Climatological analyses of low-level jets (LLJs) can be negatively influenced by the coarse spatial and temporal resolution and frequent changes in observing and archiving protocols of rawinsonde observations (raobs). The introduction of reanalysis datasets, such as the North American Regional Reanalysis (NARR), provides new resources for climatological research with finer spatial and temporal resolution and potentially fewer inhomogeneities. To assess the compatibility of LLJ characteristics identified from NARR wind profiles with those obtained from raob profiles, LLJs were extracted using standard jet definitions from NARR and raobs at 12 locations in the central United States for four representative years that reflect different rawinsonde protocols. LLJ characteristics (e.g., between-station differences in relative frequency, diurnal fluctuations, and mean speed and elevation) are generally consistent, although absolute frequencies are smaller for NARR relative to raobs at most stations. LLJs are concurrently identified in the NARR and raob wind profiles on less than 60% of the observation times with LLJ activity. Variations are seen between analysis years and locations. Of particular note is the substantial increase in LLJ frequency seen in raobs since the introduction of the Radiosonde Replacement System, which has led to a greater discrepancy in jet frequency between the NARR and raob datasets. The analyses suggest that NARR is a viable additional resource for climatological analyses of LLJs. Many of the findings are likely applicable for other fine-resolution reanalysis datasets, although differences between reanalyses require that each be carefully evaluated before its use in climatological analyses of wind maxima.

The impact of a forest canopy on smoke concentration is assessed by applying a numerical weather prediction model coupled with a Lagrangian particle dispersion model to two low-intensity wildland (prescribed) fires in the New Jersey Pine Barrens. A comparison with observations indicates that the coupled numerical model can reproduce some of the observed variations in surface smoke concentrations and plume heights. Model sensitivity analyses highlight the effect of the forest canopy on simulated meteorological conditions, smoke concentrations, and plume heights. The forest canopy decreases near-surface wind speed, increases buoyancy, and increases turbulent mixing. Sensitivities to the time of day, plant area density profiles, and fire heat fluxes are documented. Analyses of temporal variations in smoke concentrations indicate that the effect of the transition from a daytime to a nocturnal planetary boundary layer is weaker when sensible heat fluxes from the fires are stronger. The results illustrate the challenges in simulating meteorological conditions and smoke concentrations at scales where interactions between the fire, fuels, and atmosphere are critically important. The study demonstrates the potential for predictive tools to be developed and implemented that could help fire and air-quality managers assess local air-quality impacts during low-intensity wildland fires in forested environments.

Lower-tropospheric wind maxima, known as low-level jets (LLJs), play a vital role in weather and climate around the world. In this study, two 10-year (2006–2015) regional climate simulations using current (2011) and future (2100) land-use/land-cover (LULC) patterns over the continental United States (CONUS) are used to assess the sensitivity of LLJ properties, including jet occurrence, maximum speed, and the elevation of the maximum, to changes in LULC. The three simulated LLJ properties exhibit greater sensitivity in summer than in winter. Summertime jets are projected to increase in frequency in the central CONUS, where cropland replaces grassland, and decrease in parts of the Ohio-River Valley and the Southeast, particularly Florida, where urban expansion occurs. Little change is projected for wintertime jet frequency. Larger modifications to jet speed and elevations are projected in parts of the Ohio River Valley, the upper Southeast, and the Intermountain West. While there is some evidence of weaker, more elevated jets with urban expansion, the connection between changes in jet speed and elevation and changes in LULC patterns at a given location is weak. This result suggests that LULC will primarily affect the large-scale atmospheric conditions that contribute to the formation of LLJs, particularly in winter.

We have demonstrated the use of an advanced Gaussian-Process (GP) emulator to estimate wildland fire emissions over a wide range of fuel and atmospheric conditions. The Fire Emission Production Simulator, or FEPS, is used to produce an initial set of emissions data that correspond to some selected values in the domain of the input fuel and atmospheric parameters for the purpose of training the emulator. The emulated emissions are found to be within ±5% of the FEPS simulated emissions, providing confidence in the potential use of the GP-emulator for this and other similar applications.Cluster analysis for 1000 emulator-produced posterior samples spanning a wide-range of fuel and environmental conditions suggest that the emulator not only produces valid results but also preserves the physical relationships between the fire emission and the fuel and environmental conditions. Results show that the GP-emulator could be used as an alternative to the simulations from the FEPS modeling system when four or more input parameters related to fuel type, fuel moisture, and weather condition are allowed to vary.This work also provides a conceptual basis for constructing a nation-wide emissions inventory based on a trained GP-emulator representing the complex geographic distribution of fuel types and environmental conditions.

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