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Wildfires that occurred over the western United States during August 2012 were fewer in number but larger in size when compared with all other Augusts in the twenty-first century. This unique characteristic, along with the tremendous property damage and potential loss of life that occur with large wildfires with erratic behavior, raised the question of whether future climate will favor rapid wildfire growth so that similar wildfire activity may become more frequent as climate changes. This study addresses this question by examining differences in the climatological distribution of the Haines index (HI) between the current and projected future climate over the western United States. The HI, ranging from 2 to 6, was designed to characterize dry, unstable air in the lower atmosphere that may contribute to erratic or extreme fire behavior. A shift in HI distribution from low values (2 and 3) to higher values (5 and 6) would indicate an increased risk for rapid wildfire growth and spread. Distributions of Haines index are calculated from simulations of current (1971-2000) and future (2041-70) climate using multiple regional climate models in the North American Regional Climate Change Assessment Program. Despite some differences among the projections, the simulations indicate that there may be not only more days but also more consecutive days with HI ≥ 5 during August in the future. This result suggests that future atmospheric environments will be more conducive to erratic wildfires in the mountainous regions of the western United States. [ABSTRACT FROM AUTHOR]

Soil temperature can exhibit considerable memory from weather and climate signals and is among the most important initial conditions in numerical weather and climate models. Consequently, a more accurate long-term land surface soil temperature dataset is needed to improve weather and climate simulation and prediction, and is also important for the simulation of agricultural crop yield and ecological processes. The North American Land Data Assimilation phase 2 (NLDAS-2) has generated 31 years (1979-2009) of simulated hourly soil temperature data with a spatial resolution of ⅛°. This dataset has not been comprehensively evaluated to date. Thus, the purpose of this paper is to assess Noah-simulated soil temperature for different soil depths and time scales. The authors used long-term (1979-2001) observed monthly mean soil temperatures from 137 cooperative stations over the United States to evaluate simulated soil temperature for three soil layers (0-10, 10-40, and 40-100 cm) for annual and monthly time scales. Short-term (1997-99) observed soil temperatures from 72 Oklahoma Mesonet stations were used to validate simulated soil temperatures for three soil layers and for daily and hourly time scales. The results showed that the Noah land surface model generally matches observed soil temperature well for different soil layers and time scales. At greater depths, the simulation skill (anomaly correlation) decreased for all time scales. The monthly mean diurnal cycle difference between simulated and observed soil temperature revealed large midnight biases in the cold season that are due to small downward longwave radiation and issues related to model parameters. [ABSTRACT FROM AUTHOR]