In this paper we present the first direct observational evidence that the condensation level in pyrocumulus and pyrocumulonimbus clouds can be significantly higher than the ambient lifted condensation level. In addition, we show that the environmental thermodynamic profile, day-to-day variations in humidity, and ambient wind shear all exert significant influence over the onset and development of pyroconvective clouds. These findings are established using a scanning Doppler lidar and mobile radiosonde system during two large wildfires in northern California, the Bald Fire and the Rocky Fire. The lidar is used to distinguish liquid water from smoke backscatter during the plume rise, and thus provides a direct detection of plume condensations levels. Plume tops are subsequently determined from both the lidar and nearby radar observations. The radiosonde data, obtained adjacent to the fires, contextualize the lidar and radar observations, and enable estimates of the plume ascent, convective available potential energy, and equilibrium level. A noteworthy finding is that in these cases, the convective condensation level, not the lifted condensation level, provides the best estimate of the pyrocumulus initiation height.
Pyrocumulus clouds (pyroCus) form when wildfire convective plumes rise to their condensation level and subsequently develop cumuliform cloud tops (American Meteorological Society, 2015a). The extent of pyroCu development depends on the relationships amongst atmospheric stratification, ambient moisture, and fire fluxes of heat and moisture (Potter, 2005; Luderer et al., 2006, 2009; Freitas et al., 2007). Some pyroCus release significant moist instability aloft and thereby trigger deep convective clouds that sometimes grow into pyrocumulonimbus clouds (pyroCbs). Compared to their lesser counterparts, pyroCbs possess glaciated cloud tops and can thus generate precipitation, downdrafts, and lightning (American Meteorological Society, 2015b). In exceptional cases, pyroCbs have been linked with extreme fire growth (Peterson et al., 2015), devastating firestorms (Fromm et al., 2006), and even fire-induced tornados (Cunningham and Reeder, 2009; McRae et al., 2013).
In addition to their impact on fire behavior, pyroCus/Cbs have garnered significant research attention due to their affect on vertical smoke transport, atmospheric chemistry, and cloud microphysics. For example, pyroCus can cause significantly deeper smoke injection than is caused in dry convective cases (Frietas et al., 2007), and pyroCb clouds are now recognized as the source of previously unexplained aerosol layers lofted in the lower stratosphere (Fromm and Servranckx, 2003; Fromm et al., 2006, 2010). In addition, satellite and dual polarimetric radar observations of pyroCb show that the extreme aerosol loading results in high concentrations of small ice particles (Rosenfeld et al., 2007), especially as compared to nearby clouds forming in smoke free air. The abundance of ice particles changes the radiative properties of the clouds and also favors atypical positive polarity lightning strokes (Rosenfeld et al., 2007; Lang et al., 2006, 2014).
Despite the significant research on pyroCu/Cb microphysics, surprisingly little is known about the environmental controls on pyroCu development. To date, only a handful of studies explicitly examines the thermodynamic and kinematic structure of these cloud-topped convective columns (Potter, 2005; Trentman et al., 2006; Luderer et al., 2006, 2009; Freitas et al., 2007) and no studies include direct observations of pyroCu/Cb initiation. As a result, there is an open scientific debate regarding the plume condensation level, which is an important parameter for modeling smoke injection height and plume evolution (Freitas et al., 2007). Specifically, there are contrasting views in the literature about whether the plume condensation level is expected to be higher than or lower than the ambient lifted condensation level (LCL).
Potter (2005), for example, proposes that pyroCus/Cbs should exhibit cloud bases lower than the ambient LCL due to the moisture released during combustion of woody fuels and from the evaporation of fuel moisture. Drawing on historical cases of pyroCus/Cbs, radiosonde data, and theoretical considerations, he hypothesizes that the latent heat release may be the dominant factor in many moist-pyroconvective events. A limitation of this study is the anecdotal treatment of condensation levels, which are estimated, and the use of radiosonde observations that may not reflect the near fire environment.
In contrast to Potter (2005), Luderer et al. (2006, 2009) use high-resolution simulations and theoretical sensitivity calculations to conclude that “the combined effect of released moisture and heat from the fire almost always results in a higher cloud base compared to ambient conditions.” They also find that moisture released in combustion constitutes less than 10 % of the pyroCu/Cb water budget with the remainder of the plume water resulting from entrained environmental air. While these modeled results are rather convincing, they lack clear observational support.
