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Non-analog increases to air, surface, and belowground temperature extreme events due to climate change

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Abstract

Air temperatures (Ta) are rising in a changing climate, increasing extreme temperature events. Examining how Ta increases are influencing extreme temperatures at the soil surface and belowground in the soil profile can refine our understanding of the ecological consequences of rising temperatures. In this paper, we validate surface and soil temperature (Ts: 0–100-cm depth) simulations in the SOILWAT2 model for 29 locations comprising 5 ecosystem types in the central and western USA. We determine the temperature characteristics of these locations from 1980 to 2015, and explore simulations of Ta and Ts change over 2030–2065 and 2065–2100 time periods using General Circulation Model (GCM) projections and the RCP 8.5 emissions scenario. We define temperature extremes using a nonstationary peak over threshold method, quantified from standard deviations above the mean (0-σ: an event \(>\sim \) 51% of extreme events; 2-\(\sigma :>\sim 98\%\)). Our primary objective is to contrast the magnitude (∘C) and frequency of occurrence of extreme temperature events between the twentieth and twenty-first century. We project that temperatures will increase substantially in the twenty-first century. Extreme Ta events will experience the largest increases by magnitude, and extreme Ts events will experience the largest increases by proportion. On average, 2-σ extreme Ts events will increase by 3.4 ∘C in 2030–2065 and by 5.3 ∘C in 2065–2100. Increases in extreme Ts events will often exceed + 10 ∘C at 0–20 cm by 2065–2100, and at 0–100 cm will often exceed 5.0 standard deviations above 1980–2015 values. 2-σ extreme Ts events will increase from 0.9 events per decade in 1980–2015 to 23 events in 2030–2065 and 38 events in 2065–2100. By 2065–2100, the majority of months will experience extreme events that co-occur at 0–100 cm, which did not occur in 1980–2015. These projections illustrate the non-analog temperature increases that ecosystems will experience in the twenty-first century as a result of climate change.

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Funding

Portions of this study were funded by a grant from the USDA Forest Service, Western Wildland Environmental Threat Assessment Center.

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Authors and Affiliations

  1. School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV, USA

    M. D. Petrie

  2. US Geological Survey, Southwest Biological Science Center, Flagstaff, AZ, USA

    J. B. Bradford, D. R. Schlaepfer & C. M. Andrews

  3. School of Forestry and Environmental Studies, Yale University, New Haven, CT, USA

    W. K. Lauenroth & D. R. Schlaepfer

  4. Center for Adaptable Western Landscapes, Northern Arizona University, Flagstaff, AZ, USA

    D. R. Schlaepfer

  5. Pacific Northwest Research Station, USDA Forest Service, Corvallis, OR, USA

    D. M. Bell

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  1. M. D. Petrie
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  4. D. R. Schlaepfer
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  5. C. M. Andrews
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Appendix

Appendix

We used the peak over threshold (POT) technique of Coelho et al. (2008) to calculate monthly extreme temperature thresholds from daily values of Ta and Ts. This analysis is conducted for a timeseries of each month individually (e.g., all days in January from 1980 to 2015). We calculated the monthly extreme temperature threshold using the following steps:

  1. Step 1.

    Calculate the 5-year floating mean from daily values. Using the 5-year floating mean results in an analysis window that is 4 years shorter than the time period length. For example, 1980–2015 has a floating mean for 1982–2013.

  2. Step 2.

    Rank the daily values in each month (January, 1983, for example) that are above the corresponding floating mean temperature value from highest to lowest (x = a vector of ranked daily temperature values).

  3. Step 3.

    Multiply the number of daily values in x by 0.05 (Obs = number of observations in x multiplied by 0.05).

  4. Step 4.

    If Obs < 1.0, there is no extreme threshold value for the corresponding month, and therefore no extreme event.

  5. Step 5.

    If Obs ≥ 1.0, the extreme threshold value for the corresponding month is the Obs+ 1th value in x. This value is assigned as a monthly extreme event.

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Petrie, M.D., Bradford, J.B., Lauenroth, W.K. et al. Non-analog increases to air, surface, and belowground temperature extreme events due to climate change. Climatic Change 163, 2233–2256 (2020). https://doi.org/10.1007/s10584-020-02944-7

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  • DOI: https://doi.org/10.1007/s10584-020-02944-7

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