1. Introduction
Major wildfires in the western United States have increased in acreage, societal impacts, and economic costs during the past several decades (e.g., Dennison et al. 2014; Abatzoglou and Williams 2016; Jones 2017; Parks and Abatzoglou 2020), with many of the nation’s largest and most impactful fires occurring in California (Littell et al. 2009; Nauslar et al. 2018; Addison and Oommen 2020; Brewer and Clements 2020). Previous research has described the effects of slowly varying climatic predictors on fire statistics across large western U.S. ecoregions (Marlon et al. 2012; Abatzoglou and Kolden 2013; Abatzoglou and Williams 2016; Keeley and Syphard 2017; Williams et al. 2019; Parks and Abatzoglou 2020; Brey et al. 2021; Abatzoglou et al. 2021a). However, the role of spatially and temporally variable weather, especially dry conditions and strong near-surface winds, in fostering wildfire at fire outset or during periods of rapid fire growth is increasingly evident from work concerning California fires (Pagni 1993; Keeley et al. 2009; Abatzoglou et al. 2018; Coen et al. 2018; Keeley and Syphard 2019; Williams et al. 2019; Khorshidi et al. 2020; McClung and Mass 2020; Dong et al. 2021). The goal of this work is to provide a better understanding of the relationship between observed California fire with the spatially and temporally variable regional meteorology while accounting for California’s major surface fuels.
California’s climate, expanding human development, and frequently dry surface fuels interact to make the state a favorable location for wildfire occurrence (Pagni 1993; Skinner and Chang 1996; Field and Jensen 2005; Hammer et al. 2007; Moritz et al. 2010; Coen et al. 2018; Radeloff et al. 2018; Syphard et al. 2019; McClung and Mass 2020). California typically experiences temperate, moist winters (Beck et al. 2018) that facilitate the annual growth of fast-growing savanna vegetation (defined as the continuum from grassland and chaparral to woodland1 as in the Global Fire Emissions Database, version 4.1, GFED4s, described in van der Werf et al. 2017). In contrast, California’s summers are generally hot and dry, rapidly desiccating savanna fuels and more slowly drying forest environments (Beck et al. 2018). Anthropogenic land use changes, such as urban development in wildland areas, enhance fire-related ignitions and associated loss from wildfire (Syphard et al. 2019). Human fire ignition has increased dramatically in many regions of the United States including California, lengthening the fire season, and is now more prevalent than natural ignition in most areas of the nation (Balch et al. 2017). Due to their proximity to urban areas, California’s savanna regions are more frequently human-ignited than forests, which are more often ignited by lightning. Fire exclusion practices dating back to the late 1800s have contributed to the increased frequency, intensity (defined in terms of energy released), and severity (defined in terms of ecological consequence) of California wildfires. Such exclusion has made California ecosystems, which historically experienced frequent low to moderate severity fire, more susceptible to ignition, fire spread, and more severe wildfire (Schoennagel et al. 2004; Collins et al. 2011; Marlon et al. 2012; Rossi and Kuusela 2019). Furthermore, the replacement of native vegetation by flammable invasive species has enhanced the vulnerability of California’s savanna regions to wildfire (Keeley et al. 2011). Finally, at the interface between savanna and forest ecosystems, fires may ignite in savanna and spread to forest (Bond and Midgley 1995; Syphard and Keeley 2015; Mass and Ovens 2020).
During the past decade, wind-driven wildfires have caused numerous fatalities and substantial economic loss in central and northern California. The 2017 Tubbs Fire (the most damaging of the Wine Country Fires), the 2018 Camp Fire, and the 2020 North Complex Fires led to 122 deaths. The Tubbs Fire, the Camp Fire, and the 1970 Laguna Fire were initiated by failing electrical infrastructure during high winds, which also produced rapid fire spread (Keeley and Zedler 2009; Mass and Ovens 2019, 2020). The Camp Fire was the costliest insured environmental loss of 2018 globally at $12,500,000,000 (U.S. dollars), exceeding the cost of the 2017 Wine Country Fires the year before (Associated Press 2018; Löw 2019). The 2020 fire season led to the first recorded “megafire” in California history, as the wind-driven August Complex Fire burned more than one million acres (Kaur 2020). Except for the 1970 Laguna Fire, the abovementioned fires were considered diablo wind fires, associated with strong northeasterly winds over northern California (Werth et al. 2016; McClung and Mass 2020).
Major wind-driven fires in southern California are often associated with strong, dry northeasterly Santa Ana winds (e.g., Moritz et al. 2010). Examples of wildfires resulting from Santa Ana winds include the 1889 fire season, the 1970 Laguna Fire, several fires during the 2003 and 2007 fire seasons, and the 2017 Thomas Fire (Mensing et al. 1999; Keeley and Fotheringham 2003; Keeley et al. 2004, 2009; Keeley and Zedler 2009; Addison and Oommen 2020). The 1889 fires were associated with strong winds and large burned areas not matched until the past decade (Keeley et al. 2004). The 2003 Cedar Fire was the largest on record at the time and was a wind-driven event (Mensing et al. 1999; Keeley and Fotheringham 2003; Keeley et al. 2004). In 2007, seven lives were lost in large southern California wildfires associated with Santa Ana winds that produced $1.8 billion in property loss (Karter 2008; Keeley et al. 2009). The December 2017 Thomas Fire, the largest fire at the time of occurrence, was associated with strong, dry winds and resulted in nearly two-dozen deaths and approximately $207 million in damage (Addison and Oommen 2020).
