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Changes in the essential climate extremes indices and surface variables for the end of the twenty-first century are assessed in this study based on two transient climate change simulations, with and without land-use and land-cover changes (LULCC), but identical atmospheric forcing. The two simulations are performed with the 5th generation of the Canadian Regional Climate Model (CRCM5) driven by the Canadian Earth System Model for the (2006-2100)-Representative Concentration Pathway 4.5 (RCP4.5) scenario. For the simulation with LULCC, land-cover data sets are taken from the global change assessment model (GCAM) representing the RCP4.5 scenario for the period 2006-2100. LULCC in RCP4.5 scenario suggest significant reduction in cultivated land (e.g. Canadian Prairies and Mississippi basin) due to afforestation. CRCM5 climate projections imply a general warming by the end of the twenty-first century, especially over the northern regions in winter. CRCM5 projects more warm spell-days per year over most areas of the continent, and implicitly more summer days and tropical nights at the expense of cold-spell, frost and ice days whose number is projected to decrease by up to 40% by the end of the twenty-first century with respect to the baseline period 1971-2000. Most land areas north of 45°N, in all seasons, as well as the southeastern United States in summer, exhibit increases in mean precipitation under the RCP4.5 scenario. In contrast, central parts of the continent in summer and much of Mexico in all seasons show reduced precipitation. In addition, large areas of North America exhibit changes of 10 to 40% (depending on the season and geographical location) in the number of heavy precipitation days. Results also suggest that the biogeophysical effects of LULCC on climate, assessed through differences between the two simulations, lead to warmer regional climates, especially in winter. The investigation of processes leading to this response shows high sensitivity of the results to changes in albedo as a response to LULCC. Overall, at the seasonal scale, results show that intense afforestation may contribute to an additional 25% of projected changes. [ABSTRACT FROM AUTHOR]

This study examines the dominant heatwave variability over North America (NA), extracted from an empirical orthogonal function (EOF) analysis of summertime monthly warm extreme index anomalies over 1959–2021. The principal mode features a dipole structure with a large area of anomaly over northwestern NA and an anomaly of opposite sign over the southern U.S. The corresponding principal component is associated with a large-scale atmospheric wave train extending from the North Pacific to North America (NP-NA) and a northeastward injection of moisture from the subtropical western Pacific towards western NA, which are key factors in supporting the NA heatwave variability. The NP-NA wave train can be systematically reinforced and supported by synoptic-scale eddies, and may also be forced by an anomalous convection over the tropical-subtropical western Pacific. Surface radiation heating directly contributes to surface temperature anomalies and is dominated by anomalous downwelling shortwave and longwave radiations. In association with a positive phase of the heatwave variability, the NP-NA wave train brings an anticyclonic anomaly over northern NA, leading to anomalous descent, reduced total cloud cover and below-normal precipitation and surface relative humidity over northern NA. Over northwestern NA, the anomalous subsidence causes air to warm through compression. Reduced cloud cover results in increased downward shortwave radiation that is a key contributor to surface radiation heating. In addition, increase in vertically integrated water vapour through the moisture injection from the North Pacific collocates with tropospheric warming. The atmosphere has more water vapor holding capability and acts as a greenhouse gas to absorb longwave radiation, leading to increased downward longwave radiation that is the second major contributor to surface radiation heating. Processes with circulation and surface radiation anomalies of opposite signs will likewise lead to the negative heatwave variability. [ABSTRACT FROM AUTHOR]

We report on the characteristics of precipitation associated with three types of landfalling atmospheric rivers (ARs) over western North America in the winter season from 1980 to 2004. The ARs are classified according to three landfalling regions as southern, middle and northern types. Two main centers of precipitation are associated with the contributions by the ARs: one over Baja California linked to the southern type of the ARs, and the other over Washington State correlated with the northern and middle types of the ARs. ARs are seen to play a dominant role in the occurrences of extreme precipitation events, with a proportionately greater impact on more extreme events. Moisture flux convergence makes the dominant contribution to precipitation when ARs and extreme precipitation occur simultaneously in the studied areas. Moisture flux convergence in these cases is, in turn, dominated by the mean and transient moisture transported by the transient wind, with greater contribution from the latter, which is mainly concentrated in certain areas. The magnitude and direction of vertically integrated vapor transport (IVT) also play a role in determining the amount of precipitation received in the three regions considered. Larger IVT magnitude corresponds to more precipitation, while an IVT direction of about 220° (0° indicating east wind) is most favorable for high precipitation amount, which is especially obvious for the northern type of the ARs. [ABSTRACT FROM AUTHOR]

