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Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the "firehose" of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.

During marine cold‐air outbreaks (MCAOs), when cold polar air moves over warmer ocean, a well‐recognized cloud pattern develops, with open or closed mesoscale cellular convection (MCC) at larger fetch over open water. The Cold‐Air Outbreaks in the Marine Boundary Layer Experiment provided a comprehensive set of ground‐based in situ and remote sensing observations of MCAOs at a coastal location in northern Norway. MCAO periods that unambiguously exhibit open or closed MCC are determined. Individual cells observed with a profiling Ka‐band radar are identified using a watershed segmentation method. Using self‐organizing maps (SOMs), these cells are then objectively classified based on the variability in their vertical structure. The SOM nodes contain some information about the location of the cell transect relative to the center of the MCC. This adds classification noise, requiring numerous cell transects to isolate cell dynamical information. The SOM‐based classification shows that comparatively intense convection occurs only in open MCC. This convection undergoes an apparent lifecycle. Developing cells are associated with stronger updrafts, large spectrum width, larger amounts of liquid water, lower surface precipitation rates, and lower cloud tops than mature and weakening cells. The weakening of these cells is associated with the development of precipitation‐induced cold pools. The SOM classification also reveals less intense convection, with a similar lifecycle. More stratiform vertical cloud structures with weak vertical motions are common during closed MCC periods and are separated into precipitating and non‐precipitating stratiform cores. Convection is observed only occasionally in the closed MCC environment. Plain Language Summary: During marine cold‐air outbreaks a characteristic cloud field develops over the open ocean. At large fetch, this cloud field is characterized by open and closed mesoscale cellular convection (MCC). The Cold‐Air Outbreaks in the Marine Boundary Layer Experiment in northern Norway provided comprehensive observations of mixed‐phase MCC using ground‐based and remote sensing instruments. Distinct open or closed MCC periods are identified using a vertically pointing cloud radar. Within these periods individual cells are identified. Using a machine learning algorithm, these cells are objectively classified based on their vertical structure as observed by the radar. The classification reveals that intense convection primarily occurs in open MCC, displaying a lifecycle with developing cells characterized by strong updrafts, substantial liquid water, lower precipitation rates, and lower cloud tops compared to mature and weakening cells. Weakening cells are associated with precipitation‐induced cold pools. Less intense convection with a similar lifecycle is observed during open and closed MCC. Most frequently during closed MCC, stratiform cells with weak vertical motions are observed, some of them without precipitation reaching the surface. The vertical cloud structure of the precipitating stratiform cells is very similar to weakening convective cells. Key Points: Cloud cells in marine cold‐air outbreaks are objectively identified and classified using a profiling mm‐wave radarThe classification reveals that open‐cellular clouds undergo a convective lifecycle with distinct characteristics at each lifecycle stageClosed‐cellular clouds contain occasional convection but generally have more stratiform characteristics [ABSTRACT FROM AUTHOR]

The intensity and frequency of wildfires in California (CA) have increased in recent years, causing significant damage to human health and property. In October 2007, a number of small fire events, collectively referred to as the Witch Creek Fire or Witch Fire started in Southern CAand intensified under strong Santa Ana winds. As a test of current mesoscale modeling capabilities, we use the Weather Research and Forecasting (WRF) model to simulate the 2007 wildfire event in terms of meteorological conditions. The main objectives of the present study are to investigate the impact of horizontal grid resolution and planetary boundary layer (PBL) scheme on the model simulation of meteorological conditions associated with a Mega fire. We evaluate the predictive capability of the WRF model to simulate key meteorological and fire-weather forecast parameters such as wind, moisture, and temperature. Results of this study suggest that more accurate predictions of temperature and wind speed relevant for better prediction of wildfire spread can be achieved by downscaling regional numerical weather prediction products to 1 km resolution. Furthermore, accurate prediction of near-surface conditions depends on the choice of the planetary boundary layer parameterization. The MYNN parameterization yields more accurate prediction as compared to the YSU parameterization. WRF simulations at 1 km resolution result in better predictions of temperature and wind speed than relative humidity during the 2007 Witch Fire. In summary, the MYNN PBL parameterization scheme with finer grid resolution simulations improves the prediction of near-surface meteorological conditions during a wildfire event. [ABSTRACT FROM AUTHOR]

Improving the calculation of land‐atmosphere fluxes of heat and water vapor in mountain terrain requires better resolution of thermally driven diurnal winds (i.e., valley, slope winds) due to differential heating by terrain and radiative fluxes. In this study, the Weather Research and Forecasting model is used to simulate flow in large‐eddy simulation (LES) mode over the complex terrain of the Fortress Mountain and Marmot Creek research basins, Kananaskis Valley, Canadian Rockies, Alberta in mid‐summer. The model was used to examine the temporal and spatial evolution of local winds and near‐surface boundary layer processes with variability in topography and elevation. Numerically resolving complex terrain wind flow effects require smaller grid cell size. However, the use of terrain‐following coordinates in most numerical weather prediction models results in large numerical errors when flow over steep terrain is simulated. These errors propagate through the domain and can result in numerical instability. To avoid this issue when simulating flow over steep terrain a local smoothing approach was used, where smoothing is applied only where slope exceeds some predetermined threshold. LES results from local smoothing were compared with a mesoscale model and LES with global smoothing. Simulations are evaluated using sounding data and meteorological stations. The differences in flow patterns and reversals in two mountain basins suggest that valley geometry and volume is relevant to the break up of inversion layers, removal of cold‐air pools, and strength of thermally driven winds. Key Points: Large‐eddy simulations in complex terrain utilizing smoothing techniques resolve thermally driven mountain flowsMesoscale flow interactions with mountainous terrain can influence valley windsTopographical differences in mountain basins affects local flows and cold‐air pooling [ABSTRACT FROM AUTHOR]

Following the destructive Lahaina Fire in Hawaii, our team has modeled the wind and fire spread processes to 10 understand the drivers of this devastating event. The results are in good agreement with observations recorded during the event. Extreme winds with high variability, a fire ignition close to the community, and construction characteristics led to continued fire spread in multiple directions. Our results suggest that available modeling capabilities can provide vital information to guide decision-making and emergency response management during wildfire events. [ABSTRACT FROM AUTHOR]