Both strong winds and dry conditions (low relative humidity, large vapor pressure deficit) contribute to California wildfires. Dry conditions reduce the fuel moisture content of vegetation and thus increase its flammability (Chandler et al. 1983; Agee 1993; Westerling et al. 2004; Liu et al. 2021; Smith et al. 2018). At the peak of the fire season, the fuel moisture content (percentage of water in a plant) of even live timber can dip below the threshold “moisture of extinction,” below which a flame may be sustained on a plant (Chandler et al. 1983; Agee 1993). The moisture content of dead fuels is controlled by surrounding environmental conditions (Finney 1998; Matthews 2013). Dead fuels are classified by the time required for fuel moisture content to reach two-thirds of the equilibrium value relative to the surrounding environment. This time lag is dependent on the dead fuel’s diameter2: 1-h fuels are under ¼ in., 10-h fuels are between ¼ and 1 in., 100-h fuels are between 1 and 3 in., and 1000-h fuels are between 3 and 8 in. in diameter. Grasses behave as dead fuels once cured, a desiccating process that occurs seasonally during an herbaceous plant’s lifetime (Scott and Burgan 2005). Once cured, rainfall will not cause annual grasses to green up again; cured perennial grasses may grow but the fire potential across the fuel bed would remain low (Duff et al. 2019). Moisture from rain or dew can reduce grass flammability; however, this reduction in fire potential only lasts a few hours under sufficiently dry conditions (Bradstock et al. 2012).
Wind influences fire spread rate by both advecting superheated gas and spotting, in which strong, turbulent winds loft firebrands ahead of the flame front, initiating new fires (Koo et al. 2010; Fernandez-Pello 2017). Wind may also facilitate the drying of fuel or lead to fire ignition, such as with failing electrical infrastructure or when trees fall on powerlines (e.g., McClung and Mass 2020). Wind and humidity are often not independent, especially in the presence of topography where strong, dry downslope flow can occur. The peak of the fire season in California encompasses late summer and fall, a particularly dangerous time since it follows the extended California dry season and is often a period of strong, dry, downslope winds associated with building high pressure over the Intermountain West resulting from the cooling of the continental interior.
Prior research has suggested that combining dryness and wind speed can provide useful wildfire guidance (e.g., Sharples et al. 2009a,b). For example, the hot-dry-windy (HDW) index, which combines wind speed and vapor pressure deficit (VPD), enables skillful prediction of fire danger at short time lags (Srock et al. 2018). VPD is used rather than relative humidity (RH) because VPD is better related to the evaporation that can occur at a certain temperature, especially in vegetation (Johnston 1919; Anderson 1936; Seager et al. 2015; Srock et al. 2018; Williams et al. 2019; Parks and Abatzoglou 2020). One drawback of HDW is that the combination of VPD and wind speed does not inform about their individual contributions to the criterion, since high values of HDW may be due to high winds, large VPD, or both. Other fire indices combine dryness and winds, such as the burning index (BI), which combines a spread component dependent on wind speed and an energy release component (ERC) related to the available potential energy in the fuels, which is dependent on drying conditions (Heinsch et al. 2017). Red flag warnings, perhaps the most widely known fire danger index, depend on the relative humidity and wind speed associated with past fires, with thresholds adjusted for different regions (Murdoch and Gitro 2010).
Although the area burned in California is dominated by savanna/shrubland landscapes, extensive regions of the state are forested (Keeley and Syphard 2017; Schwartz and Syphard 2021). The wildfire characteristics of savanna and forest fuels can differ in important ways. Savanna land cover, including grasses, bushes, and small vegetation, dries more rapidly and is more easily ignited than forest. Savanna fire intensity is characterized by the high energy release potential of its fuels and may foster particularly fast-moving wildfires (Scott and Burgan 2005). Timber fires have the potential for higher emissions; however, it is more difficult to burn live timber than savanna and particularly difficult to achieve tree mortality because of the relatively thick bark of trees, generally necessitating damage to the tree canopy to initiate tree death (Butler and Dickinson 2010; Lawes et al. 2011).
Fire emissions of combustible vegetation, such as total carbon emissions, provide a quantification of fire extent and severity (Xie et al. 2020) and relate to ecosystem function (Loudermilk et al. 2013), the global climate (Mouillot and Field 2005), and human health (Johnston et al. 2012; McClure and Jaffe 2018). Fires with greater spread (burned area), severity (e.g., combustion completeness), and fuel density generally result in higher emissions due to burning more material (van der Werf et al. 2017). Wildfire emissions may have impacts far beyond their local sources; for example, the majority of the smoke in the eastern and central United States is due to fires in the western United States (Burke et al. 2021) and carbon emissions from fire affect the global carbon budget (Mouillot and Field 2005). The emissions datasets used in this paper are not measured directly but are derived from emissions models based on burned area and fuels (section 2). Although wind and VPD are not included directly in the emissions calculation we expect greater VPD and winds to mechanistically increase emissions by increasing fire spread.
Previous studies have compared charcoal records or post-fire burned area to monthly-to-seasonal wind, temperature, or humidity over the aggregate western United States (Marlon et al. 2012; Abatzoglou and Williams 2016; Brey et al. 2021; Abatzoglou et al. 2021a). Other work has divided the western United States into large subareas (Abatzoglou and Kolden 2013; Keeley and Syphard 2017; Williams et al. 2019; Parks and Abatzoglou 2020). However, such geographically broad views often neglect local fuels, meteorology, and topography, which can be important modulators of wildfire potential (Rothermel 1972; Keeley and Syphard 2019; Syphard et al. 2019; O’Brien et al. 2018). Such geographic variations are important in California, where a heterogeneous distribution of savanna and forests interacts with large mesoscale meteorological contrasts. Additionally, reliance on slowly varying climate predictors may not include transient weather effects on wildfire, such as the occurrence of short periods of strong winds or intense downslope warming/drying. To illustrate the problem, a recent study created a statistical climate-based model that generally well captured a trend in western United States burned area over recent years (Abolafia-Rosenzweig et al. 2022). However, that study noted a breakdown in the model for 2020, a year in which short-period meteorological events were crucial for several wildfires.
