There is an increasing need for simulating the evolution of wildland fires. The realism of the simulation increases by accounting for feedbacks between the fire and the atmosphere. These coupled models combine a fire behavior model with a regional numerical weather prediction model and have been used for fire research during the last few decades. This is the case, for instance, for the widely adopted Weather Research and Forecasting model with fire extensions (WRF-Fire). Typically, the coupling includes specific code for the particular models being coupled such as interpolation procedures to exchange variables between the atmospheric grid to the fire grid, and vice versa. However, having a fire modeling framework that can be coupled to different atmospheric models is advantageous to foster collaborations and joint developments. With this aim, we have created, for the first time, a fire behavior model that can be connected to other atmospheric models without the need for developing specific low-level procedures for the particular atmospheric model being used. To this end, the fire behavior model, referred to as the Community Fire Behavior model (CFBM), makes use of the Earth System Modeling Framework (ESMF) library to communicate information between the fire and the atmosphere. More specifically, CFBM is available as a national unified operational prediction capability (NUOPC) component which allows for an agnostic coupling to atmospheric models and other Earth system components. CFBM closely follows WRF-Fire version 4.3.3 methods in its version 0.2.0 which allows us to verify the adequacy of our implementation. The CFBM can be also run offline using an existing WRF simulation to propagate the fires in what we refer to as the standalone model. Herein we describe CFBM and its implementation in the Unified Forecast System (UFS). Simulations of the Cameron Peak Fire performed with UFS and WRF-Fire are presented to compare results from both models in order to verify our implementation. Results from both models, as well as with the standalone version, are consistent indicating a proper development of the CFBM and its coupling to the UFS-Atmosphere. This is the starting point to go beyond WRF-Fire methods and improve the realism of the simulations in the future. The possibility of using the fire behavior model with other atmospheric models provides an attractive collaborative framework to further improve the realism of the CFBM model in order to meet the growing demand for accurate wildland fire simulations.

Accurate wildfire spread modeling critically depends on the representation of wind dynamics, which vary with terrain, land cover characteristics, and height above ground. Many fire spread models are often coupled with coarse atmospheric grids that cannot explicitly resolve the vertical variation of wind near flame heights. Rothermel’s fire spread model, a widely used parameterization, relies on midflame wind speed to calculate the fire rate of spread. In coupled fire atmosphere models such as the Community Fire Behavior Model (CFBM), users are required to specify the midflame height before running a fire spread simulation. This study evaluates the use of logarithmic interpolation wind adjustment factors (WAF) for improving midflame wind speed estimates, which are critical for the Rothermel model. We compare the fixed wind height approach that is currently used in CFBM with WAF-derived winds for unsheltered and sheltered surface fire spread. For the first time in this context, these simulations are validated against satellite and ground-based observations of fire perimeters. The results show that WAF implementation improves fire perimeter predictions for both grass and canopy fires while reducing the overestimation of fire spread. Moreover, this approach solely depends on the fuel bed depth and estimation of canopy density, enhancing operational efficiency by eliminating the need for users to specify a wind height for simulations.

On 30 December 2021, the Marshall Fire devastated the Boulder, Colorado region. The fire initiated in fine fuels in open space just southeast of Boulder and spread rapidly due to the strong, downslope winds that penetrated into the Boulder Foothills. Despite the increasing occurrence of wildland-urban interface (WUI) disasters, many questions remain about how fires progress through vegetation and the built environment. To help answer these questions for the Marshall Fire, we use a coupled fire-atmosphere model and Doppler on Wheels (DOW) observations to study the fire's progression as well as examine the physical drivers of its spread. Evaluation of the model using the DOW suggests that the model is able to capture general characteristics of the flow field; however, it does not produce as robust of a hydraulic jump as the one observed. Our results highlight limitations of the model that should be addressed for successful WUI simulations.

Smoke from wildfires or burning biomass directly affects air quality and weather through modulating cloud microphysics and radiation. A simple wildfire emission coupling of black carbon (BC) and organic carbon (OC) with microphysics was implemented using the Weather Research and Forecasting model's fire module. A set of large‐eddy simulations inspired by unique surface and upper atmospheric observations from the 2021 Santa Coloma de Queralt Fire (Spain) were conducted to investigate the influence of background conditions and interactions between atmospheric and fire processes such as fire smoke, ambient moisture, and latent heat release on the formation and evolution of pyroconvective clouds. While the microphysical impact of BC and OC emissions on the dynamics of fire behavior is minimal on short time scales (<6 hr), their presence increased the cloud water content and decreased the rain rates in our case study. In our case study, atmospheric moisture played an important role in the formation and development of pyroconvective clouds, which in turn enhanced the surface winds (8%) and fire spread rate (25%). The influence of fuel moisture on the pyroconvective cloud formation is smaller when compared with the atmospheric moisture content. A better representation of cloud processes can improve the mesoscale forecasts, which is important for better fire behavior modeling.

