Climate Dynamics Preceding Summer Forest Fires in California and the Extreme Case of 2018

Tess W. P. Jacobson aLamont-Doherty Earth Observatory, Palisades, New York
bDepartment of Earth and Environmental Sciences, Columbia University, New York, New York

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Richard Seager aLamont-Doherty Earth Observatory, Palisades, New York

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A. Park Williams cDepartment of Geography, University of California, Los Angeles, Los Angeles, California

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Naomi Henderson aLamont-Doherty Earth Observatory, Palisades, New York

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Abstract

Recent record-breaking wildfire seasons in California prompt an investigation into the climate patterns that typically precede anomalous summer burned forest area. Using burned-area data from the U.S. Forest Service’s Monitoring Trends in Burn Severity (MTBS) product and climate data from the fifth major global reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ERA5) over 1984–2018, relationships between the interannual variability of antecedent climate anomalies and July California burned area are spatially and temporally characterized. Lag correlations show that antecedent high vapor pressure deficit (VPD), high temperatures, frequent extreme high temperature days, low precipitation, high subsidence, high geopotential height, low soil moisture, and low snowpack and snowmelt anomalies all correlate significantly with July California burned area as far back as the January before the fire season. Seasonal regression maps indicate that a global midlatitude atmospheric wave train in late winter is associated with anomalous July California burned area. July 2018, a year with especially high burned area, was to some extent consistent with the general patterns revealed by the regressions: low winter precipitation and high spring VPD preceded the extreme burned area. However, geopotential height anomaly patterns were distinct from those in the regressions. Extreme July heat likely contributed to the extent of the fires ignited that month, even though extreme July temperatures do not historically significantly correlate with July burned area. While the 2018 antecedent climate conditions were typical of a high-burned-area year, they were not extreme, demonstrating the likely limits of statistical prediction of extreme fire seasons and the need for individual case studies of extreme years.

Significance Statement

The purpose of this study is to identify the local and global climate patterns in the preceding seasons that influence how the burned summer forest area in California varies year-to-year. We find that a dry atmosphere, high temperatures, dry soils, less snowpack, low precipitation, subsiding air, and high pressure centered west of California all correlate significantly with large summer burned area as far back as the preceding January. These climate anomalies occur as part of a hemispheric scale pattern with weak connections to the tropical Pacific Ocean. We also describe the climate anomalies preceding the extreme and record-breaking burned-area year of 2018, and how these compared with the more general patterns found. These results give important insight into how well and how early it might be possible to predict the severity of an upcoming summer wildfire season in California.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Tess W. P. Jacobson, tessj@ldeo.columbia.edu

Abstract

Recent record-breaking wildfire seasons in California prompt an investigation into the climate patterns that typically precede anomalous summer burned forest area. Using burned-area data from the U.S. Forest Service’s Monitoring Trends in Burn Severity (MTBS) product and climate data from the fifth major global reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ERA5) over 1984–2018, relationships between the interannual variability of antecedent climate anomalies and July California burned area are spatially and temporally characterized. Lag correlations show that antecedent high vapor pressure deficit (VPD), high temperatures, frequent extreme high temperature days, low precipitation, high subsidence, high geopotential height, low soil moisture, and low snowpack and snowmelt anomalies all correlate significantly with July California burned area as far back as the January before the fire season. Seasonal regression maps indicate that a global midlatitude atmospheric wave train in late winter is associated with anomalous July California burned area. July 2018, a year with especially high burned area, was to some extent consistent with the general patterns revealed by the regressions: low winter precipitation and high spring VPD preceded the extreme burned area. However, geopotential height anomaly patterns were distinct from those in the regressions. Extreme July heat likely contributed to the extent of the fires ignited that month, even though extreme July temperatures do not historically significantly correlate with July burned area. While the 2018 antecedent climate conditions were typical of a high-burned-area year, they were not extreme, demonstrating the likely limits of statistical prediction of extreme fire seasons and the need for individual case studies of extreme years.

Significance Statement

The purpose of this study is to identify the local and global climate patterns in the preceding seasons that influence how the burned summer forest area in California varies year-to-year. We find that a dry atmosphere, high temperatures, dry soils, less snowpack, low precipitation, subsiding air, and high pressure centered west of California all correlate significantly with large summer burned area as far back as the preceding January. These climate anomalies occur as part of a hemispheric scale pattern with weak connections to the tropical Pacific Ocean. We also describe the climate anomalies preceding the extreme and record-breaking burned-area year of 2018, and how these compared with the more general patterns found. These results give important insight into how well and how early it might be possible to predict the severity of an upcoming summer wildfire season in California.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Tess W. P. Jacobson, tessj@ldeo.columbia.edu
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