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Future increases in Arctic lightning and fire risk for permafrost carbon

Nature Climate Change volume 11, pages 404–410 (2021)Cite this article

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Abstract

Lightning is an indicator and a driver of climate change. Here, using satellite observations of lightning flash rate and ERA5 reanalysis, we find that the spatial pattern of summer lightning over northern circumpolar regions exhibits a strong positive relationship with the product of convective available potential energy (CAPE) and precipitation. Applying this relationship to Climate Model Intercomparison Project Phase 5 climate projections for a high-emissions scenario (RCP8.5) shows an increase in CAPE (86 ± 22%) and precipitation (17 ± 2%) in areas underlain by permafrost, causing summer lightning to increase by 112 ± 38% by the end of the century (2081–2100). Future flash rates at the northern treeline are comparable to current levels 480 km to the south in boreal forests. We hypothesize that lightning increases may induce a fire–vegetation feedback whereby more burning in Arctic tundra expedites the northward migration of boreal trees, with the potential to accelerate the positive feedback associated with permafrost soil carbon release.

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Fig. 1: Contemporary lightning flash rates across high-northern-latitude regions are positively correlated with the product of CAPE and Precip.
Fig. 2: Lightning flash rates in high-northern-latitude terrestrial ecosystems are projected to increase by 93 ± 27%, with a larger increase (112 ± 38%) in areas underlain by permafrost.
Fig. 3: By the end of the twenty-first century, projected lightning flash rates over Arctic tundra are similar to levels now detected over boreal forests south of the treeline.
Fig. 4: Future increases in lightning flash rate may initiate a feedback that amplifies the impacts of climate change in high-northern-latitude terrestrial ecosystems.

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Data availability

The LIS/OTD lightning data products are from the NASA Global Hydrology Resource Center website (https://lightning.nsstc.nasa.gov/data/data_lis-otd-climatology.html), the CMIP5 meteorological data are from the Earth System Grid Federation (https://esgf-node.llnl.gov/search/cmip5/) and the burned-area data are from the Global Fire Emissions Database (http://www.globalfiredata.org/), the Alaska Interagency Coordination Center (https://fire.ak.blm.gov) and the Canadian Wildland Fire Information System (http://cwfis.cfs.nrcan.gc.ca/). Other data supporting the findings of this study are available within the paper and its supplementary information files. Source data are provided with this paper.

Code availability

The code used for the lightning and burned area analysis is available from the corresponding author upon request.

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Acknowledgements

This work was supported by the US Department of Energy (DOE) Office of Science Biological and Environmental Research RUBISCO Science Focus Area (with funding to J.T.R, Z.A.M. and W.J.R.), the NGEE-Arctic project (with funding to Z.A.M. and W.J.R.) and NASA’s Interdisciplinary Science (IDS) and Carbon Monitoring System (CMS) programmes (with grants to J.T.R and Y.C.). D.M.R. was supported by the US DOE Atmospheric System Research (ASR), an Office of Science, Office of Biological and Environmental Research programme. Lawrence Berkeley National Laboratory is operated for the DOE by the University of California under contract no. DE-AC02-05CH11231. We thank the World Climate Research Programme Working Group on Coupled Modeling, responsible for CMIP, and we thank the climate modelling groups for generating their model outputs and making them available.

Author information

Author notes

  1. Jacob T. Seeley

    Present address: Harvard University Center for the Environment, Harvard University, Cambridge, MA, USA

Authors and Affiliations

  1. Department of Earth System Science, University of California, Irvine, CA, USA

    Yang Chen & James T. Randerson

  2. Department of Earth and Planetary Science, University of California, Berkeley, CA, USA

    David M. Romps & Jacob T. Seeley

  3. Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    David M. Romps, William J. Riley & Zelalem A. Mekonnen

  4. Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Sander Veraverbeke

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Contributions

Y.C. and J.T.R. designed the study. Y.C. led the research and performed the analyses described in the main text and supporting information. D.M.R. and J.T.S. derived the lightning index (CAPE × Precip) from meteorological variables archived from historical and RCP8.5 ESM simulations contributed to CMIP5. S.V. contributed to the development of the lightning model and to the conceptual model of a lightning-initiated dynamic vegetation feedback. W.J.R. and Z.A.M. contributed to the conceptual model of the dynamic vegetation feedback and to the discussion of the implications of a changing lightning regime for terrestrial ecosystems. All authors contributed to the writing and review of the manuscript.

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Correspondence to Yang Chen.

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The authors declare no competing interests.

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Peer review information Nature Climate Change thanks the anonymous reviewers for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Circumpolar observations of present-day lightning flash rate, tree cover fraction, permafrost soil carbon, and burned area.

a, lightning flash rate (# km−2 mo−1, from OTD, averaged over May-August of 1996-1999); b, tree cover fraction (%, based on MODIS observations in 2012); c, permafrost soil carbon at depth of 0-100 cm (kg C m−2, from NCSCDv2); and d, burned area (% yr−1, from GFED4s, averaged over 1996-2016) in high northern latitude regions (north of 55°N).