To that end, the only field observations that address plume moisture are from small-scale grass fire experiments, where significant increases in water vapor mixing ratio are documented near the surface, but then decrease rapidly with height (Clements et al., 2006, 2007; Kiefer et al., 2012). While these observations are consistent with the dominant role of entrainment, such small-scale plumes may not be representative of deep convective plumes that extend into the upper troposphere or even lower stratosphere.
In this paper we present the first direct observations of condensation levels in two wildfire pyroCu/Cb cases. The fires, the Bald Fire and the Rocky Fire, were located in northern California, and observations were conducted on 2 August 2014 and 30 July 2015, respectively (Fig. 1). The pyroCu cloud bases and plume rise dynamics were measured using a mobile atmospheric profiling system (Clements and Oliphant, 2014) that included a scanning Doppler lidar and an upper-air radiosonde system which provided thermodynamic profiles immediately upstream of the fire perimeters. From these data, our results clearly show that observed plume condensation levels are substantially higher than the ambient LCL. Additional aspects of the plume rise, including limiting factors on convective growth and the role of environmental moisture are also examined.
Overview map showing the regional topography (terrain shading), locations of the Rocky Fire and the Bald Fire (red circles), the locations and names of the NWS radars used in the plume analysis (white circles), and the KOAK sounding site (white circle).
In this study, data from a Halo Photonics scanning Doppler lidar are
examined (Pearson et al., 2009). The lidar emits a 1.5
Near-IR lidars are sensitive to aerosol, cloud droplets, and forest fire smoke. Due to these sensitivities numerous previous studies have used lidars to examine smoke layers and smoke plumes (Banta et al., 1992; Kovalev et al., 2005; Pahlow et al., 2005; Charland and Clements, 2013; Lareau and Clements, 2015).
Forest fire smoke typically exhibits a log-normal particle number
distribution with a peak near 0.13
The 1.5
Near-IR lidars also record high backscatter and rapid attenuation due to cloud droplets, making them an ideal tool for cloud base and cloud top detections (Hogan et al., 2003; Winker et al., 2009). In this study we leverage this attribute of the lidar to determine pyroCu cloud bases and edges in the convective column. Similarly, Banta et al. (1992) used an IR lidar to identify pyroclouds in a wildfire smoke column.
The lidar was programmed to conduct “range-height indicator” (RHI) scans
centered on the Bald Fire and Rocky Fire pyroconvective plumes. The scan
azimuth angles were determined visually. During the Bald Fire, the RHI
elevation step was 0.7
The lidar was also used to examine the velocity field near the fires and
within the convective plumes. For example, the Doppler radial velocity data
collected during the RHI scans are used to inspect the plume structure.
These data have a resolution of 3–4 cm s
Examples of the plume detection and attenuation algorithm based on
the filtered (solid black line) and unfiltered (gray line) lidar
signal-to-noise ratio (SNR
The lidar data are post-processed to determine plume boundaries and beam
attenuation depth. The edge detection algorithm uses a combination of the
lidar signal-to-noise ratio (SNR) and attenuated backscatter coefficient to
isolate the plume. Similar approaches are presented in previous studies
(Kovalelv et al., 2005; Charland and Clements, 2013). In our analysis, we
first apply a 5th order Butterworth filter with a 5-point window to the
SNR data along each lidar beam to eliminate some of the instrument noise.
Next we record the radial location of maximum attenuated backscatter
coefficient. Starting from that location we search inward along the beam for
the first range gate where the SNR
To demonstrate the algorithm, Fig. 2 presents lidar data extracted from two
elevation angles (10.2, 46.7
Data from four National Weather Service (NWS) radars are used to examine plume structure. These 10 cm radars are sensitive to large ash and precipitation particles in the convective column but insensitive to cloud droplets and sub-micron smoke. Radars have been used in numerous wildfires studies (Banta et al., 1992; Hufford et al., 1998; Fromm et al., 2006; Rosenfeld et al., 2007; Jones and Christopher, 2010a, b). Recently, dual-polarization radars have been used to examine the microphysics of wildfire plumes and clouds (Melnikov et al., 2008, 2009; Lang et al., 2014).
