In recent years, extreme high temperature events occurred more frequently in Northern Africa (NA) posing significant impacts on ecological systems and socioeconomic development. However, the physical origin of these extreme high temperatures remains unexplored. To address this issue, Empirical Orthogonal Function (EOF) analysis technics is employed to investigate the key physical factors influencing the spatial patterns of extreme high temperature days (EHDs) over NA. Three major modes of EHDs (EOF1, EOF2 and EOF3) accounting for 43%, 11% and 8% of the total variance were identified in this study. EOF1 features uniform distribution associated with positive geopotential heights and anticyclonic flows, while EOF2 is characterized by a meridional dipole pattern. Using reanalysis datasets, these modes are further linked to ocean – land – atmosphere interactions to reveal underlying physical mechanism. EOF1 is influenced by tropical and subtropical positive SSTA associated by mid tropospheric heights which triggers heat wave transport and subsidence. This mode is also influenced by weakening of west African monsoon system which suppresses moisture transport towards NA. EOF2 is influenced by combination of tropical Indian ocean and western Pacific wave trains leading subsidence over NA. EOF3 captures more the transient or regional scale influences on EHDs due to it weak association with large-scale teleconnections. Generally, this study classifies the factors influencing summer patterns of EHDs over NA as 1) tropical and subtropical SST warming, 2) decaying of Monsoon circulation, and 3) Strengthened upper-level subsidence. Gaining an understanding of these processes is essential for improving climate prediction and setting strategies for early warning and mitigation of the impacts from extreme heat events.
References
[1]
African Development Bank (2018). African Economic Outlook 2018: North Africa. https://www.afdb.org/fileadmin/uploads/afdb/Documents/Publications/2018AEO/African-Economic-Outlook-2018-North-Africa.pdf
[2]
Alexander, L. V., Zhang, X., Peterson, T. C., Caesar, J., Gleason, B., Klein Tank, A. M. G., Haylock, M., Collins, D., Trewin, B., Rahimzadeh, F., Tagipour, A., Rupa Kumar, K., Revadekar, J., Griffiths, G., Vincent, L., Stephenson, D. B., Burn, J., Aguilar, E., Brunet, M., Vazquez‐Aguirre, J. L. et al. (2006). Global Observed Changes in Daily Climate Extremes of Temperature and Precipitation. Journal of Geophysical Research: Atmospheres, 111, D05109. https://doi.org/10.1029/2005jd006290
[3]
Biasutti, M. (2013). Forced Sahel Rainfall Trends in the CMIP5 Archive. Journal of Geophysical Research: Atmospheres, 118, 1613-1623. https://doi.org/10.1002/jgrd.50206
[4]
Budikova, D., Ford, T. W., & Ballinger, T. J. (2019). United States Heat Wave Frequency and Arctic Ocean Marginal Sea Ice Variability. Journal of Geophysical Research: Atmospheres, 124, 6247-6264. https://doi.org/10.1029/2018JD029365
[5]
Chakilu, G. G., Sándor, S., & Zoltán, T. (2023). The Dynamics of Hydrological Extremes under the Highest Emission Climate Change Scenario in the Headwater Catchments of the Upper Blue Nile Basin, Ethiopia. Water, 15, Article No. 358. https://doi.org/10.3390/w15020358
[6]
Chen, X., & Tung, K.-K. (2018). Global-Mean Surface Temperature Variability: Space-Time Perspective from Rotated EOFs. Climate Dynamics, 51, 1719-1732. https://doi.org/10.1007/s00382-017-3979-0
[7]
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Vitart, F. et al. (2011). The ERA‐Interim Reanalysis: Configuration and Performance of the Data Assimilation System. Quarterly Journal of the Royal Meteorological Society, 137, 553-597. https://doi.org/10.1002/qj.828
[8]
Dembélé, A., Ye, X., & Touré, A. (2018). Analysis of Land Surface Temperature Change Based on MODIS Data, Case Study: Inner Delta of Niger. https://doi.org/10.5194/nhess-2018-208
[9]
Deng, K., Yang, S., Ting, M., Zhao, P., & Wang, Z. (2019). Dominant Modes of China Summer Heat Waves Driven by Global Sea Surface Temperature and Atmospheric Internal Variability. Journal of Climate, 32, 3761-3775. https://doi.org/10.1175/JCLI-D-18-0256.1
[10]
Ding, Gao, H., & Li, W. (2018). Extreme High-Temperature Event in Southern China in 2016 and the Possible Role of Cross-Equatorial Flows. International Journal of Climatology, 38, 3579-3594.