Some studies have examined the large-scale spatial meteorological patterns driving fire or fire-relevant weather conditions across California (Schroeder et al. 1964; Dong et al. 2021). Early work detailed the synoptic meteorology during times of high potential fire danger across subregions of the United States (Schroeder et al. 1964). Another more recent work composited the synoptic pressure, wind, dryness, and temperature on the initiation days of more than 1000 California fires with large areas burned (Dong et al. 2021). A focus of our work is expanding on these methods.
The important goal of this work is to understand the effects of spatiotemporally varying meteorology and spatially varying fuels at sufficiently high resolution to resolve the essential fire-associated mesoscale meteorology of the region. Specifically, this paper considers several major questions regarding the complex nature of California wildfires, including:
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What are the historical spatial and temporal characteristics of California wildfire emissions in the major fuels categories (savanna and forest)?
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How do fire-relevant weather conditions such as day-of-fire dryness, antecedent dryness, and day-of-fire wind affect local and regional fire emissions in savanna and forest?
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What are the composite mesoscale spatial patterns of the meteorological forcings associated with varying wildfire emissions in different California subregions?
This paper is organized as follows. Section 2 describes the fire emissions dataset and discusses the spatial and temporal climatology of California fires, including their evolution in different fuels ecosystems. In section 3, the meteorological dataset is described and the relationship between weather and emissions is examined. In section 4 we composite the fires and meteorology by emissions and describe the aggregate meteorological conditions associated with fires of varying emissions. In section 5 we present the spatially varying meteorology associated with the different emissions levels described in section 4. Finally, in section 6 we present our conclusions.
2. Climatology of wildfire emissions across California
In this work, we apply the Global Fire Emissions Database, Version 4.1 (GFED4s as our dataset also includes the small fire data) also referred to as GFED. The GFED dataset includes gridded fuel and fire emissions data, both derived from Terra and Aqua satellite Moderate Resolution Imaging Spectroradiometer (MODIS) imagery supplemented with other sensors (Mu et al. 2011; Randerson et al. 2012; Giglio et al. 2013; van der Werf et al. 2017; Randerson et al. 2018). The emissions are derived from burned area and active fire detections run through an emissions model, which includes fuel type, surface temperature, solar radiation, and soil moisture (Akagi et al. 2011; van der Werf et al. 2017). GFED data were available daily from January 2003 to October 2020, with a horizontal grid spacing of 0.25°. Small fires mainly occur in the agricultural central valley of California and affect grid cells with very low emissions (around 1 g C m−2 month−1 or less) (van der Werf et al. 2017).
In this paper, a fire refers to a GFED grid cell with greater than zero emissions. The area burned by large fires can span an entire grid cell or multiple grid cells, and multiple fires can occur in a single grid cell. Continuous emissions in a single grid cell are considered one fire for the purposes of this paper. Overall, nearly 80 000 days of fire are obtained.
The GFED dataset also provides the percentage of varying land covers (fuel types) within each grid cell (Fig. 1). In California, the three major land cover types in GFED are savanna (described as “savanna, grassland, or shrubland” in the MODIS land cover products, Friedl et al. 2002), forest (temperate extratropical forest distinct from boreal forest as described in Akagi et al. 2011), and agriculture. Most savanna grid cells contain no temperate forest, and most forest grid cells contain no savanna. However, there are some mixed grid cells with both savanna and forest, which are identified as either savanna or forest if 60% of the cell is of a single type; otherwise, they are discarded (blue boxes in the middle subplot, Fig. 1). Two additional land covers are shown in Fig. 1, non-vegetated and urban, with non-vegetated analogous to “bare ground” in Scott and Burgan (2005). Although agricultural, non-vegetated, and urban areas theoretically do not allow fire spread, subgrid scale fuels may exist, so emissions from these regions are considered in this paper.
Distribution of savanna, mixed savanna/forest, and forest grid cells, as well as cells that are predominantly (75%) agriculture or nonvegetated. Urban areas are indicated by dots. Grid boxes that are discarded are shown in blue.
Citation: Weather and Forecasting 38, 2; 10.1175/WAF-D-22-0045.1
To illustrate the application of the GFED dataset for regional wildfire analysis, Fig. 2 displays the monthly carbon emissions across California savanna and forest for 2003–20. Emissions are highest during the late summer to early fall in both savanna and forest and August is generally the month of the highest emissions for both fuels. Emissions appear to increase over time, with 2020 possessing peak or near-peak emissions in both ecosystems. Savanna emissions have more intra-annual variability than forest emissions and span a wider range of months, often starting earlier and extending later into the autumn. The greater seasonal extent of wildfires in savanna is likely due to its small diameter fuels drying more quickly than large diameter timber, both earlier in the year and after autumn rain events. Such fuels, such as cured seasonal grasses, are more prevalent in savanna environments. Forest emissions possess greater interannual variability, likely due to the relative difficulty in igniting and sustaining fire in forest, while having a larger amount of carbon available to burn than savanna when fires do occur. Emissions maxima in forest are generally higher than those of savanna, although more area is burned in savanna/shrubland (Keeley and Syphard 2017). Results described and conclusions drawn in this paper are not meaningfully affected by the outlier peak in fire in 2020.
Monthly emissions (kg C m−2 month−1; colors) in California’s savanna and forest for 2003–20. The annual totals and monthly medians are displayed for both fuels. The gray areas in the bottom panels define the 25th and 75th percentiles of emissions and the dashed lines indicate the maximum and minimum yearly values.