In this study we leverage three aspects of the NWS radars. First we examine the radar echo tops to estimate the maximum cloud height. The echo tops are the highest level at which the radar reflectivity exceeds 18 dbZ (Lakshmanan et al., 2013). Second we combine radar reflectivity from multiple radars to generate volume renderings of the pyroconvective plumes. These volumes are constructed by creating a gridded interpolant from all the available contemporaneous radar data. Data from the Medford, Reno, Beale, and Sacramento radars are combined for the Bald Fire, and from the Beale and Sacramento radars for the Rocky Fire. The radar locations relative to the fires are shown in Fig. 1.
Finally, we inspect the differential reflectivity (
Visible satellite observations from the Geostationary Operational Environmental Satellite (GOES-15) are used to characterize the presence of pyroCus above each fire. These data have a spatial resolution of 1 km and a nominal temporal resolution of 15 min, depending on the scan schedule. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua satellites are also used. These data include both true color visible images and fire-radiative power (FRP). The nominal resolution is 500 m. FRP is derived by differencing fire pixels from adjacent non-fire pixels using infrared radiance (Wooster, 2002) and has been shown to provide high fidelity representation of fire activity during California wildfires (Koltunov et al., 2012; Peterson et al., 2015). FRP data from GOES are also examined.
Thermodynamic profiles were collected adjacent to both fires using a
GRAW
The sonde data are used to examine the ambient condensation level by considering three lifted parcels (1) the most unstable (MU) parcel, (2) the mixed-layer (ML) parcel, and (3) the convective (CONV) parcel. The MU parcel is the parcel with the highest convective available potential energy (CAPE), whereas the ML parcel is based on the mean temperature and mixing ratio in the lowest 150 hPa. The CONV parcel reflects the surface temperature required for free convection based on the surface mixing ratio. The condensation level for each of these parcels is compared in the analyses below.
The Bald Fire (40.9
Bald and Eiler Fire progression map for 1 and 2 August. The fire perimeters are from the US National Forest Service National Infrared Operations (NIROPS) flights. The background is a satellite image draped over the terrain, which is highlighted with hill shading. Also shown are the truck location (yellow dot), lidar scan path (yellow line), and radiosonde location (yellow star).
Overview of the pyrocumulus initiation and growth on 2 August 2014.
During its rapid expansion on 2 August, the Bald Fire developed a towering pyroCu that subsequently matured into a pyroCb. Visible satellite data show the pyroCu initiation occurred at 13:30 PDT, with continued cloud growth through mid-afternoon (Fig. 4a–d). At 14:26 PDT the MODIS-Aqua satellite recorded a detailed image of the growing pyroCu, showing crisp cumuliform cloud features above the fire perimeter with more diffuse cloud elements extending to the northeast (Fig. 4e). The spreading cloud features were detrained from the primary updraft and then advected in southwesterly flow aloft.
The total FRP from the Bald Fire at the time of the MODIS-Aqua image was 19 700 MW summed over 30 fire pixels. The pixel maximum was 2258 MW, though the pyroCu obscures a substantial portion of the fire. For comparison, the earlier MODIS-Terra overpass at 12:45 PDT yielded a maximum FRP of just 829 MW and a total FRP of 3836 MW summed over 13 fire pixels. Clearly the fire experienced a rapid change in size and intensity during the early afternoon, coincident with the development of the pyroCu.
The truck-mounted Doppler lidar was situated
Figure 5 shows a sequence of lidar scans spanning the 5 min period prior
to the MODIS-Aqua overpass. These data are expressed as the logarithmic
attenuated backscatter coefficient (hereafter backscatter) in units of
m
While pyroCus were already present at the beginning of the scan sequence, the data show the development of a new cloud element. Figure 5a and b for example, show only a few points of rapid attenuation and high backscatter aloft, whereas starting at Fig. 5c a new, upright cloud edge is detected. This nascent pyroCu element then rapidly expands during the subsequent RHI scans, reaching a height of at least 8500 m before moving out of the lidar field of view (Fig. 5d–f). As we show in the radar analysis below, the actual plume top was as high as 12 km in the 10 min following these scans.