[11]
Ding, Q. H., & Wang, B. (2005). Circumglobal Teleconnection in the Northern Hemisphere Summer. Journal of Climate, 18, 3483-3505. https://doi.org/10.1175/JCLI3473.1
[12]
Dosio, A., Mentaschi, L., Fischer, E. M., & Wyser, K. (2018). Extreme Heat Waves under 1.5 ˚C and 2 ˚C Global Warming. Environmental Research Letters, 13, Article ID: 054006. https://doi.org/10.1088/1748-9326/aab827
[13]
Fischer, E. M., & Schär, C. (2010). Consistent Geographical Patterns of Changes in High-Impact European Heatwaves. Nature Geoscience, 3, 398-403. https://doi.org/10.1038/ngeo866
[14]
Francis, J. A., & Vavrus, S. J. (2012). Evidence Linking Arctic Amplification to Extreme Weather in Mid-Latitudes. Geophysical Research Letters, 39, L06801. https://doi.org/10.1029/2012GL051000
[15]
Gao, M., Wang, B., Yang, J., & Dong, W. (2018). Are Peak Summer Sultry Heat Wave Days over the Yangtze-Huaihe River Basin Predictable? Journal of Climate, 31, 2185-2196. https://doi.org/10.1175/JCLI-D-17-0342.1
[16]
Giannini, A., Biasutti, M., Held, I. M., & Sobel, A. H. (2008). A Global Perspective on African Climate. Climatic Change, 90, 359-383. https://doi.org/10.1007/s10584-008-9396-y
[17]
Hannachi, A., Jolliffe, I. T., & Stephenson, D. B. (2007). Empirical Orthogonal Functions and Related Techniques in Atmospheric Science: A Review. International Journal of Climatology, 27, 1119-1152. https://doi.org/10.1002/joc.1499
[18]
Harr, B., Pu, B., & Jin, Q. (2024). The Emission, Transport, and Impacts of the Extreme Saharan Dust Storm of 2015. Atmospheric Chemistry and Physics, 24, 8625-8651. https://doi.org/10.5194/acp-24-8625-2024
[19]
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Thépaut, J. et al. (2020). The ERA5 Global Reanalysis. Quarterly Journal of the Royal Meteorological Society, 146, 1999-2049. https://doi.org/10.1002/qj.3803
[20]
Hong, H., Sun, J., & Wang, H. (2022). Variations in Summer Extreme High-Temperature Events over Northern Asia and the Possible Mechanisms. Journal of Climate, 35, 335-357. https://doi.org/10.1175/JCLI-D-21-0043.1
[21]
Huang, G., & Yan, Z. (1999). The East Asian Summer Monsoon Circulation Anomaly Index and Its Interannual Variations. Chinese Science Bulletin, 44, 1325-1329. https://doi.org/10.1007/BF02885855
[22]
Hurrell, J. W., Kushnir, Y., Ottersen, G., & Visbeck, M. (2003). An Overview of the North Atlantic Oscillation. The North Atlantic Oscillation: Climatic Significance and Environmental Impact (Vol. 134). Geophys. Monogr.
[23]
Intergovernmental Panel on Climate Change (IPCC) (2023). Climate Change 2021—The Physical Science Basis. Cambridge University Press. https://doi.org/10.1017/9781009157896
[24]
Jolliffe, I. T., & Cadima, J. (2016). Principal Component Analysis: A Review and Recent Developments. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374, Article ID: 20150202. https://doi.org/10.1098/rsta.2015.0202
[25]
Kanamitsu, M., Ebisuzaki, W., Woollen, J., Yang, S. K., Hnilo, J. J., Fiorino, M., & Potter, G. L. (2002). NCEP-DOE AMIP-II Reanalysis (R-2). Bulletin of the American Meteorological Society, 83, 1631-1644.
[26]
Largeron, Y., Guichard, F., Roehrig, R., Couvreux, F., & Barbier, J. (2020). The April 2010 North African Heatwave: When the Water Vapor Greenhouse Effect Drives Nighttime Temperatures. Climate Dynamics, 54, 3879-3905. https://doi.org/10.1007/s00382-020-05204-7
[27]
Lau, N.-C., & Nath, M. J. (2012). A Model Study of Heat Waves over North America: Meteorological Aspects and Projections for the Twenty-First Century. Journal of Climate, 25, 4761-4784. https://doi.org/10.1175/JCLI-D-11-00575.1
[28]
Lelieveld, J., Proestos, Y., Hadjinicolaou, P., Tanarhte, M., Tyrlis, E., & Zittis, G. (2016). Strongly Increasing Heat Extremes in the Middle East and North Africa (MENA) in the 21st Century. Climatic Change, 137, 245-260. https://doi.org/10.1007/s10584-016-1665-6
[29]
Lien, V. S., Raj, R. P., & Chatterjee, S. (2024). Surface and Bottom Marine Heatwave Characteristics in the Barents Sea: A Model Study. State of the Planet, 4, 1-11. https://doi.org/10.5194/sp-4-osr8-8-2024
[30]
Lienert, F., & Doblas‐Reyes, F. J. (2013). Decadal Prediction of Interannual Tropical and North Pacific Sea Surface Temperature. Journal of Geophysical Research: Atmospheres, 118, 5913-5922. https://doi.org/10.1002/jgrd.50469
[31]
Long, Y., Li, J., Zhu, Z., & Zhang, J. (2022). Predictability of the Anomaly Pattern of Summer Extreme High-Temperature Days over Southern China. Climate Dynamics, 59, 1027-1041. https://doi.org/10.1007/s00382-022-06170-y
[32]
Lorenz, E. N. (1956). Empirical Orthogonal Functions and Statistical Weather Prediction. MIT Department of Meteorology Statistical Forecasting Project Scientific Rep.