This paper surveys the current state of knowledge regarding large-scale meteorological patterns (LSMPs) associated with short-duration (less than 1 week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defined based on the characteristic spatial variations of a meteorological field or on the remote circulation response to a known forcing, LSMPs are defined relative to the occurrence of a specific phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary influence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to definitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many different definitions of "extreme" are in use, making it difficult to directly compare different studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some promising analysis techniques have been identified and the LSMP perspective is useful for evaluating the model dynamics associated with extremes. [ABSTRACT FROM AUTHOR]

Using historical simulations of the Coupled Model Intercomparison Project-5 (CMIP5) and multiple observationally-based datasets, we employ skill metrics to analyze the fidelity of the simulated Northern Annular Mode, the North Atlantic Oscillation, the Pacific North America pattern, the Southern Annular Mode, the Pacific Decadal Oscillation, the North Pacific Oscillation, and the North Pacific Gyre Oscillation. We assess the benefits of a unified approach to evaluate these modes of variability, which we call the common basis function (CBF) approach, based on projecting model anomalies onto observed empirical orthogonal functions (EOFs). The CBF approach circumvents issues with conventional EOF analysis, eliminating, for example, corrections of arbitrarily assigned, but inconsistent, signs of the EOF's/PC's being compared. It also avoids the problem that sometimes the first observed EOF is more similar to a higher order model EOF, particularly if the simulated EOFs are not well separated. Compared to conventional EOF analysis of models, the CBF approach indicates that models compare significantly better with observations in terms of pattern correlation and root-mean-squared-error (RMSE) than heretofore suggested. In many cases, models are doing a credible job at capturing the observationally-based estimates of patterns; however, errors in simulated amplitudes can be large and more egregious than pattern errors. In the context of the broad distribution of errors in the CMIP5 ensemble, sensitivity tests demonstrate that our results are relatively insensitive to methodological considerations (CBF vs. conventional approach), observational uncertainties in pattern (as determined by using multiple datasets), and internal variability (when multiple realizations from the same model are compared). The skill metrics proposed in this study can provide a useful summary of the ability of models to reproduce the observed EOF patterns and amplitudes. Additionally, the skill metrics can be used as a tool to objectively highlight where potential model improvements might be made. We advocate more systematic and objective testing of simulated extratropical variability, especially during the non-dominant seasons of each mode, when many models are performing relatively poorly. [ABSTRACT FROM AUTHOR]

We synthesized an expert review of climate change implications for hydroecological and terrestrial ecological systems in the northern coastal temperate rainforest of North America. Our synthesis is based on an analysis of projected temperature, precipitation, and snowfall stratified by eight biogeoclimatic provinces and three vegetation zones. Five IPCC CMIP5 global climate models (GCMs) and two representative concentration pathways (RCPs) are the basis for projections of mean annual temperature increasing from a current average (1961-1990) of 3.2 °C to 4.9-6.9 °C (5 GCM range; RCP4.5 scenario) or 6.4-8.7 °C (RCP8.5), mean annual precipitation increasing from 3130 mm to 3210-3400 mm (3-9 % increase) or 3320-3690 mm (6-18 % increase), and total precipitation as snow decreasing from 1200 mm to 940-720 mm (22-40 % decrease) or 720-500 mm (40-58 % decrease) by the 2080s (2071-2100; 30-year normal period). These projected changes are anticipated to result in a cascade of ecosystem-level effects including: increased frequency of flooding and rain-on-snow events; an elevated snowline and reduced snowpack; changes in the timing and magnitude of stream flow, freshwater thermal regimes, and riverine nutrient exports; shrinking alpine habitats; altitudinal and latitudinal expansion of lowland and subalpine forest types; shifts in suitable habitat boundaries for vegetation and wildlife communities; adverse effects on species with rare ecological niches or limited dispersibility; and shifts in anadromous salmon distribution and productivity. Our collaborative synthesis of potential impacts highlights the coupling of social and ecological systems that characterize the region as well as a number of major information gaps to help guide assessments of future conditions and adaptive capacity. [ABSTRACT FROM AUTHOR]