Citation: Weather and Forecasting 38, 2; 10.1175/WAF-D-22-0045.1
The spatial characteristics and seasonality of California wildfire emissions are described for different emissions levels in Fig. 3. Figure 3a shows the month of maximum fire frequency (colors) and the number of fire days at each point (indicated by size) for 2003 through 2020 for fires with greater than zero 24-h emissions. Fires are most frequent in the Central Valley of California due to numerous agricultural burns. Most agricultural burns are small and take place early in the year (March–April) when wildfires are infrequent. Figure 3b, which provides emissions amounts (marker sizes) for the month of maximum emissions (colors), indicates that wildfires with larger emissions (bigger markers) are generally observed later in the year (June–October), typically on mountain slopes and northern California forests. Some individual events such as the July portion of the 2018 Carr Fire and the November 2018 Camp Fire are evident on Fig. 3.
Wildfire emissions across California (squares: forest, circles: savanna). (a) The calendar month (indicated by color) with the greatest number of wildfires, with the marker size indicating the number of fires. (b) The calendar month (indicated by color) of greatest wildfire emissions, with the total emissions indicated by symbol size. (c)–(e) As in (b), but for wildfires with maximum daily emissions exceeding 10, 50, and 100 g C m−2 (24 h)−1, respectively.
Citation: Weather and Forecasting 38, 2; 10.1175/WAF-D-22-0045.1
Figure 3 also shows the spatial distributions of wildfires with maximum daily emissions exceeding 10, 50, and 100 g C m−2 (24 h)−1 (Figs. 3c–e, respectively). Higher emission fires are mainly found over the terrain of central and northern California, with the fire frequency in southern California rapidly declining as emissions increase. This lack of high emission fires across southern California reflects the low density of savanna fuels that dominate the southern portion of the state.
The differences in emissions between savanna and forest areas are further explored in Fig. 4, which presents cumulative frequency histograms as a function of emissions for savanna and forest for the entire state of California during 2003–20. The emissions distribution for savanna is dominated by small fires, with only 1.1% of the fires emitting more than 10 g C m−2 (24 h)−1. In contrast, for forest areas, 11.8% of the fires emit 10 g C m−2 (24 h)−1 or more. Considering both forest and savanna together, fire days with emissions greater than 10 g C m−2 (24 h)−1 make up approximately 4% of the overall days of fire but account for nearly 85% of the overall emissions. For the remainder of this paper, emissions greater than 10 g C m−2 (24 h)−1 are considered “high emissions” and results are shown, categorized, and discussed in terms of emissions amount.
Cumulative histograms showing the percentiles of fires in (left) savanna and (right) forest fuels that reach the emissions thresholds of 10, 50, and 100 g C m−2 (24 h)−1, respectively.
Citation: Weather and Forecasting 38, 2; 10.1175/WAF-D-22-0045.1
The GFED database can be used to examine the temporal evolution of savanna and forest fires over California. To illustrate, Fig. 5 presents the evolution of individual savanna and forest fires that emitted more than 10 g C m−2 (24 h)−1 on at least one day. Most savanna fires begin with their highest emissions day or reach their highest emissions within the two subsequent days. Savanna wildfire emissions decline rapidly after they peak, and these fires rarely last more than 30 days (Fig. 5a). In contrast, most forest fires last over a week and maintain higher emissions over an extended period, with some lasting more than 40 days (Fig. 5b).
Wildfire emissions evolution for fires that emit greater than 10 g C m−2 (24 h)−1 on any day for (a) savanna and (b) forest. The line color corresponds to the fire’s eventual duration (colors shown on abscissa). (c) The emission evolution of four wildfires whose peak in emissions occurs after day 30.
Citation: Weather and Forecasting 38, 2; 10.1175/WAF-D-22-0045.1
There is a subset of fires that show little growth for extended periods, with a rapid increase in emissions weeks later. Such delayed growth is generally the result of renewed fire growth/spread associated with a rapid acceleration of surface winds. Figure 5c illustrates the evolution of four such events in forest whose emissions maxima occurred at least 30 days after ignition. For example, the Red Salmon Fire, which was ignited in late July 2020 (cyan color with peak emissions date of 8 September 2020 labeled), had a weak-to-moderate level of emissions for nearly a month before exploding under the influence of very strong easterly winds (Abatzoglou et al. 2021b; Mass et al. 2021; Reilly et al. 2022). Other fires peaked multiple times during the weeks after ignition.
3. Meteorological conditions associated with California fire emissions
a. Meteorological dataset and validation
The meteorological data used in this work is from the fifth major global reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ERA5), which assimilates weather observations using the ECMWF model. ERA5 fields used in this work include temperature, relative humidity (RH), zonal and meridional components of wind, and geopotential height. We acquired these fields at hourly resolution from January 2003 to October 2020. The data have a horizontal grid spacing of 0.25° (∼30 km) and are vertically interpolated to 100-m increments.
Two meteorological parameters are considered in this work: near-surface wind speed and VPD, the difference between the saturation vapor pressure and actual vapor pressure. Large VPDs indicate enhanced drying conditions. In this paper, the saturation vapor pressure is calculated assuming dry adiabatic vertical mixing to the surface during turbulence or daytime convection (Srock et al. 2018). Further in this section, we describe our choice of boundary layer depth within which we calculate fire-influencing dryness and winds. VPD is calculated daily and for the prior 30 days.
Compared to RH, VPD is better related to the evaporation from fuels than RH, and thus more useful for evaluating preconditioning of wildfires (Johnston 1919; Anderson 1936; Kucera 1954). To illustrate the value of VPD compared to RH during wildfire events, Fig. 6 compares every fifth value of daily RH, VPD, and temperature in the 500-m layer above the surface from 2017 to 2020 across grid points in California. High VPD, and thus strong drying, is only observed during periods of low RH. However, low RH is sometimes observed during periods of near-zero VPD, a clear problem for the use of RH in evaluating surface drying. During such times temperatures are usually low, and the absolute humidity of the air is low as well. Cumulative counts are also shown in Fig. 6 for VPD. Roughly 60% of the VPD samples are less than 15 hPa.
