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Abstract The path toward a warmer global climate is not smooth, but, rather, is made up of a succession of positive and negative temperature trends, with cooling having more chance to occur the shorter the time scale considered. In this paper, estimates of the probabilities of short-term cooling ( P cool ) during the period 2006–35 are performed for 5146 locations across Canada. Probabilities of cooling over durations from 5 to 25 yr come from an ensemble of 60 climate scenarios, based on three different methods using a gridded observational product and CMIP5 climate simulations. These methods treat interannual variability differently, and an analysis in hindcast mode suggests they are relatively reliable. Unsurprisingly, longer durations imply smaller P cool values; in the case of annual temperatures, the interdecile range of P cool values across Canada is, for example, ~2%–18% for 25 yr and ~40%–46% for 5 yr. Results vary slightly with the scenario design method, with similar geographical patterns emerging. With regards to seasonal influence, spring and winter are generally associated with higher P cool values. Geographical P cool patterns and their seasonality are explained in terms of the interannual variability over background trend ratio. This study emphasizes the importance of natural variability superimposed on anthropogenically forced long-term trends and the fact that regional and local short-term cooling trends are to be expected with nonnegligible probabilities.

With the refinement of grid meshes in regional climate models permitted by the increase in computing power, the grid telescoping or cascade method, already used in numerical weather prediction, can be applied to achieve very high-resolution climate simulations. The purpose of this study is two-fold: (1) to illustrate the perspectives offered by climate simulations on kilometer-scale grid meshes using the wind characteristics in the St. Lawrence River Valley (SLRV) as the test-bench; and (2) to establish some constraints to be satisfied for the physical realism and the computational affordability of these simulations. The cascade method is illustrated using a suite of five one-way nested, time-slice simulations carried out with the fifth-generation Canadian Regional Climate Model, with grid meshes varying from roughly 81 km, successively to 27, 9, 3 and finally 1 km, over domains centered on the SLRV. The results show the added value afforded by very high-resolution meshes for a realistic simulation of the SLRV winds. Kinetic energy spectra are used to document the spin-up time and the effective resolution of the simulations as a function of their grid meshes. A pragmatic consideration is developed arguing that kilometer-scale simulations could be achieved at a reasonable computational cost with time-slice simulations of high impact climate events. This study lends confidence to the idea that climate simulations and projections at kilometer-scale could soon become operationally feasible, thus offering interesting perspectives for resolving features that are currently out of reach with coarser-mesh models.

Abstract This article examines the types of winter precipitation that occur near 0°C, specifically rain, freezing rain, freezing drizzle, ice pellets, snow pellets, and wet snow. It follows from a call by M. Ralph et al. for more attention to be paid to this precipitation since it represents one of the most serious wintertime quantitative precipitation forecasting (QPF) issues. The formation of the many precipitation types involves ice-phase and/or liquid-phase processes, and thresholds in the degree of melting and/or freezing often dictate the types occurring at the surface. Some types can occur simultaneously so that, for example, ensuing collisions between supercooled raindrops and ice pellets that form ice pellet aggregates can lead to substantial reductions in the occurrence of freezing rain at the surface, and ice crystal multiplication processes can lead to locally produced ice crystals in the subfreezing layer below inversions. Highly variable fall velocities within the background temperature and wind fields of precipitation-type transition regions lead to varying particle trajectories and significant alterations in the distribution of precipitation amount and type at the surface. Physically based predictions that account for at least some of the phase changes and particle interactions are now in operation. Outstanding issues to be addressed include the impacts of accretion on precipitation-type formation, quantification of melting and freezing rates of the highly variable precipitation, the consequences of collisions between the various types, and the onset of ice nucleation and its effects. The precipitation physics perspective of this article furthermore needs to be integrated into a comprehensive understanding involving the surrounding and interacting environment.

