctic Oscillation and Winter Wildfires in Southern China

doi: 10.1007/s13753-024-00589-z

Meng Meng¹,
Daoyi Gong^2,3,4,5,
Yunfei Lan^2,3,4,5,
Qichao Yao^{1
,
,},
Lamei Shi¹,
Zhou Wang¹

1. National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing, 100085, China;
2. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China;
3. Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing, 100875, China;
4. Institute of Disaster Risk Science, Beijing Normal University, Beijing, 100875, China;
5. Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China

Funds:

This study was supported by the National Key Research and Development Program for Global Change and Adaptation (Grant No. 2020YFA0608201).

Accepted Date: 2024-10-10

Available Online: 2024-12-07

Publish Date: 2024-10-28

Abstract

Abstract

The recent increase of regional wildfire occurrences has been associated with climate change. In this study, we investigated the association between the February to March wildfire points and burned area in the southern region of China (20°N-30°N and 105°E-115°E) and the simultaneous Arctic Oscillation (AO) index during 2001-2022 and 2001-2020, respectively. After removing the El Niño-Southern Oscillation and Indian Ocean Dipole signals, time series of the regional mean fire points and burned area over the study area is significantly correlated with the AO index at -0.37 and -0.47, significant at the 0.1 level. Precipitation significantly affects wildfire variations. The positive AO could trigger a southeastward Rossby wave train and induce anomalous cyclone activity approximately located in the area encompassed by 15°N-27°N and 85°E-100°E. This outcome could help to enhance the southern branch trough and results in positive precipitation anomalies in southern China. This increasing moisture is conductive to reducing wildfire risks, vice versa. Our results are potentially useful for strengthening the understanding of the mechanisms of wildfire occurrences in southern China.
- Arctic Oscillation,
- Climate change,
- ENSO,
- Southern China wildfires

FullText(HTML)

References(49)