Generating accurate weather forecasts of planetary boundary layer (PBL) properties is challenging in many geographical regions, oftentimes due to complex topography or horizontal variability in, for example, land characteristics. While recent advances in high-performance computing platforms have led to an increase in the spatial resolution of numerical weather prediction (NWP) models, the horizontal gridcell spacing (Delta x) of many regional-scale NWP models currently fall within or are beginning to approach the gray zone (i.e., Delta Dx approximate to 100-1000 m). At these gridcell spacings, three-dimensional (3D) effects are important, as the most energetic turbulent eddies are neither fully parameterized (as in traditional meso-scale simulations) nor fully resolved [as in traditional large-eddy simulations (LES)]. In light of this modeling challenge, we have implemented a 3D PBL parameterization for high-resolution mesoscale simulations using the Weather Research and Forecasting Model. The PBL scheme, which is based on the algebraic model developed by Mellor and Yamada, accounts for the 3D effects of turbulence by calculating explicitly the momentum, heat, and moisture flux divergences in addition to the turbulent kinetic energy. In this study, we present results from idealized simulations in the gray zone that illustrate the benefit of using a fully consistent turbulence closure framework under convective conditions. While the 3D PBL scheme reproduces the evolution of convective features more appropriately than the traditional 1D PBL scheme, we highlight the need to improve the turbulent length scale formulation. SIGNIFICANCE STATEMENT: The spatial resolution of weather models continues to increase at a rapid rate in accordance with the enhancement of computing power. As a result, smaller-scale atmospheric features become more explicitly resolved. However, most numerical models still ignore the impact of horizontal weather variations on boundary layer flows, which becomes more important at these smaller spatial scales. To address this issue, we have implemented a new modeling approach, using fundamental principles, which accounts for horizontal variability. Our results show that including three-dimensional effects of turbulence is necessary to achieve realistic boundary layer characteristics. This novel technique may be useful for many applications including complex terrain flows, pollutant dispersion, and surface-atmosphere interaction studies.

Accurate representation of heterogeneous surface layer processes is essential for numerical weather prediction (NWP) with sub-kilometer grid spacing. NWP models such as the Weather Research and Forecasting (WRF) model generally use second-moment turbulent models for parameterizing the planetary boundary layer (PBL). The most common parameterizations follow Mellor and Yamada (1982) and account for the vertical turbulent mixing only, that is, standard PBL parameterizations are one-dimensional (1DPBL). The horizontal diffusion of momentum is parameterized based on Smagorinsky’s (1963) model for numerical stability. Although the combination of 1DPBL and 2D Smagorinsky parameterizations is successful at coarse grid resolutions (e.g., grid-size dx ∼ 12 – 2 km), it does not represent well the effect of horizontal turbulence as grid-cell size decreases (< 1 km). To reconcile the representation of vertical and horizontal turbulent mixing, a full three-dimensional PBL scheme (3DPBL) based on the Mellor and Yamada model was implemented in WRF. The 3DPBL uses the horizontal and vertical turbulent fluxes diagnosed from the flow gradients to handle the turbulent mixing. These gradients cannot be directly calculated near the surface. Therefore, the 3DPBL parameterization is coupled herein to a second-order diagnostic model of the three-dimensional turbulent fluxes in the surface layer. Several adjustments to the original Mellor and Yamada model, including a modified length-scale, were introduced to capture flow anisotropy and dependence on stability conditions. The results are compared against data from the Wind Forecast Improvement Project 2 (WFIP2) for different weather regimes and using different grid resolutions to examine stability- and scale-dependency.

Wind energy applications including wind resource assessment, wind power forecasting, and wind plant optimization require high-resolution mesoscale simulations. High resolution mesoscale simulations are essential for accurate characterization of atmospheric flows over heterogeneous land use and complex terrain. Under such conditions, the assumption of grid-cell homogeneity, used in one-dimensional planetary boundary layer (1D PBL) parameterizations, breaks down. However, in most numerical weather prediction (NWP) models, boundary layer turbulence is parameterized using 1D PBL parameterizations. We have therefore developed a three-dimensional (3D) PBL parameterization to better account for horizontal flow heterogeneities. We have implemented and tested the 3D PBL parameterization in the Weather Research and Forecasting (WRF) numerical weather prediction model. The new parameterization is validated using observations from the Wind Forecast Improvement 2 (WFIP 2) project and compared to 1D PBL results.