High-Latitude Volcanic Eruption Impacts on Climate: Filling the Gaps; Stockholm, Sweden, 5–7 November 2014

Evergreen broadleaved forests in subtropical China contain a complicated structure of diverse species. The impact of topographic and soil factors on the assembly of woody species in the forest has been poorly understood. We used Ripley’s K(t) function to analyze the spatial patterns and associations of dominant species and residual analysis (RDA) to quantify the contribution of topography and soil to species assembly. The 1 ha plot investigated had 4797 stems with a diameter at breast height (dbh) larger than 1 cm that belong to 73 species, 55 genera, and 38 families. All stems of the entire forest and four late successional species exhibited a reversed J shape for dbh distribution, while two early successional species showed a unimodal shape. Aggregation was the major spatial pattern for entire forests and dominant species across vertical layers. Spatial associations between inter- and intra-species were mostly independent. Topographic and soil factors explained 28.1% of species assembly. The forest was close to late succession and showed the characteristics of diverse woody species, high regeneration capacity, and aggregated spatial patterns. Topographic and soil factors affected species assembly, but together they could only explain a small part of total variance.

Abstract The Australian east coast low (ECL) is both a major cause of damaging severe weather and an important contributor to rainfall and dam inflow along the east coast, and is of interest to a wide range of groups including catchment managers and emergency services. For this reason, several studies in recent years have developed and interrogated databases of east coast lows using a variety of automated cyclone detection methods and identification criteria. This paper retunes each method so that all yield a similar event frequency within the ECL region, to enable a detailed intercomparison of the similarities, differences, and relative advantages of each method. All methods are shown to have substantial skill at identifying ECL events leading to major impacts or explosive development, but the choice of method significantly affects both the seasonal and interannual variation of detected ECL numbers. This must be taken into consideration in studies on trends or variability in ECLs, with a subcategorization of ECL events by synoptic situation of key importance.

Abstract. Numerical model scenarios of future climate depict a global increase in temperatures and changing precipitation patterns, primarily driven by increasing greenhouse gas (GHG) concentrations. Aerosol particles also play an important role by altering the Earth's radiation budget and consequently surface temperature. Here, we use the general circulation aerosol model ECHAM5-HAM, coupled to a mixed layer ocean model, to investigate the impacts of future air pollution mitigation strategies in Europe on winter atmospheric circulation over the North Atlantic. We analyse the extreme case of a maximum feasible end-of-pipe reduction of aerosols in the near future (2030), in combination with increasing GHG concentrations. Our results show a more positive North Atlantic Oscillation (NAO) mean state by 2030, together with a significant eastward shift of the southern centre of action of sea-level pressure (SLP). Moreover, we show a significantly increased blocking frequency over the western Mediterranean. By separating the impacts of aerosols and GHGs, our study suggests that future aerosol abatement may be the primary driver of both the eastward shift in the southern SLP centre of action and the increased blocking frequency over the western Mediterranean. These concomitant modifications of the atmospheric circulation over the Euro-Atlantic sector lead to more stagnant weather conditions that favour air pollutant accumulation, especially in the western Mediterranean sector. Changes in atmospheric circulation should therefore be included in future air pollution mitigation assessments. The indicator-based evaluation of atmospheric circulation changes presented in this work will allow an objective first-order assessment of the role of changes in wintertime circulation on future air quality in other climate model simulations.

Abstract Bias correction of climate model outputs has emerged as a standard procedure in most recent climate change impact studies. A crucial assumption of all bias correction approaches is that climate model biases are constant over time. The validity of this assumption has important implications for impact studies and needs to be verified to properly address uncertainty in future climate projections. Using 10 climate model simulations, this study specifically tests the bias stationarity of climate model outputs over Canada and the contiguous United States (U.S.) by comparing model outputs with corresponding observations over two 20 year historical periods (1961–1980 and 1981–2000). The results show that precipitation biases are clearly nonstationary over much of Canada and the contiguous U.S. and where they vary over much shorter time scales than those normally considered in climate change impact studies. In particular, the difference in biases over two very close periods of the recent past are, in fact, comparable to the climate change signal between future (2061–2080) and historical (1961–1980) periods for precipitation over large parts of Canada and the contiguous U.S., indicating that the uncertainty of future impacts may have been underestimated in most impact studies. In comparison, temperature bias can be considered to be approximately stationary for most of Canada and the contiguous U.S. when compared with the magnitude of the climate change signal. Given the reality that precipitation is usually considered to be more important than temperature for many impact studies, it is advisable that natural climate variability and climate model sensitivity be better emphasized in future impact studies. , Key Points Climate model biases are nonstationary over much of North America The difference in biases is comparable to the climate change signal The uncertainty of impacts may have been underestimated in most impact studies

