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Hourly data for sulfur dioxide (SO 2 ), nitrogen oxides (NO x ), and inhalable particulate matter (PM 10 ) over a 33-month period from a network of air quality monitoring stations across Qingdao, a major coastal city in eastern China, along with surface and upper-air meteorological data, are used to characterize the spatiotemporal variability of these pollutants in the region and the role of meteorological conditions play in pollution episodes. Large differences in the concentrations of all three pollutants are found between densely populated or industrial areas and suburban commercial or residential or coastal tourist areas, but the differences are relatively small between older and newer parts of the residential-commercial areas and between old and newly developed industrial areas. Wavelet analyses revealed a strong seasonal cycle for all three pollutants, introseasonal variability with a periodicity depending on pollutant and location, and diurnal and a semi-diurnal variability with season-dependent amplitude and phase. Low wind speed is found to be the leading factor for pollution buildup in the region. These results may prove useful for urban planning and development and implementation of effective air pollution control strategies for other coastal regions with economic development similar to Qingdao.

The ambient atmospheric environment affects the growth and spread of wildland fires, whereas heat and moisture released from the fires and the reduction of the surface drag in the burned areas can significantly alter local atmospheric conditions. Observational studies on fire–atmosphere interactions have used instrumented towers to collect data during prescribed fires, but a few towers in an operational-scale burn plot (usually > 10 3 m2) have made it extremely challenging to capture the myriad of factors controlling fire–atmosphere interactions, many of which exhibit strong spatial variability. Here, we present analyses of atmospheric turbulence data collected using a 4 × 4 array of fast-response sonic anemometers during a fire experiment on a 10 m × 10 m burn plot. In addition to confirming some of the previous findings on atmospheric turbulence associated with low-intensity surface fires, our results revealed substantial heterogeneity in turbulent intensity and heat and momentum fluxes just above the combustion zone. Despite the small plot (100 m2), fire-induced atmospheric turbulence exhibited strong dependence on the downwind distance from the initial line fire and the relative position specific to the fire front as the surface fire spread through the burn plot. This result highlights the necessity for coupled atmosphere–fire behavior models to have 1–2 m grid spacing to resolve heterogeneities in fire–atmosphere interactions that operate on spatiotemporal scales relevant to atmospheric turbulence. The findings here have important implications for modeling smoke dispersion, as atmospheric dispersion characteristics in the vicinity of a wildland fire are directly affected by fire-induced turbulence. [ABSTRACT FROM AUTHOR]

The ambient atmospheric environment affects the growth and spread of wildland fires, whereas heat and moisture release from the fires and the reduction of the surface drag in the burned areas can significantly alter local atmospheric conditions. Observational studies on fire-atmosphere interactions have used instrumented towers to collect data during prescribed fires, but a few towers in an operational scale burn plot (usually > 103 m2) have made it extremely challenging to capture the myriad of factors controlling fire-atmosphere interactions, many of which exhibit strong spatial variability. Here, we present analyses of atmospheric turbulence data collected using a 4×4 array of fast-response sonic anemometers during a fire experiment on a 10 m × 10 m burn plot. In addition to confirming some of the previous findings on atmospheric turbulence associated with low-intensity surface fires, our results revealed substantial heterogeneity in turbulent intensity and heat and momentum fluxes just above the combustion zone. Despite the small plot (100 m2), fire-induced atmospheric turbulence exhibited strong dependence on the downwind distance from the initial line fire and the relative position specific to the fire front as the surface fire spread through the burn plot. This result highlights the necessity for coupled atmosphere-fire behavior models to have 1–2 m grid spacing to resolve heterogeneities in fire-atmosphere interactions that operate on spatiotemporal scales relevant to atmospheric turbulence. The findings here have important implications for modeling smoke dispersion, as atmospheric dispersion characteristics in the vicinity of a wildland fire are directly affected by fire-induced turbulence. [ABSTRACT FROM AUTHOR]