The scans, which were roughly parallel to the mean wind direction, also reveal that the plume experienced significant variations in tilt with time, alternating between windward (Fig. 5a) and rearward sloping geometries (Fig. 5f). In fact, the windward protrusion of the plume was as much as 2 km away from its base. Large coherent vortices are also apparent along the plume edge, especially in Fig. 5a and b as the “stair step” pattern in the plume edge detections. Based on the radial velocity data (not shown) the inward clefts in the plume edge correspond to enhanced flow into the plume and outward lobes reflecting flow towards the lidar. Vortices of this sort are a well-known feature of rising thermals and plumes and play a leading role in entrainment (Scorer, 1957; Woodward, 1959).
Following the initial plume rise, sustained pyroCus were observed with the lidar until 15:32 PDT, at which point the truck was relocated for safety reasons. To determine the plume condensation level, we aggregate data from all of the lidar scans during this period. From this larger data sample, Fig. 6a presents the time-maximum backscatter as a function of height and distance, and Fig. 6b as a function of height only. In addition, Fig. 6c shows the computed percentiles (5, 50, and 95th percentiles) of the attenuation depth binned into 100 m intervals. Collectively, these data reinforce many of the aspects of the initial plume rise sequence discussed above. For example, there is a persistent transition in backscatter near 5500 m (blue line in Fig. 6a and b). Below this level, the backscatter approximately linearly decreases with height, consistent with the entrainment of clear air into an aerosol-laden plume. In contrast, at 5500 m the backscatter sharply increases (as does the SNR, not shown), corresponding to the condensation level and development of the pyroCu. The backscatter intensity remains high there and above due to the continued presence of liquid water.
Plume rise sequence recorded by successive lidar RHI scans from
14:19 to 14:24 PDT. The displayed data are the logarithmic attenuated backscatter
coefficient (m
Statistical analysis of lidar data between 13:50 and 15:02 PDT showing the
plume condensation level.
The attenuation depth also shows a sharp transition at 5500 m (Fig. 6c).
Below that level the median attenuation depth increases with height, which
is again consistent with the dilution of the smoke plume via entrainment. At
5500 m the attenuation depth (across all percentiles) sharply decreases,
converging towards a median value of
Since the pyroCu cloud tops exceeded the lidar range, the maximum smoke
injection depth is obtained from the radar echo tops product from the NWS
radar in Medford, OR (KMAX), which is
An additional interesting aspect of the radar data is the presence of deep echo tops southwest (e.g., upwind) of the infrared fire perimeter (solid contours, Fig. 7a). This observation is consistent with the periodic forward tilt of the plume as observed in the lidar backscatter (Figs. 5 and 6). We hypothesize that the forward tilt relates to large-scale vortices that form as the plume penetrates through a stable layer at the top of the boundary layer (Saunders, 1962), and due to the deflection of the ambient flow around the plume.
Figure 7b shows the corresponding time series of the maximum radar echo tops. The pyroCu initiation at 13:30 PDT, as shown in Fig. 4b, corresponds to a rapid rise in echo tops from 6500 to 10 000 m. Following the initial plume growth, the plume tops slowly rise until 14:20 PDT at which point a second period of rapid plume growth occurs, pushing the convective column to heights above 12 km. The onset of this deep plume penetration closely corresponds to the lidar plume rise sequence shown in Fig. 6, as well as the MODIS-aqua image. The plume heights subsequently subside, remaining near 10 km for the balance of the afternoon before diminishing more substantively at night.
Radar analysis of the Bald Fire convective column.
A 3-D volume rendering of radar reflectivity from the Bald Fire at the time of maximum injection height (14:29 PDT) reveals additional aspects of the plume structure (Fig. 7c). The isosurfaces for 30, 28, 26, 24, and 18 dbZ are shown, along with the fire perimeters (red shading), lidar scan plane (black dots), lidar plume edge detections (yellow dots), and the lidar-derived condensation level (green contour). These volume data show an expansive region of high reflectivity immediately above the fire perimeter. The reflectivity and plume height diminish towards the northeast, consistent with the fall out of the larger soot and ash particles in the downwind direction (e.g., southwest flow aloft). We note that since the radar is not sensitive to cloud droplets or micron-sized smoke, it is possible that the cloud edges and some smoke reside outside of the radar volume rendering. It is also clear from these data that the lidar sees only the leading edge of the plume before attenuating in dense smoke and cloud water, consistent with the analyses presented above.
