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Sorenson et al. (2024) studied fresh smoke plumes from the proximal Dixie fire in northern California and concluded that the smoke cooled the air and Earth surface below the smoke by shielding of incoming solar radiation. The so-attributed cooling was immediate, sudden and on par with diurnal temperature variations. This comment takes issue with their conclusions, reasoning, and method. By examining the same case and others, it is shown that the observed cooling within the smoke plume is caused by plume particulates sufficiently large to intercept and thereby alter upwelling thermal infrared radiation. The evidence presented is the same satellite and radar data employed by Sorenson et al. (2024), but expanded with temporal animations. A key element of the new analysis is the demonstration of smoke-associated cooling at nighttime, a circumstance decoupled from the solar-shielding explanation. The refutation of the proposed solar-shield-cooling in fresh smokes is an essential refinement of the constraints on the radiative cause-effect in such conditions.

Arabidopsis plants subjected to a daily dehydration stress and watered recovery cycle display physiological and transcriptional stress memory. Previously stressed plants have stomatal apertures that remain partially closed during a watered recovery period, facilitating reduced transpiration during a subsequent dehydration stress. Guard cells (GCs) display transcriptional memory that is similar to that in leaf tissues for some genes, but display GC‐specific transcriptional memory for other genes. The rate‐limiting abscisic acid (ABA) biosynthetic genes NINE‐CIS‐EPOXYCAROTENOID DIOXYGENASE 3 (NCED3) and ALDEHYDE OXIDASE 3 (AAO3) are expressed at much higher levels in GCs, particularly during the watered recovery interval, relative to their low levels in leaves. A genetic analysis using mutants in the ABA signaling pathway indicated that GC stomatal memory is ABA‐dependent, and that ABA‐dependent SNF1‐RELATED PROTEIN KINASE 2.2 (SnRK2.2), SnRK2.3 and SnRK2.6 have distinguishable roles in the process. SnRK2.6 is more important for overall stomatal control, while SnRK2.2 and SnRK2.3 are more important for implementing GC stress memory in the subsequent dehydration response. Collectively, our results support a model of altered ABA production in GCs that maintains a partially closed stomatal aperture during an overnight watered recovery period.

Monitoring tree regeneration in forest areas disturbed by resource extraction is a requirement for sustainably managing the boreal forest of Alberta, Canada. Small remotely piloted aircraft systems (sRPAS, a.k.a. drones) have the potential to decrease the cost of field surveys drastically, but produce large quantities of data that will require specialized processing techniques. In this study, we explored the possibility of using convolutional neural networks (CNNs) on this data for automatically detecting conifer seedlings along recovering seismic lines: a common legacy footprint from oil and gas exploration. We assessed three different CNN architectures, of which faster region-CNN (R-CNN) performed best (mean average precision 81%). Furthermore, we evaluated the effects of training-set size, season, seedling size, and spatial resolution on the detection performance. Our results indicate that drone imagery analyzed by artificial intelligence can be used to detect conifer seedling in regenerating sites with high accuracy, which increases with the size in pixels of the seedlings. By using a pre-trained network, the size of the training dataset can be reduced to a couple hundred seedlings without any significant loss of accuracy. Furthermore, we show that combining data from different seasons yields the best results. The proposed method is a first step towards automated monitoring of forest restoration/regeneration.

In 2017, western Canadian wildfires injected smoke into the stratosphere that was detectable by satellites for more than 8 months. The smoke plume rose from 12 to 23 kilometers within 2 months owing to solar heating of black carbon, extending the lifetime and latitudinal spread. Comparisons of model simulations to the rate of observed lofting indicate that 2% of the smoke mass was black carbon. The observed smoke lifetime in the stratosphere was 40% shorter than calculated with a standard model that does not consider photochemical loss of organic carbon. Photochemistry is represented by using an empirical ozone-organics reaction probability that matches the observed smoke decay. The observed rapid plume rise, latitudinal spread, and photochemical reactions provide new insights into potential global climate impacts from nuclear war.

The Black Summer fire season of 2019–2020 in southeastern Australia contributed to an intense ‘super outbreak’ of fire-induced and smoke-infused thunderstorms, known as pyrocumulonimbus (pyroCb). More than half of the 38 observed pyroCbs injected smoke particles directly into the stratosphere, producing two of the three largest smoke plumes observed at such altitudes to date. Over the course of 3 months, these plumes encircled a large swath of the Southern Hemisphere while continuing to rise, in a manner consistent with existing nuclear winter theory. We connect cause and effect of this event by quantifying the fire characteristics, fuel consumption, and meteorology contributing to the pyroCb spatiotemporal evolution. Emphasis is placed on the unusually long duration of sustained pyroCb activity and anomalous persistence during nighttime hours. The ensuing stratospheric smoke plumes are compared with plumes injected by significant volcanic eruptions over the last decade. As the second record-setting stratospheric pyroCb event in the last 4 years, the Australian super outbreak offers new clues on the potential scale and intensity of this increasingly extreme fire-weather phenomenon in a warming climate.