VPD compared to RH throughout the lowest 500 m of the atmosphere across California for 2017–20 for 35 abscissa and 41 ordinate bins. Values correspond to the centroid of each bin and the color denotes the temperature (°C). Overlaid on the figure is a cumulative histogram of raw (non-binned) VPD (orange). RH greater than 100% and VPD less than 0 hPa are clipped for this figure. Such values do not affect fire and arise due to vertical interpolation applied to the ERA5 above mountainous terrain. No minimum count is used in the binning.
Citation: Weather and Forecasting 38, 2; 10.1175/WAF-D-22-0045.1
The ERA5 reanalysis is of sufficiently fine resolution (∼30-km grid spacing) to resolve the broad characteristics of mesoscale features such as downslope wind events. To illustrate, ERA5 fields were used to describe conditions associated with the rapidly spreading 2018 Camp Fire (Fig. 7). That fire was initiated on the morning of 8 November 2018 by a downslope, easterly wind event that damaged electrical infrastructure on the western slopes of the central Sierra Nevada (Mass and Ovens 2020). Maps of maximum winds and VPD in the lowest 500 m at 1400 UTC 8 November 2018 show strong winds above the western slopes of the Sierra Nevada and over the coastal terrain, with higher VPD on the western Sierra Nevada slopes (Figs. 7a,b). Vertical cross sections along 39.75°N show that the ERA5 analysis defines downslope winds on the Sierra Nevada and mountain wave modulation of wind and VPD (Figs. 7c,d). These structures are consistent with higher-resolution model simulations of the event (Mass and Ovens 2020).
(a),(c) Wind speed magnitude (U; m s−1) and (b),(d) VPD (hPa) associated with the 2018 Camp Fire (fire location shown at the circle marker). The fields are shown at 1400 UTC 8 Nov 2018, near the time of fire initiation. The location of the vertical cross section is indicated in the top panels (39.75°N).
Citation: Weather and Forecasting 38, 2; 10.1175/WAF-D-22-0045.1
b. Meteorological conditions during savanna and forest wildfires
To determine the meteorological conditions associated with varying wildfire emissions, hourly VPD and wind speed from the ERA5 dataset are compared with daily GFED emissions over the 18-yr period of GFED data. For each daily fire emission event in a GFED grid cell, hourly VPD and wind speed during that day are recorded across the lowest 500 m above ground in the four horizontally adjacent ERA5 grid columns. The four surrounding columns are used because the ERA5 and GFED grids are offset by 0.125° in both horizontal directions. The wind speed and VPD for each emission point are calculated as follows. The wind speed is the maximum hourly wind speed that day recorded in the lowest 500 m. The VPD is the daily average of the hourly VPD maxima in the lowest 500 m. The 30-day prior average VPD is calculated as well.
Maximum daily winds are used rather than the daily average because strong winds are critical for fire initiation and rapid fire spread. Such daily maximum winds in the ERA5 are generally close to the peak wind gusts observed at anemometers proximate to the wildfires. For example, the observed wind gusts for the Camp Fire (Jarbo Gap RAWS3: 17.9 m s−1 at 1413 UTC 8 November 2018) are comparable to the daily maximum ERA5 wind (18.2 m s−1 at 1400 UTC 8 November 2018). For the Wine Country Fires, the ERA daily maximum wind of 23.9 m s−1 for 9 October 2017 compares favorably to the Santa Rosa RAWS4 observations (22.8 m s−1 at 0729 UTC 9 October 2017).
Daily emissions and associated meteorology for both savanna and forest wildfires are compared for all days with emissions, the day of maximum emissions of each fire, and the first day of emissions of each fire. Scatter diagrams of daily averaged near-surface VPD and daily maximum wind speed (Fig. 8, left panels) indicate that high-emission savanna fires [red colors, emissions above 10 g C m−2 (24 h)−1] for all days and maximum emissions days are generally limited to periods with VPD greater than 15 hPa. In forest, high emission fires for all days and maximum emission days predominantly occur when daily VPD is greater than 10 hPa. The first days of fires exhibited slightly higher dryness in both fuel categories. To explore the potential impacts of antecedent conditions, daily VPD is replaced with VPD averaged over the preceding 30 days (right panels). In forest, a greater VPD occurs prior to high emissions, with high emissions occurring above approximately 15 hPa. For savanna, the use of the 30-day prior VPD produces little change in the scatter diagram compared to using day-of values. Weak emissions fires can occur at high dryness (large VPD) and strong winds in both fuel types.
Emission amount (colors), daily maximum wind (U; m s−1), and average VPD [hPa; day-of VPD in the left two columns and 30-day prior VPD in the right two columns] are compared for all fire days, the maximum day of emissions, and the first fire day in savanna and forest.
Citation: Weather and Forecasting 38, 2; 10.1175/WAF-D-22-0045.1
4. Aggregate meteorology and emissions
To gain further insights into the relationship between emissions and near-surface meteorological conditions, the emissions were subdivided into small ranges (logarithmically equally spaced spans). Within these emissions spans, averages in the corresponding VPD and winds were computed, and their relationships with emissions explored.
a. The effect of VPD and wind speed on fire emissions
The relationship between average VPD and emissions is evaluated for both savanna and forest on all emission days, the maximum emission day, and the first emission day of each fire (Fig. 9). For savanna, there is little trend in VPD from weak to moderately high emissions [less than approximately 1 g C m−2 (24 h)−1], but as emissions increase to higher levels [above 10 g C m−2 (24 h)−1] there is a steady upward trend in associated VPD. For forest areas, there is a progressive increase in VPD from weak to high emissions. Above the high emissions threshold [10 g C m−2 (24 h)−1] in both fuels, the trend with increasing VPD flattens (for all days) and is more variable, suggesting diminishing impacts of increasing dryness for high emissions wildfires. However, increases in the lower bound of the VPD spread (gray area) and the increase in the 25th percentile of VPD imply that, for moderate and high emissions, elevated dryness may be a necessary condition.