References

[1]	Bowd, E.J., S.C. Banks, A. Bissett, T.W. May, and D.B. Lindenmayer. 2021. Direct and indirect disturbance impacts in forests. Ecology Letters 24(6): 1225-1236.
[2]	Chen, F., Z.F. Fan, S.K. Niu, and J.M. Zheng. 2014. The influence of precipitation and consecutive dry days on burned areas in Yunnan Province, southwestern China. Advances in Meteorology 2014(3-4): 748923.
[3]	Chen, A.P., R.Y. Tang, J.F. Mao, C. Yue, X.R. Li, M.D. Gao, X.Y. Shi, and M.Z. Jin et al. 2020. Spatiotemporal dynamics of ecosystem fires and biomass burning-induced carbon emissions in China over the past two decades. Geography and Sustainability 1(1): 47-58.
[4]	Chen, J.P., Z.P. Wen, R.G. Wu, Z.S. Chen, and P. Zhao. 2014. Interdecadal changes in the relationship between southern China winter-spring precipitation and ENSO. Climate Dynamics 43: 1327-1338.
[5]	Cui, L.L., C.J. Luo, C.L. Yao, Z.B. Zou, G.L. Wu, Q. Li, and X.L. Wang. 2022. The influence of climate change on forest fires in Yunnan Province, southwest China detected by GRACE satellites. Remote Sensing 14(3): 712.
[6]	Di Virgilio, G., J.P. Evans, S.A.P. Blake, M. Armstrong, A.J. Dowdy, J. Sharples, and R. McRae. 2019. Climate change increases the potential for extreme wildfires. Geophysical Research Letters 46(14): 8517-8526.
[7]	Dong, X.Y., and J.S. Fu. 2015. Understanding interannual variations of biomass burning from peninsular southeast Asia, part II: Variability and different influences in lower and higher atmosphere levels. Atmospheric Environment 115: 9-18.
[8]	Fang, K.Y., Q.C. Yao, Z.T. Guo, B. Zheng, J.H. Du, F.Z. Qi, P. Yan, and J. Li et al. 2021. ENSO modulates wildfire activity in China. Nature Communications 12: 1764.
[9]	Flannigan, M., A.S. Cantin, W.J. de Groot, M. Wotton, A. Newbery, and L.M. Gowman. 2013. Global wildland fire season severity in the 21st century. Forest Ecology and Management 294: 54-61.
[10]	Gao, M.-N., J. Yang, D.-Y. Gong, and S.-J. Kim. 2014. Unstable relationship between spring Arctic Oscillation and east Asian summer monsoon. International Journal of Climatology 34(7): 2522-2528.
[11]	Gong, D.-Y., Y.Q. Gao, D. Guo, R. Mao, J. Yang, M. Hu, and M.N. Gao. 2013. Interannual linkage between Arctic/North Atlantic Oscillation and tropical Indian Ocean precipitation during boreal winter. Climate Dynamics 42(3-4): 1007-1027.
[12]	Gong, D.-Y., Y.-Q. Gao, M. Hu, and D. Guo. 2013. Association of Indian Ocean ITCZ variations with the Arctic Oscillation during boreal winter. Atmospheric and Oceanic Science Letters 6(5): 300-305.
[13]	Gu, Y.S., D.M. Pearsall, S.C. Xie, and J.X. Yu. 2008. Vegetation and fire history of a Chinese site in southern tropical Xishuangbanna derived from phytolith and charcoal records from Holocene sediments. Journal of Biogeography 35(2): 325-341.
[14]	Guan, Z.Y., and T. Yamagata. 2003. The unusual summer of 1994 in East Asia: IOD teleconnections. Geophysical Research Letters. https://doi.org/10.1029/2002GL016831.
[15]	Guo, M., Q.C. Yao, H.Q. Suo, X.X. Xu, J. Li, H.S. He, S. Yin, and J.N. Li. 2023. The importance degree of weather elements in driving wildfire occurrence in mainland China. Ecological Indicators 148: 110152.
[16]	Harris, I., T.J. Osborn, P. Jones, and D. Lister. 2020. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Scientific Data 7: 109.
[17]	Hersbach, H., B. Bell, P. Berrisford, S. Hirahara, A. Horányi, J. Muñoz-Sabater, J. Nicolas, and C. Peubey et al. 2020. The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society 146(730): 1999-2049.
[18]	Holsinger, L., S.A. Parks, and C. Miller. 2016. Weather, fuels, and topography impede wildland fire spread in western US landscapes. Forest Ecology and Management 380: 59-69.
[19]	Jones, M.W., J.T. Abatzoglou, S. Veraverbeke, N. Andela, G. Lasslop, M. Forkel, A.J.P. Smith, and C. Burton et al. 2022. Global and regional trends and drivers of fire under climate change. Reviews of Geophysics 60(3): e2020RG000726.
[20]	Li, X.Z., and W. Zhou. 2016. Modulation of the interannual variation of the India-Burma trough on the winter moisture supply over southwest China. Climate Dynamics 46: 147-158.
[21]	Li, X.Z., Y.Q.D. Chen, and W. Zhou. 2017. Response of winter moisture circulation to the India-Burma trough and its modulation by the South Asian waveguide. Journal of Climate 30(4): 1197-1210.
[22]	Li, P., Z.M. Feng, C.W. Xiao, K. Boudmyxay, and Y. Liu. 2018. Detecting and mapping annual newly-burned plots (NBP) of swiddening using historical Landsat data in montane mainland Southeast Asia (MMSEA) during 1988-2016. Journal of Geographical Sciences 28(9): 1307-1328.
[23]	Li, J.-X., G. Liu, R.G. Wu, H.-L. Ren, H.-M. Wang, X. Mao, and X.-C. Wei. 2022. Narrow and wide India-Burma trough-like circulations: Their different impacts on precipitation over southern China. Geoscience Letters 9: 1-12.
[24]	Lizundia-Loiola, J., G. Otón, R. Ramo, and E. Chuvieco. 2020. A spatio-temporal active-fire clustering approach for global burned area mapping at 250 m from MODIS data. Remote Sensing of Environment 236: 111493.
[25]	Luo, Y.Y., J. Shi, X.D. An, and C. Li. 2022. The combined impact of subtropical wave train and polar-Eurasian teleconnection on the extreme cold event over North China in January 2021. Climate Dynamics 60: 3339-3352.