[33]
Meehl, G. A., Zwiers, F., Evans, J., Knutson, T., Mearns, L., & Whetton, P. (2000). Trends in Extreme Weather and Climate Events: Issues Related to Modeling Extremes in Projections of Future Climate Change. Bulletin of the American Meteorological Society, 81, 427-436. https://doi.org/10.1175/1520-0477(2000)081<0427:TIEWAC>2.3.CO;2
[34]
North, G. R., Bell, T. L., Cahalan, R. F., & Moeng, F. J. (1982). Sampling Errors in the Estimation of Empirical Orthogonal Functions. Monthly Weather Review, 110, 699-706. https://doi.org/10.1175/1520-0493(1982)110<0699:SEITEO>2.0.CO;2
[35]
Patricola, C. M., & Cook, K. H. (2010). Northern African Climate at the End of the Twenty-First Century: An Integrated Application of Regional and Global Climate Models. Climate Dynamics, 35, 193-212. https://doi.org/10.1007/s00382-009-0623-7
[36]
Pavithra, N. L., Ashalatha, K. V., Megha, J., Manjunath, G. R., & Hanabar, S. (2019). Food Grain Production Index Using Principal Component Analysis in Karnataka State. International Journal of Current Microbiology and Applied Sciences, 8, 3138-3143. https://doi.org/10.20546/ijcmas.2019.801.335
[37]
Screen, J. A., & Simmonds, I. (2014). Amplified Mid-Latitude Planetary Waves Favour Particular Regional Weather Extremes. Nature Climate Change, 4, 704-709. https://doi.org/10.1038/nclimate2271
[38]
Sultan, B., & Janicot, S. (2003). The West African Monsoon Dynamics. Part II: The “Preonset” and “Onset” of the Summer Monsoon. Journal of Climate, 16, 3407-3427. https://doi.org/10.1175/1520-0442(2003)016<3407:TWAMDP>2.0.CO;2
[39]
Sun, J. Q., & Wang, H. J. (2012). Changes of the Connection between the Summer North Atlantic Oscillation and the East Asian Summer Rainfall. Journal of Geophysical Research: Atmospheres, 117, D08110. https://doi.org/10.1029/2012JD017482
[40]
Sun, Y., Zhang, X., Zwiers, F. W., Song, L., Wan, H., Hu, T., Yin, H., & Ren, G. (2014). Rapid Increase in the Risk of Extreme Summer Heat in Eastern China. Nature Climate Change, 4, 1082-1085. https://doi.org/10.1038/nclimate2410
[41]
Taye, M. T., Ntegeka, V., Ogiramoi, N. P., & Willems, P. (2011). Assessment of Climate Change Impact on Hydrological Extremes in Two Source Regions of the Nile River Basin. Hydrology and Earth System Sciences, 15, 209-222. https://doi.org/10.5194/hess-15-209-2011
[42]
Ting, M., Kushnir, Y., Seager, R., & Li, C. (2011). Robust Features of Atlantic Multi-Decadal Variability and Its Climate Impacts. Geophysical Research Letters, 38, L17705. https://doi.org/10.1029/2011GL048712
[43]
Wang, W., Zhou, W., Li, X., Wang, X., & Wang, D. (2016). Synoptic-Scale Characteristics and Atmospheric Controls of Summer Heat Waves in China. Climate Dynamics, 46, 2923-2941. https://doi.org/10.1007/s00382-015-2741-8
[44]
WMO (2024). State of the Climate in Africa 2023 (WMO-No. 1360). https://library.wmo.int/idurl/4/69000
[45]
Wold, S., Esbensen, K., & Geladi, P. (1987). Principal Component Analysis. Chemometrics and Intelligent Laboratory Systems, 2, 37-52. https://doi.org/10.1016/0169-7439(87)80084-9
[46]
Wu, M., Zhou, T., Li, C., Li, H., Chen, X., Wu, B., Zhang, W., & Zhang, L. (2021). A Very Likely Weakening of Pacific Walker Circulation in Constrained Near-Future Projections. Nature Communications, 12, Article No. 6502. https://doi.org/10.1038/s41467-021-26693-y
[47]
Zhang, R., Sun, C., Zhu, J., Zhang, R., & Li, W. (2020). Increased European Heat Waves in Recent Decades in Response to Shrinking Arctic Sea Ice and Eurasian Snow Cover. NPJ Climate and Atmospheric Science, 3, Article No. 7. https://doi.org/10.1038/s41612-020-0110-8
[48]
Zhu, B., Sun, B., & Wang, H. (2020). Dominant Modes of Interannual Variability of Extreme High-Temperature Events in Eastern China during Summer and Associated Mechanisms. International Journal of Climatology, 40, 841-857. https://doi.org/10.1002/joc.6242