The
Citation: Weather and Forecasting 38, 2; 10.1175/WAF-D-22-0045.1
Daily and antecedent (30-day prior) VPD were compared across emissions spans, with relatively small differences between the two periods (figure not shown). For the maximum day and the first day of high emissions savanna fires, daily VPD is greater than antecedent VPD by around 5 hPa (the difference is significant at the 95% significance level). In forest, a smaller difference exists in emissions for daily and 30-day antecedent VPD.
The relationship between the daily maximum winds and emissions is shown in Fig. 10 for all days, the maximum emission days, and the first days of emission. For savanna, there is little trend in wind speed for emissions below 10 g C m−2 (24 h)−1, but high emissions [above 10 g C m−2 (24 h)−1] are associated with increasing winds. For forest fires, wind speed initially declines with increasing emission, but wind speed increases for high emissions [above ∼10–30 g C m−2 (24 h)−1]. In forest, the initial decrease in wind speed is due in part to aliasing in fire seasonality and the relationship between emissions and VPD; the lowest emissions fires are relatively more possible in cool, wet, and windy months. Compared to forest fires, low emissions savanna fires can take place any time of year. Importantly, the largest increasing trend of winds with higher emissions occurs during the first day of fires in both fuels. This seems reasonable since strong winds are frequently associated with fire initiation and initial rapid wildfire growth, a finding supported by other research (Abatzoglou et al. 2018; McClung and Mass 2020; Dong et al. 2021).
The
Citation: Weather and Forecasting 38, 2; 10.1175/WAF-D-22-0045.1
b. How unusual are the winds and VPD for varying emissions?
Another way of exploring the relationship between emissions and meteorology is to examine emissions as a function of the climatological percentiles of wind and VPD. Are high emissions associated with unusually strong meteorological forcing? To answer this question, we present emissions spans as a function of the percentiles of wind and VPD for 2003–20 (Fig. 11). The percentiles are calculated based on the populations of first, maximum, and all fire days in similar fuels. The number of cases in each emissions span is shown by the symbol size.
The
Citation: Weather and Forecasting 38, 2; 10.1175/WAF-D-22-0045.1
For savanna, weak and moderate emissions [below ∼10 g C m−2 (24 h)−1, respectively] are associated with winds near the 50th percentile. For VPD, there is a trend toward higher percentiles (from approximately 40th to 80th) for weak to moderate emissions (from green to yellow). High emissions in savanna [from yellow to red, above 10 g C m−2 (24 h)−1] are associated with both higher percentile strong winds and higher percentile VPD, with increasing emissions more correlated with wind speed increases. For weak-to-moderate forest emissions [below ∼10 g C m−2 (24 h)−1] wind speed declines and VPD increases for increasing emissions. The decline in wind speed across these emissions is due in part to underlying seasonality between VPD and wind. Weak-to-moderate emissions relate well to dryness (Fig. 9) and wind speeds tend to vary inversely with dryness at lower VPDs. As in savanna, winds in forests increase rapidly for high emissions [from yellow to red above 10 g C m−2 (24 h)−1]. For the highest forest emissions, both winds and VPD approach the 90th percentile. High emissions on the first days of fires are associated with the greatest winds and dryness. When such atmospheric conditions occur early in a fire’s evolution the conditions may help rapidly spread the fire and increase emissions (Abatzoglou et al. 2018). In summary, for both savanna and forest, the highest emissions (dark orange, red) are found during periods of the most extreme simultaneous dryness and wind, as found for recent Oregon wildfire cases (Abatzoglou et al. 2021b; Mass et al. 2021).
c. Seasonality of emissions
Although the seasonality of emissions was noted earlier (in Figs. 2, 3, 10 and 11), in this section we describe the occurrence of varying levels of emissions as a function of the day of the year (Fig. 12). We simplify the emissions spans into six bands: three weak-to-moderate bins [below 10 g C m−2 (24 h)−1] and three high emissions bins [above 10 g C m−2 (24 h)−1]. In both savanna and forests, weak-to-moderate emissions [under 10 g C m−2 (24 h)−1] occur year-round; however, as emissions increase, fires occur preferentially during the late summer and early autumn. There is a greater tendency for (relatively rare) high emission events to occur in autumn for forests, with a longer season for weak-to-moderate wildfires (green-yellow colors) in savanna.
Annual variation of the maximum day of emissions in savanna and forest binned by emissions amounts. The transparency of the vertical lines is related to the frequency of such emissions on a particular day (more transparent: fewer cases).
Citation: Weather and Forecasting 38, 2; 10.1175/WAF-D-22-0045.1
5. Regional spatial meteorology for varying savanna and forest emissions
To explore the spatial structure of the meteorological fields accompanying California wildfires, this section presents maps that composite near-surface air temperature and wind anomalies during the days of maximum emissions for various fuels and subregions of the state. These fields are shown as standardized anomalies, where the deviation from climatology is divided by the standard deviation over the climatological period (2003–20). Both the climatology and standard deviations are computed based on the 30-day period encompassing the event in question. Meteorological composites are computed for the regions shown in Fig. 13, which divide the state spatially and by dominant surface fuel type. Emissions subregions qualitatively divide California into similar latitude regions and ecoregions, reflecting the heterogeneity of fuels and meteorology.
The four savanna regions (warm colors) and two forest regions (cool colors) considered in this study.