The shape of particles within the plume can be inferred by considering the
differential reflectivity (
The lidar-observed condensation level and radar-estimated plume tops provide
valuable constraints on the plume structure when contextualized with
atmospheric profiles collected adjacent to the fire. Figure 9a, for example,
shows data from a radiosonde launched at 21:00 PDT from
Differential reflectivity (
Thermodynamic analysis of the ambient environment and plume parcels.
The sounding shows that the afternoon CBL extends from the surface (1364 m)
to
Relative to the observed profile, the “in cloud” profile is estimated by
pseudo-adiabatically lifting a parcel from the lidar-observed condensation
level at 5500 m. The resulting parcel possesses 910 J kg
Also of note, the homogeneous freezing level (
One of the main goals of this paper is to compare the observed plume properties with conventional estimates of condensational level and convective potential. To that end, in this subsection we consider each of the three lifted parcels described in Sect. 2.4 as representations of the observed plume. The parcel ascents are shown in Fig. 9b.
In this case, the MU parcel (red line, Fig. 9b) originates in the CBL and produces an LCL of 4367 m, which is more than 1 km lower than the lidar-observed condensation level. In addition, compared to the observed plume structure, the MU parcel possesses minimal CAPE and must overcome appreciable convective inhibition (CIN) before reaching its level of free convection. Similarly, the ML parcel encounters its LCL at 4641 m, possesses almost no CAPE, and also must overcome appreciable CIN (cyan line, Fig. 9b). The LCL for the ML parcel is higher than that of the MU parcel because the layer averaged mixing ratio is less than the maximum mixing ratio in the CBL.
Interestingly, the CONV parcel provides the best representation
of the observed plume (dark blue line, Fig. 9b). In this case the surface
mixing ratio is 5.2 g kg
From these analyses it is clear that the plume condensation level is substantively higher than the ambient LCL, supporting the results of Luderer et al. (2006, 2009). Further, using the CCL, not the LCL, and assuming that the fire readily exceeds the convective temperature, provides the best representation of the plume condensation level in this case. This is a potentially useful diagnostic for forecasters and fire managers. It should be noted, however, that the CONV parcel, and its associated dry-adiabat up to the CCL (dark blue line, Fig. 9b), does necessarily reflect the actual properties of the lower plume. Rather, the plume must be superadiabatic near its base, cooling largely due to entrainment as it decays towards adiabatic ascent further aloft (Emanuel, 1994; Trentmann et al., 2006; Freitas et al., 2007).
Rocky Fire progression map for 30 July 2015. The fire perimeters are from the US National Forest Service National Infrared Operations (NIROPS) flights. The background is a satellite image draped over the terrain, which is indicated with hill shading. Also shown are the truck location (yellow dot), lidar scan paths (colored lines), radiosonde location (yellow star), and weather station location (white star).
Visible satellite (GOES-15) images showing the difference in the Rocky Fire plume between 16:45 PDT on 29 and 30 July. The data show a pyroCu tower on 30 July that is absent on 29 July.
Pyrocumulus development from 15:59–16:09 PDT on 30 July 2015.
Pyrocumulus development from 18:05–18:13 PDT on 30 July 2015.
The Rocky Fire (38.9
Lidar RHI scans where conducted between 15:45 and 20:08 PDT from an already burned area within the Rocky Fire perimeter (Fig. 10). This location allowed for scans of four separate pyroCu plumes rising from the complex fire perimeter. A total of 267 RHI scans were performed.
PyroCu were first observed with the lidar starting at
By 16:03 PDT, however, a distinct cumuliform cloud had developed (Fig. 12b)
and the lidar backscatter showed a commensurate increase in intensity and
attenuation along the pyroCu edge (Fig. 12g). Based on these data the cloud
base was at
Another pyroCu event at 18:00 PDT is detailed in Fig. 13 corresponding to a
lidar azimuth of 86
The photographs detailing the plume rise show changes in smoke color near the base of the convective column (Fig. 13a–d). For example, at 18:05 PDT the smoke is a dark gray (Fig. 13a), whereas later the smoke is increasingly white (Fig. 13d). We believe the change in smoke coloration is associated with changes in the completeness of combustion: flaming combustion produces smoke dominated by black carbon aerosols, whereas smoldering combustion generates more organic carbon aerosol, which more effectively backscatter sunlight and appear whiter (Bellouin, 2014; Saleh et al., 2014).
