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Wildfires are an essential part of a healthy ecosystem, yet the expansion of the wildland-urban interface, combined with climatic changes and other anthropogenic activities, have led to the rise of wildfire hazards in the past few decades. Managing future wildfires and their multi-dimensional impacts requires moving from traditional reactive response to deploying proactive policies, strategies, and interventional programs to reduce wildfire risk to wildland-urban interface communities. Existing risk assessment frameworks lack a unified analytical method that properly captures uncertainties and the impact of decisions across social, ecological, and technical systems, hindering effective decision-making related to risk reduction investments. In this paper, a conceptual probabilistic wildfire risk assessment framework that propagates modeling uncertainties is presented. The framework characterizes the dynamic risk through spatial probability density functions of loss, where loss can include different decision variables, such as physical, social, economic, environmental, and health impacts, depending on the stakeholder needs and jurisdiction. The proposed approach consists of a computational framework to propagate and integrate uncertainties in the fire scenarios, propagation of fire in the wildland and urban areas, damage, and loss analyses. Elements of this framework that require further research are identified, and the complexity in characterizing wildfire losses and the need for an analytical-deliberative process to include the perspectives of the spectrum of stakeholders are discussed. [ABSTRACT FROM AUTHOR]

This study uses the method for object‐based diagnostic evaluation (MODE) technique to examine and compare the statistics of drought attributes over the upper Colorado River basin (UCRB). The drought objects are based on the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI) on a 36‐month timescale (SPI36 and SPEI36, respectively). The drought indicators are calculated using monthly precipitation as well as minimum and maximum temperatures from the Precipitation–Elevation Regression on Independent Slopes Model data sets from 1948 to 2012. MODE uses paired object attributes such as centroid distance, orientation angle, area ratio, and intersection area and a combination of parameter thresholds to determine the number of objects identified and retained in the merging and matching process in the two fields. Using MODE run with convolution radius of zero (no smoothing) and an area threshold of four grid points, this study computes and analyses object statistics including centroid locations, areas, and intensity percentiles. Results of the analysis show that SPI36 produces more drought objects than SPEI36. Although the spatial patterns are roughly similar leading up to almost similar statistics of object attributes, such as locations of the object centroids, the SPI36 produces higher percentile intensity of drought objects than does SPEI36, which is clearly obvious in the 90th percentile intensity of drought objects. The largest difference between SPEI36 and SPI36 occurs in the area of drought objects during the early 2000s when the region experienced multi‐year drought resulting from increased warming of the atmosphere. This study demonstrates the use of MODE as a tool to evaluate and monitor drought event over the UCRB. [ABSTRACT FROM AUTHOR]

This study analyzes spatial and temporal characteristics of multiyear droughts and pluvials over the southwestern United States with a focus on the upper Colorado River basin. The study uses two multiscalar moisture indices: standardized precipitation evapotranspiration index (SPEI) and standardized precipitation index (SPI) on a 36-month scale (SPEI36 and SPI36, respectively). The indices are calculated from monthly average precipitation and maximum and minimum temperatures from the Parameter-Elevation Regressions on Independent Slopes Model dataset for the period 1950-2012. The study examines the relationship between individual climate variables as well as large-scale atmospheric circulation features found in reanalysis output during drought and pluvial periods. The results indicate that SPEI36 and SPI36 show similar temporal and spatial patterns, but that the inclusion of temperatures in SPEI36 leads tomore extreme magnitudes in SPEI36 than in SPI36. Analysis of large-scale atmospheric fields indicates an interplay between different fields that yields extremes over the study region. Widespread drought (pluvial) events are associated with enhanced positive (negative) 500-hPa geopotential height anomaly linked to subsidence (ascent) and negative (positive) moisture convergence and precipitable water anomalies. Considering the broader context of the conditions responsible for the occurrence of prolonged hydrologic anomalies provides water resource managers and other decision-makers with valuable understanding of these events. This perspective also offers evaluation opportunities for climate models. [ABSTRACT FROM AUTHOR]