Citation: Weather and Forecasting 38, 2; 10.1175/WAF-D-22-0045.1
a. Regional spatial meteorology for forest fires
Starting with fires in the North-Forest subregion, the area of highest emissions during the 2003–20 period (Fig. 3), the temperature spatial composites (Fig. 14a) indicate a weak warm anomaly over most of California for weak-to-moderate emissions, with highest temperatures over central/northern California. For higher emissions, a temperature gradient develops along the crest of the Sierra Nevada, with warmer temperatures to the west. For the highest emissions [greater than 464 g C m−2 (24 h)−1], an intense warm anomaly develops over central and coastal California with colder-than-normal conditions over Nevada. Such interior cooling and coastal warming are consistent with cool, surface high pressure systems moving into the intermountain basin, producing an offshore pressure gradient that drives strong easterly downslope flow (and associated adiabatic warming) across the Sierra Nevada range (McClung and Mass 2020). The wind composites (Fig. 14b) for the North-Forest subregion show lighter-to-normal winds across the domain during weak-to-moderate emissions fires. For higher emissions, the positive wind anomalies increase, especially across the North-Forest subregion and over southern California.
Standardized anomalies of (a) surface temperature and (b) wind (colors) for the maximum emissions day for the North-Forest subregion. The title of each subplot provides the number of days that make up each composite average and the emissions range while the color corresponds to the emissions spans. The light gray dots indicate the North-Forest subregion shown in Fig. 13.
Citation: Weather and Forecasting 38, 2; 10.1175/WAF-D-22-0045.1
The temperature and wind composites for the Sierra-Forest subregion are similar to the North-Forest area and are thus not shown. The similarity in the composites is not surprising considering the relative proximity and identical fuel type compared to North-Forest. Small differences with North-Forest do exist, such as the shift of the largest temperature and wind anomalies toward the Sierra Nevada.
b. Regional spatial meteorology for savanna fires
For the savanna fuel type, we focus on the Bay-Savanna subregion, which includes 73 high-emissions fire days and several major fires such as the 2017 Wine Country Fires, and the South-Savanna subregion, which includes 66 high emissions fire days that include Santa Ana wildfires. The North-Savanna and Central-Savanna subregions contain many fewer fires than the Bay subregion and are not shown for brevity.
For the Bay-Savanna subregion, weak-to-moderate emission events [below 10 g C m−2 (24 h)−1], are associated with slightly warmer-than-normal conditions (Fig. 15a). In contrast, the higher emissions events possess an increasingly strong temperature gradient across California and Nevada, with colder air in the interior. For the highest emissions event, the coastal warming greatly intensifies, with strong cooling over northern California and Nevada.
As in Fig. 14, but for the Bay-Savanna subregion.
Citation: Weather and Forecasting 38, 2; 10.1175/WAF-D-22-0045.1
Wind anomalies during weak-to-moderate Bay-Savanna fires are near zero across California (Fig. 15b). For higher emissions, wind anomalies across the state become increasingly positive. For the most extreme case, a complex pattern of strong wind anomalies is evident, with very strong winds over the coastal terrain north of the Bay Area and near the crest of the Sierra Nevada.
Turning to the South-Savanna subregion (Fig. 16), the temperature anomalies across California are very weak or even negative for the weak-to-moderate emission cases but become warmer-than-normal as emissions increase beyond moderate levels. For the largest emissions events [60–464 g C m−2 (24 h)−1], warming increases along the coastal zone, with the interior of California and Nevada becoming cooler-than-normal. As with forest, this surface temperature gradient is associated with cool, surface high pressure moving into the intermountain west (McClung and Mass 2020). For winds, South-Savanna events with weak-to-moderate emissions are associated with near-normal wind speeds (upper panels, Fig. 16b). But as emissions over the subregion increase to higher values, the winds become much stronger over southern California, consistent with Santa Ana events (lower panels, Fig. 16b). Winds also increase over the Sierra Nevada and the mountains of northern California.
As in Fig. 14, but for the South-Savanna subregion.
Citation: Weather and Forecasting 38, 2; 10.1175/WAF-D-22-0045.1
6. Conclusions
This paper describes the climatology of California wildfires using their carbon emissions as a proxy for fire existence and growth and evaluates the relationship between daily emissions, land use, and the spatially and temporally variable regional meteorology. In this work, near-surface daily maximum wind, daily average vapor pressure deficient (VPD), and 30-day-prior average VPD are determined for California wildfires of differing emissions across savanna and forest fuel types for around 80 000 days of wildfire. The results provide valuable insights of the relationships between daily wind, VPD, surface fuels, and fire and how those relationships vary by the amount of emissions.
Two datasets are used in this work. For emissions, we apply the Global Fire Emissions Database, Version 4.1 (GFED), which provides temporally varying daily emissions data for a variety of fuel types on a 0.25° grid fromm 2003 through October 2020, while meteorological fields (temperature, relative humidity, winds) are acquired from ERA5, which is available as hourly data on 0.25° grids for the same period.
The emissions data reveal a strong seasonality for both savanna and forest wildfires, with greater seasonal extent for savanna and greater peak emissions for forest. The greatest emissions are found during autumn over the northern forest areas of California, with substantial emissions over the western slopes of the Sierra Nevada and the coastal mountains north of San Francisco. In contrast, the frequency of fires is more spatially uniform but dominated by savanna fires throughout the state and agricultural fires over the Central Valley. The cumulative histograms of wildfire frequency by emissions indicate that only 1.1% of the savanna fires emit more than 10 g C m−2 (24 h)−1. In contrast, 11.8% of the forest fires emit 10 g C m−2 (24 h)−1 or more. Although forests burn less frequently than savanna, they possess far more fuel. Considering both savanna and forest areas, emission days greater than 10 g C m−2 (24 h)−1 make up around 85% of the overall emissions.
