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Spatio-temporal Patterns between ENSO and Weather-related Power Outages in the Continental United States

Long Huo, Xin Chen, Kaiwen Li, Fengying Cai, Jürgen Kurths

Abstract

El Niño-Southern Oscillation (ENSO) exhibits significant impacts on the frequency of extreme weather events and its socio-economic implications prevail on a global scale. However, a fundamental gap still exists in understanding the relationship between the ENSO and weather-related power outages in the continental United States. Through 24-year (2000-2023) composite and statistical analysis, our study reveals that higher power outage numbers (PONs) are observed from the developing winter to the decaying summer of La Niña phases. In particular, during the decaying spring, high La Niña intensity favors the occurrences of power outage over the west coast and east of the United States, by modulating the frequency of extreme precipitations and heatwaves. Furthermore, projected increasing heatwaves from the Coupled Model Intercomparison Project Phase 6 (CMIP6) indicate that spring-time PONs over the eastern United States occur about 11 times higher for the mid-term future (2041-2060) and almost 26 times higher for the long-term future (2081-2100), compared with 2000-2023. Our study provides a strong recommendation for building a more climate-resilient power system.

Spatio-temporal Patterns between ENSO and Weather-related Power Outages in the Continental United States

Abstract

El Niño-Southern Oscillation (ENSO) exhibits significant impacts on the frequency of extreme weather events and its socio-economic implications prevail on a global scale. However, a fundamental gap still exists in understanding the relationship between the ENSO and weather-related power outages in the continental United States. Through 24-year (2000-2023) composite and statistical analysis, our study reveals that higher power outage numbers (PONs) are observed from the developing winter to the decaying summer of La Niña phases. In particular, during the decaying spring, high La Niña intensity favors the occurrences of power outage over the west coast and east of the United States, by modulating the frequency of extreme precipitations and heatwaves. Furthermore, projected increasing heatwaves from the Coupled Model Intercomparison Project Phase 6 (CMIP6) indicate that spring-time PONs over the eastern United States occur about 11 times higher for the mid-term future (2041-2060) and almost 26 times higher for the long-term future (2081-2100), compared with 2000-2023. Our study provides a strong recommendation for building a more climate-resilient power system.
Paper Structure (9 sections, 6 equations, 4 figures)

This paper contains 9 sections, 6 equations, 4 figures.

Figures (4)

  • Figure 1: Statistical relationship between the EI Niño-Southern Oscillation (ENSO) and power outages. (a) Climate regions of the U.S. There are ten climate regions. Note that two climate regions (NR and SW) are not analyzed in this study due to limited samples of weather-related power outages ($<$ 20 from 2000 to 2023). (b) Composite seasonal average power outage numbers (PONs) of all U.S. during La Niña, EI Niño, and neural-ENSO phases. (c) Cross-correlations between the La Niña intensities based on different ENSO monitoring indices (MEI, SOI, Niño 3.4, Niño 3, and Niño 4) and the regional PONs for each season. The samples with significantly (non-significantly, $p>0.05$) cross-correlations are indicated by black (gray) dots. In (B) and (C), the acronyms MAM, JJA, SON, and DJF refer to spring (March, April, May), summer (June, July, August), autumn (September, October, November), and winter (December, January, February), respectively. The ENSO phase associated with a power outage in spring, summer, autumn, or winter is determined by a $\pm$0.5 threshold of the MEI index 3, 6, 9 or 0 months (with ± 1-month tolerance interval) before the power outage occurs, $i.e.$, if the MEI $<$ -0.5, it indicates the La Niña phase; $>$ +0.5, it's the El Niño phase; otherwise, it's the neutral-ENSO phase.
  • Figure 2: Spatio-temporal patterns of weather-related power outages in spring. (a) Spatial distribution of maximum cross-correlations (CCs) between MEI-based La Niña ($MEI^{-}$) intensity and regional PONs. (b) Scatter plot of $MEI$ and regional PONs. The dots in blue, red, and gray represent samples during La Niña, EI Niño, and neural-ENSO phases. As shown by the blue solid line, the linear regression is significantly (p $\le$ 0.05) negative for $MEI$$<$ -0.5. The subplot in (b) shows the average PONs during La Niña, EI Niño, and neural-ENSO phases. (c) Time delay CCs between $MEI^{-}$ and PONs of all U.S. The positive (negative) time delays stand for La Niña (PON) predates PON (La Niña). In (d-f), the first row represents maximum CCs between $MEI^{-}$ and frequencies of cold snap $D_{cold}$, heatwave $D_{heat}$, and extreme precipitation $D_{precip}$. The second row is maximum CCs between $D_{cold}$, $D_{heat}$, or $D_{precip}$ and PONs. The shaded areas indicate areas with significant CCs (p $<$ 0.05).
  • Figure 3: Spatio-temporal patterns of weather-related power outages in summer (a-d) and winter (e-h). Spatial distribution of maximum cross-correlations (CCs) between MEI-based La Niña ($MEI^{-}$) intensity and regional PONs in summer (a) and maximum CCs between Niño 3-based La Niña (Niño 3$^{-}$) intensity and regional PONs in winter (e). (b) Scatter plot of $MEI$ and regional PONs in summer. (f) Scatter plot of Niño 3 and regional PONs in winter. The dots in blue, red, and gray represent grouped samples in La Niña, EI Niño, and neural-ENSO phases, respectively. Subplots in (b) and (f) show the average PONs during La Niña, EI Niño, and neural-ENSO phases. (c) Time delay CCs between PONs of all U.S. and $MEI^{-}$ during summer. (g) Time delay CCs between PONs of all U.S. and Niño 3$^{-}$ during winter. The positive (negative) time delays stand for La Niña (PON) occurs before PON (La Niña). (d) Maximum CCs between $MEI^{-}$ and heatwave frequencies $D_{heat}$ (top) and maximum CCs between heatwave frequencies and PONs in summer (down). (h) Maximum CCs between Niño 3$^{-}$ and extreme precipitation frequencies $D_{precip}$ (top) and maximum CCs between extreme precipitation frequencies and PONs in winter (down). The shaded areas denote areas with significant CCs (p $<$ 0.05).
  • Figure 4: Historical and future projected springtime PONs based on the changes in heatwave frequencies. The amplified ratio of (a) heatwave frequencies and (b) PONs during the period 2000-2010 to the period 2011-2023. In (b), no weather-related power outage occurs in the climate region in black (S1) during 2000-2010. (c) Time series of observed and projected heatwave frequencies and (d) observed and estimated PONs in the spring from 2000 to 2100. SSP 2-4.5 and SSP 5-8.5 denote future moderate and high emission scenarios, respectively. The gray areas denote the upper and lower boundaries of historical heatwave frequencies and corresponding PONs during 2000-2014. From 2015 to 2100, the areas in green and red stand for the upper and lower boundaries of heatwave frequencies and corresponding PONs among the 18 CMIP6 GCMs under the SSP 2-4.5 and SSP 5-8.5 scenario, respectively. The lines in black, green, and red indicate the historical, SSP 2-4.5 scenario average, and SSP 5-8.5 scenario average heatwave frequencies and PONs. The blue lines represent the observed average heatwave frequencies and PONs. (e-f) Estimated amplified ratio of PONs under SSP 2-4.5 scenario. (g-h) Estimated amplified ratio of PONs under SSP 5-8.5 scenario. Color bars and text boxes in (e-h) indicate the amplified ratio in PONs and heatwave frequencies. Compared with historical (2000-2023) average PONs, (e) and (g) show the average amplified ratio in PONs for the mid-term future (2041-2060), (f) and (h) for the long-term future (2081-2100).