An additional aspect of the observed plume rise is the relationship between
the updraft strength and the ambient wind. This relationship is examined in
Fig. 14, which displays VAD wind profiles (Fig. 14a and b) and RHI radial
velocities detailing the plume structure (Fig. 14c–e). The wind profiles
show significant shear over the lowest 2 km of the atmosphere. Strong
(5–7 m s
Compared to the ambient wind, the flow within the plume is characterized by
much stronger velocities (Fig. 14c and d). For example, outbound speeds in
excess of 15 m s
Analysis of the interaction of the plume with the ambient wind.
Statistical analysis of lidar data between 15:45 and 20:08 PDT on 30 July 2015.
Radar analysis of the Rocky Fire convective column.
Thermodynamic analysis of the ambient environment during the Rocky
Fire.
The RHI velocity data also show that the strength of the updraft diminished with time. For example, comparative histograms demonstrate that strong outbound velocities were both higher and more common at 18:09 than 18:13 PDT (Fig. 14e). This observation is consistent with the change in smoke coloration described above: flaming combustion is likely to produce stronger updrafts due to more rapid heat release.
Changes in plume geometry also accompany the reduction in updraft strength. The plume is at first mostly upright (Fig. 14c) and later becomes more sheared (Fig. 14d). Specifically, the leading plume edge becomes tilted downwind within the boundary layer, while the upper portion of the plume bends back towards the observing location. Based on these data, we hypothesize that as the fire's updraft weakens, it becomes more susceptible to the ambient shear. The role of wind shear as a limiting factor in plume development is further discussed below.
A more robust examination of the plume condensation level during the Rocky
Fire's multiple pyroCu events is presented in Fig. 15. These analyses
leverage the aggregated data from all of the RHI scans on 30 July.
Unsurprisingly, the time-maximum backscatter exhibit a sharp transition near
4200 m (Fig. 15a and b), as was indicated in the earlier plume rise sequences
(Figs. 12 and 13). Below 4200 m, the backscatter decays roughly linearly with
height, and above that level the backscatter converges to a value of near
Radar data are again used to estimate the maximum smoke injection depth. The
Rocky Fire was within
The maximum echo tops (from KDAX) occur between 7000 and 7500 m, consistent with the lidar cloud detections (Fig. 16a). The spatial pattern of echo tops indicate that plumes of similar height developed on all of the expanding flanks of the fire. Interestingly, the corresponding time series demonstrates the plume transience, showing rapid variations in plume height throughout the late afternoon (Fig. 16b). Each spike corresponds to a short-lived pyroCu with durations ranging from 10–30 min. Satellite data confirm the episodic nature of these plumes (not shown).
The variability in echo tops is also due to the presence of multiple updrafts. For example, a volume rendering of the reflectivity data at 16:09 PDT shows the two distinct updrafts associated with the complex fire perimeter (Fig. 16c). The narrow updraft rising from the northwestern flank of the fire is the same plume shown in Fig. 12, and the lidar plume detections agree well with the radar data (yellow dots, Fig. 16c). A second broader plume rises from the north and northeastern flanks of the fire at the same time. Above 5000 m the upper portions of both plumes are tilted to the north–northwest due to southeasterly flow in that layer. Later in the fire's evolution the plume growth shifted towards the east and southeast (not shown).
The Rocky Fire pyroCu development is interesting in that the thermodynamic
environment theoretically supports much deeper convection than was observed.
Using radiosonde data from
What then limits the growth? There appear to be two related limiting factors
in the plume rise: (1) wind shear, and (2) dry air entrainment. The lidar
wind profiles, presented above in Fig. 14, indicate significant wind shear
between the CBL and free troposphere. This wind shear is also apparent in
the radiosonde wind profile, which shows a 180
A second layer of significant wind shear at 7000 m separates the monsoon flow from southwesterly flow in the upper troposphere. This shear also coincides with a rapid decrease in dew point temperature, and thus relative humidity. It is notable then that the maximum echo tops occur only about 500 m above the upper shear layer. Visual observations throughout the afternoon and early evening suggest this shear zone affected the pyroCu development, tending to sweep the upper portion of the cloud away from the updraft core. The detraining upper portions of the cloud subsequently developed ragged and wispy edges indicative of dry air entrainment as opposed to the crisp crenelations of growing cumulus congestus.