Wildfire emissions, vapor pressure deficit (VPD), and wind speed are compared. We find that high emission [greater than 10 g C m−2 (24 h)−1] savanna fires for all days and maximum emission days are mainly limited to periods with VPD greater than 15 hPa, while in forest, high emission fires for all days and maximum emission days are mainly limited to periods with daily VPDs greater than 10 hPa. In savanna, little change in these results is found using the VPD of the prior 30 days while in forest the high emissions threshold using the 30-day prior VPD increases to 15 hPa. Comparing savanna emissions with VPD, there is little increase in VPD transitioning from weak to moderate emissions, followed by a steady upward trend in VPD for higher emissions. For forest areas, there is a progressive increase in VPD from low to high emissions. In both fuels, the VPD tends to level off for the highest emissions. Turning to winds, for savanna there is little trend in wind speed with weak-to-moderate emissions, but high emissions are associated with stronger winds. For forest fires, emissions initially decline as wind speed strengthens, but then increase with wind speed for higher emissions [above ∼10–30 g C m−2 (24 h)−1]. The initial decrease is partly due to aliasing in seasonality, with weak emissions in forest in cool and moist months. The first days of fires exhibit slightly higher VPDs (greater than 20 hPa) likely compensating for the lack of fuel preheating caused by a small fire early in its evolution (Pyne et al. 1996; Abatzoglou et al. 2018).
An important question relates to the relative frequency of the wind and dryness conditions associated with varying wildfire emissions in savanna and forest. This analysis finds that for savanna, weak and moderate emissions are associated with winds near the 50th percentile. For moderate emissions, increasing emissions are associated with increasing VPD (from around the 45th to 80th percentile). Higher emissions in savanna are associated with both strong winds and large VPD, with increasing emissions best related to increasing winds. In forest wildfires with weak-to-moderate emissions, winds decline (from around the 60th to 40th percentile) and VPD increases (up to around the 80th percentile) with increasing emissions. This decline in winds with low but increasing VPD is due in part to underlying seasonality between VPD and wind speed in the dataset (weaker winds during summer when VPD is highest) though wind speeds tend to decrease as VPD increases even on subseasonal time scales. As in savanna, this situation changes substantially for the high emissions with winds increasing rapidly with emissions. The highest forest emissions are associated with wind speed and dryness around the 90th percentile. The highest emissions on the first days of forest fire exhibit the most extreme combinations of strong winds and large dryness as expected from previous work on Oregon wildfires (Abatzoglou et al. 2021b; Mass et al. 2021).
Next, the spatial variations in surface wind and temperature are examined for savanna and forest wildfires. For forest fires in mountainous northern California, there is a weak warm anomaly over most of California for weak-to-moderate emissions. For the highest emissions, a strong temperature gradient develops along the crest of the Sierra Nevada between an intensifying warm anomaly over central and coastal California and colder-than-normal conditions over Nevada. Such interior cooling is consistent with cool, surface high pressure systems moving southward into the intermountain basin, producing an offshore pressure gradient that drives strong easterly downslope flow across the Sierra Nevada range (McClung and Mass 2020). Winds are weak across the domain during weak-to-moderate emissions fires, but as fires increase in emissions, the wind anomalies first decline and then increase to above normal across the domain, especially across the North-Forest subregion.
For savanna fires around the Bay subregion, weak-to-moderate emission events are associated with slightly warmer-than-normal conditions, with warming along the coast for moderate events. For high emissions events in that subregion, the coastal warming intensifies while strong cooling develops over northern California and Nevada. Wind anomalies during weak-to-moderate Bay-Savanna fires are weakly negative or near zero across California, but for higher emissions, wind anomalies across the state become increasingly positive. For the rare extreme emissions case, a complex pattern develops, with very strong winds over the coastal terrain north of the Bay Area and near the crest of the Sierra Nevada but reduced winds over the eastern portion of the Bay subregion. Such strong winds in the western portion may explain the concentration of high emissions fire in the western Bay subregion (Fig. 3).
Considering savanna fires over southern California, including the well-known Santa Ana events, the temperature anomalies across California are very weak or even negative for the weak-to-moderate emission cases but warmer-than-normal temperatures are observed as emissions increase. For the largest emissions events, warming is amplified along the coastal zone and within the interior of California while Nevada evinces as cooler-than-normal. For weak-to-moderate emissions, winds across the subregion are near normal. But as emissions over the subregion increase to higher values, the observed winds are much stronger over southern California, consistent with Santa Ana events.
An essential finding of this research is that there are substantial differences in the meteorological forcing associated with different levels of wildfire emissions and that such forcing has substantial spatial variations and dependencies on fuel type. Although there are commonalities in the meteorology associated with geographically proximate fires in savanna and forest, there are also notable differences. This work has also shown the differences in the seasonality of fires for differing fuels and fires of varying emissions amounts. A key message of this work is that both dryness (large VPD) and strong winds are essential for the highest emissions fires, and both parameters should be considered when projecting future changes in wildfire frequency and severity.
Based on this research, there are several tasks that could be productive. Long-term observed trends in the VPD and wind threshold exceedance could be determined for California and its subregions. Future projections of the criteria exceedance could be determined using regional climate model output applying realistic emissions scenarios (e.g., SSP 4.5). In addition, this work would be enhanced by using higher-resolution emissions, land use, and meteorological data.
Acknowledgments.
This research was supported by NSF Grant AGS-524134984. The authors thank Professors Brian Harvey and Ernesto Alvarado of the UW School of Environment and Forest Science for providing background on forest and fire ecology.
Data availability statement.
The data in this study may be accessed as follows. ERA5 weather data: https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview or DOI: 10.24381/cds.adbb2d47. GFED4 emissions data: https://www.geo.vu.nl/∼gwerf/GFED/GFED4/ and supporting information: https://globalfiredata.org/pages/data/. A shapefile denoting California’s border from UC Berkeley: https://geodata.lib.berkeley.edu/catalog/ark28722-s73w23.
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