Generating credible climate change and extremes projections remains a high-priority challenge, especially since recent observed emissions are above the worst-case scenario. Bias and uncertainty analyses of ensemble simulations from a global earth systems model show increased warming and more intense heat waves combined with greater uncertainty and large regional variability in the 21st century. Global warming trends are statistically validated across ensembles and investigated at regional scales. Observed heat wave intensities in the current decade are larger than worst-case projections. Model projections are relatively insensitive to initial conditions, while uncertainty bounds obtained by comparison with recent observations are wider than ensemble ranges. Increased trends in temperature and heat waves, concurrent with larger uncertainty and variability, suggest greater urgency and complexity of adaptation or mitigation decisions. [ABSTRACT FROM AUTHOR]

Climate change scenario simulations with the Community Climate System Model version 3 (CCSM3), a global coupled climate model, show that if concentrations of all greenhouse gases (GHGs) could have been stabilized at the year 2000, the climate system would already be committed to 0.4°C more warming by the end of the twenty-first century. Committed sea level rise by 2100 is about an order of magnitude more, percentage-wise, compared to sea level rise simulated in the twentieth century. This increase in the model is produced only by thermal expansion of seawater, and does not take into account melt from ice sheets and glaciers, which could at least double that number. Several tenths of a degree of additional warming occurs in the model for the next 200 yr in the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) B1 and A1B scenarios after stabilization in the year 2100, but with twice as much sea level rise after 100 yr, and doubling yet again in the next 100 yr to 2300. At the end of the twenty-first century, the warming in the tropical Pacific for the A2, A1B, and B1 scenarios resembles an El Niño–like response, likely due to cloud feedbacks in the model as shown in an earlier version. Greatest warming occurs at high northern latitudes and over continents. The monsoon regimes intensify somewhat in the future warmer climate, with decreases of sea level pressure at high latitudes and increases in the subtropics and parts of the midlatitudes. There is a weak summer midlatitude soil moisture drying in this model as documented in previous models. Sea ice distributions in both hemispheres are somewhat overextensive, but with about the right ice thickness at the end of the twentieth century. Future decreases in sea ice with global warming are proportional to the temperature response from the forcing scenarios, with the high forcing scenario, A2, producing an ice-free Arctic in summer by the year 2100. [ABSTRACT FROM AUTHOR]

Arctic climate change in the Twenty-first century is simulated by the Community Climate System Model version 3.0 (CCSM3). The simulations from three emission scenarios (A2, A1B and B1) are analyzed using eight (A1B and B1) or five (A2) ensemble members. The model simulates a reasonable present-day climate and historical climate trend. The model projects a decline of sea-ice extent in the range of 1.4–3.9% per decade and 4.8–22.2% per decade in winter and summer, respectively, corresponding to the range of forcings that span the scenarios. At the end of the Twenty-first century, the winter and summer Arctic mean surface air temperature increases in a range of 4–14°C (B1 and A2) and 0.7–5°C (B1 and A2) relative to the end of the Twentieth century. The Arctic becomes ice-free during summer at the end of the Twenty-first century in the A2 scenario. Similar to the observations, the Arctic Oscillation (AO) is the dominant factor in explaining the variability of the atmosphere and sea ice in the 1870–1999 historical runs. The AO shifts to the positive phase in response to greenhouse gas forcings in the Twenty-first century. But the simulated trends in both Arctic mean sea-level pressure and the AO index are smaller than what has been observed. The Twenty-first century Arctic warming mainly results from the radiative forcing of greenhouse gases. The 1st empirical orthogonal function (explains 72.2–51.7% of the total variance) of the wintertime surface air temperature during 1870–2099 is characterized by a strong warming trend and a “polar amplification”-type of spatial pattern. The AO, which plays a secondary role, contributes to less than 10% of the total variance in both surface temperature and sea-ice concentration. [ABSTRACT FROM AUTHOR]