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2021 North American heatwave amplified by climate change-driven nonlinear interactions

Abstract

Heat conditions in North America in summer 2021 exceeded previous heatwaves by margins many would have considered impossible under current climate conditions. Associated severe impacts highlight the need for understanding the physical drivers of the heatwave and relations to climate change, to improve the projection and prediction of future extreme heat risks. Here, we find that slow- and fast-moving components of the atmospheric circulation interacted, along with regional soil moisture deficiency, to trigger a 5-sigma heat event. Its severity was amplified ~40% by nonlinear interactions between its drivers, probably driven in part by land–atmosphere feedbacks catalysed by long-term regional warming and soil drying. Since the 1950s, global warming has transformed the peak daily regional temperature anomaly of the event from virtually impossible to a presently estimated ~200-yearly occurrence. Its likelihood is projected to increase rapidly with further global warming, possibly becoming a 10-yearly occurrence in a climate 2 °C warmer than the pre-industrial period, which may be reached by 2050.

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Fig. 1: Timing and location of the PNW heatwave and its associated atmospheric dynamical and land surface conditions.
Fig. 2: Nonlinear interactions of common drivers and their long-term trends.
Fig. 3: Modelled PNW monthly temperature variability and extreme event return periods, with versus without soil moisture interaction.
Fig. 4: 2021 heatwave likelihood estimates over recent decades and under future emissions pathways.

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Data availability

All ERA5 output data used in this study are available from ECMWF at https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels. All CAM5_GOGA output used in this study is available at https://doi.org/10.5281/zenodo.5800726. CMIP6 multimodel mean warming levels are available at https://doi.org/10.5281/zenodo.4600695.

Code availability

All figures were produced using Python v.3.6 (https://www.python.org/downloads/release/python-360/). All code needed to reproduce the main figures is available at https://doi.org/10.5281/zenodo.7153416 (ref. 69).

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Acknowledgements

We are thankful to Y. Wu, R. Horton, D. Singh, C. Raymond, C. Rogers and R. Seager for valuable feedback on this work. We thank D. Lee for configuring, running and making output available from CAM5–GOGA. Support for this work was provided by NSF-AGS-1934358 (S.B., K.K. and M.T.) and NOAA NA20OAR4310379 (M.T.).

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M.T. initiated and supervised the project. S.B. and K.K. analysed data with input from M.T. S.B. generated figures and wrote the first draft of the manuscript with input from K.K. and M.T. All authors discussed and edited the manuscript.

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Correspondence to Samuel Bartusek.

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Extended data

Extended Data Fig. 1 Atmospheric dynamics during June 2021 leading to the anomalous geopotential heights associated with the PNW heatwave.

See Text S1 for further discussion. (af): 500hPa Geopotential height (filled contours), 300hPa meridional wind speed (red and blue contours), and outgoing longwave radiation (OLR; green and dark brown contours) anomalies averaged over 9-day periods centred on the annotated date. For clarity, the meridional wind field is only shown poleward of 20°N and the OLR field is only shown within 90°E–100°W (roughly the Pacific Ocean). For example, (a) shows the 9-day mean surrounding 06/05, when geopotential heights were high in the PNW accompanying a heatwave, with centres of low and high geopotential height extending westward over the Pacific forming a tripole. By 06/10 (b)) the tripole had expanded longitudinally, placing negative geopotential height over the PNW, and begun to constitute part of a wavenumber-4 pattern in meridional wind and geopotential height encircling the midlatitudes. Over 06/10–06/20 (c–e)) this wavenumber-4 pattern moved slightly northward and shifted phase longitudinally, eventually placing high geopotential height over the PNW. Throughout the last two weeks of June (d–f)) the wavenumber-4 pattern persisted and amplified, causing extreme temperatures and dry soils in central Europe, Siberia, and the PNW, and was reinforced by a Rossby wavetrain emanating from the subtropical western Pacific.

Extended Data Fig. 2 PNW land–atmosphere anomalies during the 2021 heatwave.

Mean conditions over the whole 9-day heatwave period (06/25–07/03; left column), its first half (06/25–06/29; middle column), and its second half (06/29–07/03; right column), for 2 m temperature (T2M) (top row), T2M anomalies (second row), soil moisture (SM) anomalies (third row), and evaporative fraction (EF) anomalies (bottom row). EF is calculated from daily-mean latent heat flux (LHF) and sensible heat flux (SHF) as LHF/(SHF + LHF). Many of the regions of hottest (absolute) T2M and hottest T2M, driest SM, and lowest EF (high SHF vs. total HF) anomalies during this heatwave overlapped, particularly in the center of the region: across northern Oregon, eastern Washington, northern Idaho, and central southern British Columbia (the Interior Plateau). However, some of the largest T2M anomalies were associated with high EF (high LHF vs. total HF) anomalies instead—mostly in the Coastal and Cascade mountains on the British Columbia coast and the Cariboo and Monashee mountains between British Columbia and Alberta. This pattern is very consistent with climatological daily correlation between EF and T2M anomalies (see Extended Data Fig. 6): areas where EF and T2M are anticorrelated (both typically and during this event) tend to be warmer, non-mountain areas with relatively low soil moisture and more arid and/or Mediterranean continental climates (that is, across much of eastern Oregon and Washington (the Columbia Plateau), Idaho, and British Columbia’s Interior Plateau. Therefore, overall, throughout the heatwave (06/25–07/03), the spatial anticorrelation between EF and T2M anomalies was very weak, reflecting the diversity of land types and land–atmosphere coupling regimes across the large region (yielding r = –0.04). However, where T2M was both anomalously and climatologically high, EF and T2M were more tightly anticorrelated. Masking to retain only land regions under the 850hPa level, the spatial correlation was –0.24, with p < 0.0001 (significance tested non-parametrically, accounting for spatial autocorrelation).