The increase in wildfire risk in the United States in recent decades has been linked to rapid growth of the wildland‐urban interface and to changing climate. While there have been numerous studies on wildfires and climate change, few have separately assessed the impact of climate response to land‐use‐land‐cover change (LULCC) on wildfires. In this study, we analyse two 10‐year regional climate simulations driven by the current (2011) and future (2100) land‐use‐land‐cover patterns to assess modifications by the projected LULCC to the frequency and severity of fire‐prone atmospheric conditions described by two fire weather indices, the Canadian Forest Fire Weather Index and the Hot‐Dry‐Windy Index. The simulation corresponding to future land‐use‐land‐cover pattern yields higher surface temperature and vapour pressure deficit and lower precipitation compared to the simulation with the current pattern in areas where urbanized landscapes replace forests and grasslands, such as along the Piedmont and outside the Chicagoland region, while in areas where croplands replace forests, such as the southeast Coastal Plains, the results are reversed. These changes to local and regional atmospheric conditions lead to longer fire seasons and more extreme fire‐weather conditions in much of the eastern United States, specifically in the Southeast and Ohio River Valley where significant urban expansion is projected by the end of the century. Whereas in Southern California where some highly flammable shrublands will be replaced by urban or crop lands, fire‐prone atmospheric conditions are likely to be less frequent and less extreme in the future. However, much of California moves towards a year‐round fire season under the projected LULCC. The results suggest that by altering atmospheric conditions, LULCC may play an important role in determining fire regime, but the effects are highly heterogeneous and regionalized. [ABSTRACT FROM AUTHOR]

Wildfire regimes respond to atmospheric variability on multiple time scales from interannual variations of drought to daily fluctuations of humidity and wind. Synoptic weather patterns effectively link both short- and long-term atmospheric variability, and thus, understanding fire-prone synoptic patterns is an integral part of fire management programs. Different analysis procedures of varying complexity have been used to identify the most common synoptic weather patterns conducive to wildfires. In this study, we examine the utility of three synoptic-pattern classification methodologies, namely Composite, Empirical Orthogonal Function (EOF), and Self Organizing Map (SOM). We focused on the synoptic weather patterns associated with 203 wildfires that burned 50,000 acres (20,250 ha) or more and 80 wildfires that burned 100,000 acres (40,500 ha) or more in the Northwestern United States between 1984 and 2014. The basic 500-hPa geopotential height patterns identified by the three analysis methods were found to be similar for the two fire-size categories, but the strengths of the geopotential height anomalies were larger for the larger size fires. All three methods were able to consistently identify the dominant pattern with only small differences in strength and position of the anomalies, but the EOF and SOM methods yielded other less dominant, but still important, patterns. Particularly, the SOM method captured transitional synoptic patterns that may account for 20–30% of these large wildfires. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

• The study offers insights into atmospheric turbulence during intense grass fires. • These findings are significant as they provide the first-ever in-situ turbulence data collected during Red Flag Warnings. • The data establishes an upper limit for turbulence in prescribed grass fires, offering valuable reference points. • These results have the potential to enhance turbulence schemes in fire behavior models, contributing to better fire predictions. • This study underscores the complexities of studying fire type effects in a real-world context. A wildland fire experiment was conducted on a 40-ha tall grass prairie in Texas to study fire-atmosphere interactions. The experiment coincided with a Red Flag Warning, signifying specific weather conditions associated with an elevated risk of wildfire ignition and rapid spread. This provided a rare opportunity to observe wildland fire behavior and its impact on atmospheric flows under conditions deliberately avoided in similar experiments. This study analyzed the high frequency meteorological data collected during the experiment using three-dimensional sonic anemometers mounted on a 43-m tower (at 5.8, 10 and 20 m) and on three 10-m towers (at 5.3 m) within the burn block. The tower placements were carefully chosen to capture the impact of both head and flank fires on the mean and turbulent flows. The hypothesis is that fire-induced perturbations in the lower atmosphere, quantified through parameters like turbulent kinetic energy (TKE) and vertical fluxes, would be substantially stronger than those observed in similar wildland fires under less fire-prone atmospheric conditions. While this hypothesis was validated for heat flux and TKE, it did not hold for momentum fluxes or friction velocity. Additionally, the observations failed to confirm the hypothesis that head fires would produce more intense perturbations than flank fires. Given the homogeneity of fuel, terrain and meteorological elements across the burn unit, this underscores the challenge of disentangling the effects of fire type from other natural factors in a real-world setting. Nevertheless, the finding holds promise for improving turbulence parameterizations in fire-behavior and smoke dispersion models. [ABSTRACT FROM AUTHOR]