[26]	Lydersen, J.M., B.M. Collins, M.L. Brooks, J.R. Matchett, K.L. Shive, N.A. Povak, V.R. Kane, and D.F. Smith. 2017. Evidence of fuels management and fire weather influencing fire severity in an extreme fire event. Ecological Applications 27: 2013-2030.
[27]	Mao, R., D.-Y. Gong, J. Yang, and J.-D. Bao. 2011. Linkage between the Arctic Oscillation and winter extreme precipitation over central-southern China. Climate Research 50(2): 187-201.
[28]	Pan, Y., Y. Zhang, and S.T. Li. 2022. Assessment of CMIP models in simulating the relationship between wintertime atmospheric circulation in the Northern Hemisphere and the winter-spring temperature over the Tibetan Plateau. Journal of the Meteorological Sciences 42(4): 440-456.
[29]	Pausas, J.G., and J.E. Keeley. 2021. Wildfires and global change. Frontiers in Ecology and the Environment 19(7): 387-395.
[30]	Peterson, D.A., M.D. Fromm, R.H.D. Mcrae, J.R. Campbell, E.J. Hyer, G. Taha, C.P. Camacho, and G.P. Kablick et al. 2021. Australia’s Black Summer pyrocumulonimbus super outbreak reveals potential for increasingly extreme stratospheric smoke events. npj Climate and Atmospheric Science 4(1): 38.
[31]	Qiu, Y., W.J. Cai, X.G. Guo, and B. Ng. 2014. The asymmetric influence of the positive and negative IOD events on China’s rainfall. Scientific Reports 4: 4943.
[32]	Reddy, M.S., O. Boucher, Y. Balkanski, and M. Schulz. 2005. Aerosol optical depths and direct radiative perturbations by species and source type. Geophysical Research Letters 32(12): L12803.
[33]	Suo, M.Q., Y.H. Ding, and Z.Y. Wang. 2008. Relationship between Rossby wave propagation in southern branch of westerlies and the formation of the southern branch trough in wintertime. Journal of Applied Meteorological Science 19(6): 731-740.
[34]	Takaya, K., and H. Nakamura. 2001. A formulation of a phase-independent wave-activity flux for stationary and migratory quasigeostrophic eddies on a zonally varying basic flow. Journal of the Atmospheric Sciences 58(6): 608-627.
[35]	Thompson, D.W.J., and J.M. Wallace. 1998. The Arctic Oscillation signature in the wintertime geopotential height and temperature fields. Geophysical Research Letters 25: 1297-1300.
[36]	Wang, T.M., S. Yang, Z.P. Wen, R.G. Wu, and P. Zhao. 2011. Variations of the winter India-Burma trough and their links to climate anomalies over southern and eastern Asia. Journal of Geophysical Research: Atmospheres 116(D23): D23118.
[37]	Wu, X.F., and J.F. Mao. 2016. Interdecadal modulation of ENSO-related spring rainfall over South China by the Pacific Decadal Oscillation. Climate Dynamics 47: 3203-3220.
[38]	Xu, Y., and U. Nadine. 2018. Fire air pollution reduces global terrestrial productivity. Nature Communications 9: 5413.
[39]	Xu, K., C.W. Zhu, and W.Q. Wang. 2016. The cooperative impacts of the El Niño-Southern Oscillation and the Indian Ocean Dipole on the interannual variability of autumn rainfall in China. International Journal of Climatology 36: 1987-1999.
[40]	Yang, J., D.Y. Gong, W.S. Wang, M. Hu, and R. Mao. 2012. Extreme drought event of 2009/2010 over southwestern China. Meteorology and Atmospheric Physics 115(3-4): 173-184.
[41]	Ying, L.X., H.J. Cheng, Z.H. Shen, P.A. Guan, C.F. Luo, and X.Z. Peng. 2021. Relative humidity and agricultural activities dominate wildfire ignitions in Yunnan, southwest China: Patterns, thresholds, and implications. Agricultural and Forest Meteorology 307: 108540.
[42]	Ying, L.X., J. Han, Y.S. Du, and Z.H. Shen. 2018. Forest fire characteristics in China: Spatial patterns and determinants with thresholds. Forest Ecology and Management 424: 345-354.
[43]	Yu, P.F., S.M. Davis, O.B. Toon, R.W. Portmann, C.G. Bardeen, J.E. Barnes, H. Telg, and C. Maloney et al. 2021. Persistent stratospheric warming due to 2019-2020 Australian wildfire smoke. Geophysical Research Letters 48: e2021GL092609.
[44]	Yu, Y., J.F. Mao, S.D. Wullschleger, A.P. Chen, X.Y. Shi, Y.P. Wang, F.M. Hoffman, and Y.L. Zhang et al. 2022. Machine learning-based observation-constrained projections reveal elevated global socioeconomic risks from wildfire. Nature Communications 13: 1250.
[45]	Zhang, L., F. Sielmann, K. Fraedrich, X.H. Zhu, and X.F. Zhi. 2015. Variability of winter extreme precipitation in Southeast China: Contributions of SST anomalies. Climate Dynamics 45: 2557-2570.
[46]	Zhang, R.H., W.S. Tian, X. He, K. Qie, D. Liu, and H.Y. Tian. 2021. Enhanced influence of ENSO on winter precipitation over southern China in recent decades. Journal of Climate 34: 7983-7994.
[47]	Zhang, Y., W. Zhou, and M.Y.T. Leung. 2019. Phase relationship between summer and winter monsoons over the South China Sea: Indian Ocean and ENSO forcing. Climate Dynamics 52: 5229-5248.
[48]	Zhang, Y., W. Zhou, X. Wang, X. Wang, R.H. Zhang, Y.N. Li, and J.P. Gan. 2022. IOD, ENSO, and seasonal precipitation variation over eastern China. Atmospheric Research 270: 106042.
[49]	Zhou, Y.W., W.P. Liao, J. Yang, X.F. Huang, and C.H. Chen. 2021. Based on MODIS fire pixel location data to characterize the biomass burning and air pollutants emissions in northern and southern China. Acta Scientiae Circumstantiae 41(9): 3696-3708.