Extended Data Fig. 3 2-metre temperature anomaly, tendency, and latent versus sensible heat flux partitioning.

Two-day averages throughout 6/24–7/1, focusing on the heating phase of the event. The second-to-last row identifies points where the two-day average upward latent heat flux (LHF) was diminished and sensible heat flux (SHF) was enhanced (exhibiting negative and positive anomalies relative to 1981–2010, respectively, which tended to show strong persistence throughout the season). The last row further subselects points where the temperature tendency was also positive.

Extended Data Fig. 4 SW–warming relationship stratified by flux partitioning.

Points are daily averages for each land gridcell in the PNW region, over the heatwave period (06/25–07/02), with net SW (downward) anomaly plotted against 2-metre temperature anomaly. Orange dots represent daily averages at each point within the evolving mask shown in the second-to-last row of Extended Data Fig. 3, that is where (upward) sensible heat flux (SHF) was enhanced and latent heat flux (LHF) was diminished. Blue dots show all other land gridcells in the region. (KDE) contours are shown for each group of gridcells, considering only points with net anomalous shortwave radiation > 0, so that points not relevant to heating do not bias the KDE characterization.

Extended Data Fig. 5 Temperature tendency budget analysis at 850 hPa.

See Text S2 for further discussion. Top row, left: Temperature (at 850 hPa and 2 metres) and horizontal and vertical wind (at 850 hPa) anomalies averaged during the 2021 PNW heatwave (06/24–07/03). The green box, blue box, and yellow contour outline the subregions highlighted in the right column (the green box shows the region focused on in the main results). Bottom two rows, left: Spatial patterns of contributions from various (grouped) terms in the 850 hPa temperature tendency budget, averaged throughout the heatwave warming phase (06/24–06/29). The residual ‘diabatic’ term is calculated as the total tendency minus the sum of all non-diabatic terms, and indicates processes not accounted for by the non-diabatic terms that may in part be attributed to land–atmosphere processes. Fields are smoothed with a running 4-gridcell (~1°) window in both directions. Right column: Temporal evolution of grouped terms in the budget throughout 06/23–07/01, averaged within the green, yellow, and blue outlined areas (in top row of maps). Solid lines show the total heating, horizontal heat advection, the sum of vertical heat advection and adiabatic expansion/compression, and the residual term. Additionally, the dashed translucent red line shows the residual term only where the long-term daily correlation between latent heat flux (LHF) and soil moisture (SM) exceeds 0.2 (see Extended Data Fig. 6), that is, where land–atmosphere interactions may be more likely to cause positive feedbacks on temperature extremes. 2-metre and 850hPa temperature anomalies in each sub-region are shown on the right axes.

Extended Data Fig. 6 Climatologies and trends of PNW temperature variability and land–atmosphere quantities.

Top row: 1981–2010 June–July climatologies (top panels) and 1979–2020 linear trends (bottom panels) of 2 m temperature (T2M), T2M variability (within-year standard deviation and skewness of daily anomalies), soil moisture (SM), and evaporative fraction (EF, calculated from daily latent heat flux [LHF] and sensible heat flux [SHF] as LHF/[LHF + SHF]). Bottom row: Climatologies and trends of four metrics of land–atmosphere coupling: the first three (correlations between LHF and SHF, LHF and SM, and EF and SM) represent the terrestrial component, while EF and T2M correlation represents the total feedback pathway. Correlation climatologies are created by correlating two variables (with June–July 1979–2020 trends removed) against each other throughout all June–July 1981–2010 days. Trends are between correlations within June–July of individual years (1979–2020). While SM and T2M are nearly everywhere anticorrelated, these metrics show where soil moisture deficit may causally affect T2M: LHF/SHF anticorrelation, LHF/SM correlation, EF/SM correlation, and EF/T2M anticorrelation indicate moisture-limited (versus energy-limited) regimes with potentially stronger land–atmosphere coupling, typical of transitional climate zones. If evapotranspiration is moisture-limited, under heating EF may decrease (SHF’s partition of flux increases), allowing for positive land–atmosphere feedbacks by further increasing T2M, decreasing SM, increasing SHF and decreasing LHF. Climatologically, such areas extend from the drier interior central West to the Columbia Plateau in eastern Washington and into interior British Columbia (bottom row, top panels). Trends indicate that much of the PNW has undergone strengthening in at least the terrestrial component of land–atmosphere coupling—most notably where soil moisture is climatologically moderate as opposed to extremely low, including much of BC’s Interior Plateau, much of the Cascade Range region (including near Portland and Seattle) and to the east of the Columbia Plateau. In some of these areas, T2M itself has become more coupled to EF, potentially signifying strengthened feedbacks—but such trends have not conclusively emerged overall. The spatial pattern of strengthening land–atmosphere coupling corresponds relatively well with warming, drying, and decreasing EF, and in some places with increasing T2M variability (areas of increasing T2M standard deviation and skewness correspond better to land–atmosphere correlation trends than to SM or EF trends alone).

Extended Data Fig. 7 Fit and validation for non-stationary location, stationary-scale historical GEV fit.

Same as Fig. 4 but showing results from a GEV distribution fit with stationary-scale parameter (location parameter is still non-stationary). Bootstrapped 95% confidence intervals are shaded as in Fig. 4.

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Bartusek, S., Kornhuber, K. & Ting, M. 2021 North American heatwave amplified by climate change-driven nonlinear interactions. Nat. Clim. Chang. 12, 1143–1150 (2022). https://doi.org/10.1038/s41558-022-01520-4

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