Analysis of lifted parcels, showing the most unstable (MU), mixed-layer (ML), and convective (Conv) parcel trajectories. The condensation levels and CAPE for each parcel is described in the text.
Analysis of the environmental conditions on 29 and 30 July.
The effect of the wind shear on a buoyant parcel is easily visualized by
examining the ascent track of the radiosonde, which rose at a mean rate of
2.7 m s
Despite their limited vertical development, the Rocky Fire pyroCu provide
additional support for the hypothesis that the plume condensation level
occurs above the ambient LCL. Following the same procedures described for
the Bald Fire we examine three convective parcels, the ascents of which are
shown in Fig. 18. The LCLs for the MU and ML parcels are 3503 and 3768 m,
respectively (red and cyan lines, Fig. 18). Both of these lifted parcels
must overcome modest CIN to reach their level of free convection. In
contrast, the computed CCL of 4250 m is much closer to the lidar-observed
condensation level at
Figure 19a shows the GOES-15 and MODIS FRP in for the Rocky Fire on 29–30 July 2015. From these data it is clear that the diurnal cycle of fire intensity is similar during the first two days of fire growth, with peak FRP values near 1500 MW in the late afternoon and fire activity extending into the late evening. Interestingly, despite comparable fire intensity, pyroCus were not observed on 29 July but were widespread on 30 July.
To better understand this disparity Fig. 19b–e compares the ambient
meteorological conditions between days. These data are from a weather
station just outside the fire perimeter, the location of which is shown in
Fig. 10 (data obtained from MesoWest, Horel et al., 2002), and the 17:00 PDT
upper air soundings at Oakland International Airport (KOAK, location shown
in Fig. 1). The high temperature on both days was
Figure 19d and e show the time series of the water vapor mixing ratio and the
differences in the relative humidity from the KOAK soundings for two
afternoons. From these data it is apparent that the onset of pyroCus on
30 July corresponds to the arrival of much higher humidity air, both at the
surface and aloft. For example, the mixing ratio increases from 4.5 to
8 g kg
The observations presented in this paper demonstrate that plume condensation levels can exceed the height of the ambient LCL, sometimes substantially. For example, during the Bald Fire the plume condensation level was more than 1 km higher than the environmental LCL. As such, we conclude that the LCL should not be used, as it has been, as a parameter for assessing pyroCu/Cb potential outside of the limiting case where the CCL and LCL coincide, which is to say that widespread convective clouds are possible. While our observational results span a limited portion of the parameter space, they nonetheless provide strong support for the modeling results of Luderer et al. (2006, 2009) and Trentman et al. (2006), and seemingly contradict the results of Potter (2005).
While the CCL and the corresponding moist adiabatic ascent provide a useful approximation for plume properties, other factors must also be considered. Specifically, CAPE alone cannot determine the convective outcome. Our results from the Rocky Fire show, for example, that ambient wind shear and dry air entrainment can significantly curtail the convective development even in an environment that might otherwise support deep pyroCb. In addition, our results show that the change in environmental humidity, often in the form of a monsoonal surge, exerts a significant influence over the onset of pyroCus/Cbs by raising or lowering the height of CCL. These results suggest that the moisture release during combustion is of secondary importance, at least in these observed cases.
While our results mark an advance in understanding pyroCu/Cb development, there is a clear need for new measurement and modeling investigations of pyroconvective clouds. Future field campaigns should include observations of the ambient environment (e.g., radiosondes, CBL properties), the lower plume structure (temperature, moisture, and momentum fluxes), and cloud properties (e.g., liquid and ice water path, particle size distributions, etc.). These data should subsequently inform physical fluid dynamical models in order to investigate aspects of plume dynamics that may not be observable. Some potential avenues for obtaining these observations include dropsondes from aircraft, surface and aircraft based dual-polarization radars, unmanned aerial vehicles, and dual-Doppler lidar deployed during large-scale prescribed burn experiments where the fuel loading and extent of combustion is known or can be determined after the fact.
C. B. Clements conceived of the field program, N. P. Lareau and C. B. Clements conducted the field measurements, and N. P. Lareau led the data analysis and writing.
The lidar and radiosonde data are available upon request from the authors. All other data sources are publicly available. This research is supported under grant AGS-1151930 from the National Science Foundation. Christopher C. Camacho contributed to the field observations during the Rocky Fire. Edited by: P. Chuang