This study examines the implications of Tropical Montane Forests (TMFs) loss on orographic precipitation in the Eastern slopes of the Andes (EADS). The focus is on moist processes for synoptic regimes associated with significant EADS precipitation: (1) monsoon rainfall for weak and strong South America Low-Level Jet (LLJ) conditions and (2) heavy rainfall associated with cold air intrusions (CAI) in the dry season. High-resolution simulations using the Weather Research and Forecasting (WRF) model were conducted for realistic and modified land-cover resulting from the conversion of TMFs to savanna. The deforestation scenarios result in 50–100% decrease (up to ∼400 J kg –1 ) in Convective Available Potential Energy (CAPE) spatially organized by land-cover change along the EADS. Analysis of the differences in simulated frequency distributions of rainfall intensity shows robust daytime increases in light rainfall (<2 mm h –1 ) and decreases in moderate rainfall rates (2–10 mm h –1 ) in the altitudinal band 500–2,000 m where orographic enhancement is dominant. Whereas there are negligible changes in the spatial patterns of precipitation and hydrologic response for monsoon conditions, rainfall accumulations decrease for all cases, and the precipitation maxima shift downslope into the Amazon lowlands. Changes in rainfall amount and intensity result in runoff decreases of 5–10% at the event-scale for the CAI case. Sensitivity simulations for lower initial soil moisture conditions indicate a strong positive feedback of forest loss to hydrologic drought along the EADS foothills in the austral spring when CAIs play a key role in the tropical EADS dry season hydrometeorology.

Abstract Previous work showed that atmospheric model simulations exhibit different scaling behavior of vertically averaged horizontal wind (u,v) and moisture (q) in the mesoscales for convective (spectral slopes β~−5/3) and nonconvective (β~−11/5) conditions. Here, the focus is on the transient behavior of horizontal scaling in the vertical during the evolution of extreme orographic precipitation storms in middle (Appalachians, <2,500m) and high mountains (Andes). The results show that β exhibits a strong diurnal cycle switching between convective and nonconvective behavior following the space‐time evolution of atmospheric stability in the lower troposphere (below 700 hPa) depending on latitude, topography, landform, and the synoptic environment. Anomalous flattening of the wind and moisture spectra (i.e., spectral saturation, ∣β ∣ < 5/3) at high wavenumbers and up to 200 hPa is tied to convective activity, where and when strong vertical motions develop, corresponding to an abrupt directional switch from horizontal energy transfer to vertical energy transfer including latent heating release and parameterized microphysical processes. In the small mesoscales (<50 km), β~ − 5/3 at all times up to 200 hPa with nighttime steepening (β~−11/5) below the orographic envelope where cold air pools form at low elevations and vertical motion weakens in the Appalachians. In the Andes, the scaling behavior exhibits a stronger diurnal cycle at low levels (below 700 hPa) with significant shoaling between tropical and high latitudes. Blocking and strong modification of regional circulations result in nighttime anisotropy at midlevels on the altitudinal profile along the North‐South topographic divide.

Long-duration localized heavy rainfall (> 6 hours, < 10 km2) was recorded by raingauges on October 4, 2013 at mid-elevations (~1,500 m) in the Peruvian Andes, which was not apparent in infrared or microwave measurements from either geostationary or polar orbiting satellites. This spring event is investigated here through a numerical modeling study using the Weather and Research Forecasting (WRF) model, and examined in the context of the climatology of Cold Air Intrusions (CAIs) along the eastern flanks of the tropical Andes. The model results suggest significant precipitation enhancement from intense shallow convection at the CAI frontal boundary amplified by orographic lifting as it propagates northward latched to the slopes of Andes. Analysis of CAI mesoscale dynamics was conducted using four decades of European Center Medium-Range Weather Forecasts (ECMWF) reanalysis, Tropical Rainfall Measurement Mission (TRMM) data products, and rain-gauge observations with emphasis on characterizing year-round CAI frequency, CAI interactions with Andes topography, and their impact on orographic precipitation climatology. The data show a robust enhancement of the diurnal cycle of precipitation during CAI events in all seasons, and in particular increases in surface rainfall rate during early morning at intermediate elevations (~ 1,500 m), that is the eastern Andes orographic maximum. This link between CAI frequency and rainfall suggests that they play an important role in maintaining the Andes to Amazon year-round terrestrial connectivity through runoff production and transport by the river networks.

AbstractUnderstanding the development of the atmospheric energy spectrum across scales is necessary to elucidate atmospheric predictability. In this manuscript, the authors investigate energy transfer between the synoptic scale and the mesoscale using direct numerical simulations (DNSs) of two-dimensional (2D) turbulence transfer under forcing applied at different scales. First, DNS results forced by a single kinetic energy source at large scales show that the energy spectra slopes of the direct enstrophy cascade are steeper than the theoretically predicted −3 slope. Second, the presence of two inertial ranges in 2D turbulence at intermediate scales is investigated by introducing a second energy source in the meso-α-scale range. The energy spectra for the DNS with two kinetic energy sources exhibit flatter slopes that are closer to −3, consistent with the observed kinetic energy spectra of horizontal winds in the atmosphere at synoptic scales. Further, the results are independent of model resolution and s...