Conversion of agricultural lands to urban uses affects regional and global climate not only through the release of greenhouse gases but also through altering land surface physical processes such as energy and water balances. Most existing studies on the meteorological impacts of urbanization focus on urban heat island effects with little attention on its impacts of atmospheric humidity, a key variable in hydrometeorology and climate science. We define the influences of urbanization on reducing atmospheric humidity and elevating vapor pressure deficit as urban dry island (UDI) effects. We conduct a case study in the Yangtze River Delta, a typical humid area in southern China that is under rapid urbanization. We examine spatiotemporal characteristics of UDI and identify potential drivers during 2001–2014. Relationships and interactions between variations of air temperature, atmospheric humidity, evapotranspiration, and leaf area index of different land cover were determined using correlation and attribution analyses at both station and regional levels. We show that atmospheric humidity decreased dramatically and vapor pressure deficit increased sharply in the urban core, resulting in enhanced UDI. In addition to global warming and localized urban heat island, UDI is closely related to the loss of vegetation cover (i.e., natural wetlands and paddies). Reduction of evapotranspiration or latent heat is another important factor contributing to UDI effects. We conclude that the role of vegetated land cover and associated ecohydrological processes in moderating UDI and maintaining a stable climate and environment should be considered in massive urban planning and global change impact assessment in southern China.

The Fire and Smoke Model Evaluation Experiment (FASMEE) is designed to collect integrated observations from large wildland fires and provide evaluation datasets for new models and operational systems. Wildland fire, smoke dispersion, and atmospheric chemistry models have become more sophisticated, and next-generation operational models will require evaluation datasets that are coordinated and comprehensive for their evaluation and advancement. Integrated measurements are required, including ground-based observations of fuels and fire behavior, estimates of fire-emitted heat and emissions fluxes, and observations of near-source micrometeorology, plume properties, smoke dispersion, and atmospheric chemistry. To address these requirements the FASMEE campaign design includes a study plan to guide the suite of required measurements in forested sites representative of many prescribed burning programs in the southeastern United States and increasingly common high-intensity fires in the western United States. Here we provide an overview of the proposed experiment and recommendations for key measurements. The FASMEE study provides a template for additional large-scale experimental campaigns to advance fire science and operational fire and smoke models.

There is an urgent need for next-generation smoke research and forecasting (SRF) systems to meet the challenges of the growing air quality, health and safety concerns associated with wildland fire emissions. This review paper presents simulations and experiments of hypothetical prescribed burns with a suite of selected fire behaviour and smoke models and identifies major issues for model improvement and the most critical observational needs. The results are used to understand the new and improved capability required for the next-generation SRF systems and to support the design of the Fire and Smoke Model Evaluation Experiment (FASMEE) and other field campaigns. The next-generation SRF systems should have more coupling of fire, smoke and atmospheric processes. The development of the coupling capability requires comprehensive and spatially and temporally integrated measurements across the various disciplines to characterise flame and energy structure (e.g. individual cells, vertical heat profile and the height of well-mixing flaming gases), smoke structure (vertical distributions and multiple subplumes), ambient air processes (smoke eddy, entrainment and radiative effects of smoke aerosols) and fire emissions (for different fuel types and combustion conditions from flaming to residual smouldering), as well as night-time processes (smoke drainage and super-fog formation).

We present Daysmoke, an empirical-statistical plume rise and dispersion model for simulating smoke from prescribed burns. Prescribed fires are characterized by complex plume structure including multiple-core updrafts which makes modeling with simple plume models difficult. Daysmoke accounts for plume structure in a three-dimensional veering/sheering atmospheric environment, multiple-core updrafts, and detrainment of particulate matter. The number of empirical coefficients appearing in the model theory is reduced through a sensitivity analysis with the Fourier Amplitude Sensitivity Test (FAST). Daysmoke simulations for “bent-over” plumes compare closely with Briggs theory although the two-thirds law is not explicit in Daysmoke. However, the solutions for the “highly-tilted” plume characterized by weak buoyancy, low initial vertical velocity, and large initial plume diameter depart considerably from Briggs theory. Results from a study of weak plumes from prescribed burns at Fort Benning GA showed simulated ground-level PM_2.5 comparing favorably with observations taken within the first eight kilometers of eleven prescribed burns. Daysmoke placed plume tops near the lower end of the range of observed plume tops for six prescribed burns. Daysmoke provides the levels and amounts of smoke injected into regional scale air quality models. Results from CMAQ with and without an adaptive grid are presented.