The Australian bushfires of 2019/20 produced an unusually large number of pyrocumulonimbus (pyroCb) that injected huge amounts of smoke into the lower stratosphere. The pyroCbs from 29 December 2019 to 4 January 2020 were particularly intense, producing hemispheric-wide aerosol that persisted for months. One plume from this so-called Australian New Year (ANY) event evolved into a stratospheric aerosol mass ~1000 km across and several kilometers thick. This plume initially moved eastward toward South America in January, then reversed course and moved westward passing south of Australia in February and eventually reached South Africa in early March. The peculiar motion was related to the steady rise in plume potential temperature of ~8 K day −1 in January and ~6 K day −1 in February, due to local heating by smoke absorption of solar radiation. This heating resulted in a vertical temperature anomaly dipole, a positive potential vorticity (PV) anomaly, and anticyclonic circulation. We call this dynamical component of the smoke plume “smoke with induced rotation and lofting” (SWIRL). This study uses Navy Global Environmental Model (NAVGEM) analyses to detail the SWIRL structure over 2 months. The main diagnostic tool is an anticyclone edge calculation based on the scalar Q diagnostic. This provides the framework for calculating the time evolution of various SWIRL properties: PV anomaly, streamfunction, horizontal size, vertical thickness, flow speed, and tilt. In addition, we examine the temperature anomaly dipole, the SWIRL interaction with the large-scale wind shear, and the ozone anomaly associated with lofting of air from the lower to the middle stratosphere.

The highlight of the meanwhile 50 years of lidar-based aerosol profiling at Garmisch-Partenkirchen has been the measurements of stratospheric aerosol since 1976. After a technical breakdown in 2016, they have been continued with a new, much more powerful system in a vertical range up to almost 50 km a.s.l. (above sea level) that allowed for observing very weak volcanic aerosol up to almost 40 km. The observations since 2017 are characterized by a number of spectacular events, such as the Raikoke volcanic plume equalling in integrated backscatter coefficient that of Mt St Helens in 1981 and severe smoke from several big fires in North America and Siberia with backscatter coefficients up to the maximum values after the Pinatubo eruption. The smoke from the violent 2017 fires in British Columbia gradually reached more than 20 km a.s.l., unprecedented in our observations. The sudden increase in frequency of such strong events is difficult to understand. Finally, the plume of the spectacular underwater eruption on the Tonga Islands in the southern Pacific in January 2022 was detected between 20 and 25 km.

Plants transmit signals long distances, as evidenced in grafting experiments that create distinct rootstock-scion junctions. Noncoding small RNA is a signaling molecule that is graft transmissible, participating in RNA-directed DNA methylation; but the meiotic transmissibility of graft-mediated epigenetic changes remains unclear. Here, we exploit the MSH1 system in Arabidopsis and tomato to introduce rootstock epigenetic variation to grafting experiments. Introducing mutations dcl2 , dcl3 and dcl4 to the msh1 rootstock disrupts siRNA production and reveals RdDM targets of methylation repatterning. Progeny from grafting experiments show enhanced growth vigor relative to controls. This heritable enhancement-through-grafting phenotype is RdDM-dependent, involving 1380 differentially methylated genes, many within auxin-related gene pathways. Growth vigor is associated with robust root growth of msh1 graft progeny, a phenotype associated with auxin transport based on inhibitor assays. Large-scale field experiments show msh1 grafting effects on tomato plant performance, heritable over five generations, demonstrating the agricultural potential of epigenetic variation. The meiotic transmissibility and progeny phenotypic influence of graft-mediated epigenetic changes remain unclear. Here, the authors use the msh1 mutant in the rootstock to trigger heritable enhanced growth vigor in Arabidopsis and tomato, and show it is associated with the RNA-directed DNA methylation pathway.

The 2013 Rim Fire, which burned over 104,000 ha, was one of the most severe fire events in California’s history, in terms of its rapid growth, intensity, overall size, and persistent smoke plume. At least two large pyrocumulonimbus (pyroCb) events were observed, allowing smoke particles to extend through the upper troposphere over a large portion of the Pacific Northwest. However, the most extreme fire spread was observed on days without pyroCb activity or significant regional convection. A diverse archive of ground, airborne, and satellite data collected during the Rim Fire provides a unique opportunity to examine the conditions required for both extreme spread events and pyroCb development. Results highlight the importance of upper-level and nocturnal meteorology, as well as the limitations of traditional fire weather indices. The Rim Fire dataset also allows for a detailed examination of conflicting hypotheses surrounding the primary source of moisture during pyroCb development. All pyroCbs were associated with conditions very similar to those that produce dry thunderstorms. The current suite of automated forecasting applications predict only general trends in fire behavior, and specifically do not predict 1) extreme fire spread events and 2) injection of smoke to high altitudes. While these two exceptions are related, analysis of the Rim Fire shows that they are not predicted by the same set of conditions and variables. The combination of numerical weather prediction data and satellite observations exhibits great potential for improving automated regional-scale forecasts of fire behavior and smoke emissions.

The first observationally based conceptual model for intense pyrocumulonimbus (pyroCb) development is described by applying reanalyzed meteorological model output to an inventory of 26 intense pyroCb events from June to August 2013 and a control inventory of intense fire activity without pyroCb. Results are based on 88 intense wildfires observed within the western United States and Canada. While surface-based fire weather indices are a useful indicator of intense fire activity, they are not a skillful predictor of intense pyroCb. Development occurs when a layer of increased moisture content and instability is advected over a dry, deep, and unstable mixed layer, typically along the leading edge of an approaching disturbance or under the influence of a monsoonal anticyclone. Upper-tropospheric dynamics are conducive to rising motion and vertical convective development. Mid- and upper-tropospheric conditions therefore resemble those that produce traditional dry thunderstorms. The specific quantity of midlevel moisture and instability required is shown to be strongly dependent on the surface elevation of the contributing fire. Increased thermal buoyancy from large and intense wildfires can serve as a potential trigger, implying that pyroCb occasionally develop in the absence of traditional meteorological triggering mechanisms. This conceptual model suggests that meteorological conditions favorable for pyroCb are observed regularly in western North America. PyroCb and ensuing stratospheric smoke injection are therefore likely to be significant and endemic features of summer climate. Results from this study provide a major step toward improved detection, monitoring, and prediction of pyroCb, which will ultimately enable improved understanding of the role of this phenomenon in the climate system.