Source data

Extended Data Fig. 2 Circumpolar observations of meteorological parameters.

Maps of a, CAPE (J kg−1); b, precipitation (Precip, mm day−1); c, CAPE × Precip (W m−2); and d, surface air temperature (°C) in high northern latitude regions of 55°N, representing the mean of summers (May-August) during 1996-1999. All meteorological parameters are from the ERA5 global reanalysis dataset.

Source data

Extended Data Fig. 3 Scatter plot relationships and probability distribution functions for meteorological variables known to be important for lightning flash rate prediction.

The surface air temperature (T) is in °C, CAPE is in J kg−1, precipitation (Precip) is in mm day−1, and CAPE × Precip is in 10−3 W m−2. Each point represents a different spatial location (at a 1°×1° resolution) north of 55°N. Diagonal panels show the spatial probability distribution for each variable, created by taking the mean at each point during summers (May-August) of 1996-1999. All meteorological parameters are from the ERA5 global reanalysis dataset.

Source data

Extended Data Fig. 4 Future (2081-2100) to the present day (1986-2005) ratios of CAPE, precipitation, and lightning flash rate in Arctic tundra for different CMIP5 models.

The mean flash rate values calculated from 5 regression formula (see Supplementary Table 2) are shown for each CMIP5 model.

Source data

Extended Data Fig. 5 Sources of uncertainty for estimated lightning flash rates, burned area and carbon emissions.

The flash rates were averaged over the Arctic tundra region. The burned area and carbon emissions were averaged over the Arctic tundra region within 500 km of northern treeline as indicated in Fig. 3. Left panels show uncertainties due to the use of CAPE × Precipitation from the use of multiple CMIP5 model simulations. Right panels show uncertainties related to the use of statistical models relating flash rate and CAPE × Precipitation. SV and DV represents future burned area estimations using the ‘static vegetation’ and ‘dynamic vegetation’ approaches (see Methods and Supplementary Table 3 for detail). Note the burned area and carbon emissions have same data distribution but with different units and scales.

Source data

Extended Data Fig. 6 Present day and future estimates of total precipitation (TP) and convective precipitation (CP) as a function of distance from northern treeline.

a, TP and CP percent changes from present day to the future. b, TP and CP values for the present day and future. c, The fraction of TP change that is due to CP change. The orange shade indicates the Arctic tundra region 0-500 km north of treeline. All data are based on the ensemble means of 15 CMIP5 model simulations over 1986-2005 and 2081-2100.

Source data

Extended Data Fig. 7 Distributions of surface temperature, CAPE × Precip, and the ice water path as a function of distance north of treeline.

a, surface temperature (T2m), b, the product of CAPE and precipitation (CAPE × Precip) and c, the ice water path (IWP) were calculated during summers for a contemporary period (1986-2005) and a future period (2081-2100). The percent changes are relative to the mean values during the contemporary period. The orange shade indicates the Arctic tundra region 0-500 km north of treeline. All data are based on the ensemble means of 15 CMIP5 model simulations over 1986-2005 and 2081-2100.

Source data

Extended Data Fig. 8 Contemporary lightning and wildfire properties as a function of distance from northern treeline.

a, The ratio of burned area (BA) to lightning flash rate (FR). Black dashed line represents parameterized step function (‘static vegetation’). Purple dashed line shows the shifted step function used for future burned area estimation (‘dynamic vegetation’). b, Fire number and mean fire size in Alaska, as reported by Alaska Interagency Coordination Center for the period of 2000 to 2016. c, Fire number and mean fire size in Canada, as reported by Canadian Wildland Fire Information System during the same period. The orange shade denotes the Arctic tundra region that may be vulnerable to future changes in lightning, burned area, and vegetation dynamics (0-500 km north of treeline).

Source data

Extended Data Fig. 9 Vapor pressure deficit (VPD) and the difference between precipitation and evapotranspiration (P-E) as a function of distance from northern treeline.

The VPD and P-E values are derived from the ensemble mean meteorology of 15 CMIP5 model simulations over 1986-2005 and 2081-2100.

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Extended Data Fig. 10 Comparison of lightning flash rates measured by satellite and a surface network in Alaska during summers of 1996-1999.

a, Flash rate (# deg−1 mo−1) recorded by the Optical Transient Detector (OTD), b, Flash rate (# deg−1 mo−1) from the Alaskan Lightning Detection Network (ALDN), c, Spatial correlation between the flash rates from OTD and ALDN. Each dot represents the mean summer value in a 1°×1° grid cell in Alaska.

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Supplementary information

Supplementary Information

Supplementary Tables 1–3.

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Numerical data used to generate graphs in Extended Data Fig. 9.

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Numerical data used to generate graphs in Extended Data Fig. 10.

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Chen, Y., Romps, D.M., Seeley, J.T. et al. Future increases in Arctic lightning and fire risk for permafrost carbon. Nat. Clim. Chang. 11, 404–410 (2021). https://doi.org/10.1038/s41558-021-01011-y

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