Abstract Climate simulations made with two regional climate models (RCMs), the French Aire Limitée Adaptation Dynamique Développement International (ALADIN) and the Canadian Regional Climate Model, version 5 (CRCM5), operating on 10-km meshes for the period 1989–2011, and the Hydro-Québec hydrological model (HSAMI), are used to reconstruct the spring 2011 Richelieu River flood in the southern region of the province of Québec, Canada. The analysis shows that the simulated fields of 2-m air temperature, precipitation, and snow water equivalent by the RCMs closely match the observations with similar multiyear means and a high correlation of the monthly anomalies. The climatic conditions responsible for the 2011 flood are generally well simulated by the RCMs. The use of multidecadal RCM simulations facilitates the identification of anomalies that contributed to the flood. The flood was linked to a combination of factors: the 2010/11 winter was cold and snowy, the snowmelt in spring was fast, and there was a record amount of precipitation in April and May. Driven by outputs from the RCMs, HSAMI was able to reproduce the mean hydrograph of the Richelieu River, but it underestimated the peak of the 2011 flood. HSAMI adequately computes the water transport from the mountains to the river mouth and the storage effect of Lake Champlain, which dampens the flood over a long period. Overall, the results suggest that RCM simulations can be useful for reconstructing high-resolution climate information and providing new variables that can help better understand the causes of extreme climatic events.

Abstract The climate of the eastern seaboard of Australia is strongly influenced by the passage of low pressure systems over the adjacent Tasman Sea due to their associated precipitation and their potential to develop into extreme weather events. The aim of this study is to quantify differences in the climatology of east coast lows derived from the use of six global reanalyses. The methodology is explicitly designed to identify differences between reanalyses arising from differences in their horizontal resolution and their structure (type of forecast model, assimilation scheme, and the kind and number of observations assimilated). As a basis for comparison, reanalysis climatologies are compared with an observation-based climatology. Results show that reanalyses, specially high-resolution products, lead to very similar climatologies of the frequency, intensity, duration, and size of east coast lows when using spatially smoothed (about 300-km horizontal grid meshes) mean sea level pressure fields as input data. Moreover, at these coarse horizontal scales, monthly, interannual, and spatial variabilities appear to be very similar across the various reanalyses with a generally stronger agreement between winter events compared with summer ones. Results also show that, when looking at cyclones using reanalysis data at their native resolution (approaching 50-km grid spacing for the most recent products), uncertainties related to the frequency, intensity, and size of lows are very large and it is not clear which reanalysis, if any, gives a better description of cyclones. Further work is needed in order to evaluate the usefulness of the finescale information in modern reanalyses and to better understand the sources of their differences.

Abstract Recent studies have used numerical models to estimate the collection efficiency of solid precipitation gauges when exposed to the wind in both shielded and unshielded configurations. The models used computational fluid dynamics (CFD) simulations of the airflow pattern generated by the aerodynamic response to the gauge–shield geometry. These are used as initial conditions to perform Lagrangian tracking of solid precipitation particles. Validation of the results against field observations yielded similarities in the overall behavior, but the model output only approximately reproduced the dependence of the experimental collection efficiency on wind speed. This paper presents an improved snowflake trajectory modeling scheme due to the inclusion of a dynamically determined drag coefficient. The drag coefficient was estimated using the local Reynolds number as derived from CFD simulations within a time-independent Reynolds-averaged Navier–Stokes approach. The proposed dynamic model greatly improves the consistency of results with the field observations recently obtained at the Marshall Field winter precipitation test bed in Boulder, Colorado.

It is increasingly being recognized that global ecological research requires novel methods and strategies in which to combine process‐based ecological models and data in cohesive, systematic ways. In process‐based model applications, inherent spatial and temporal heterogeneities found within terrestrial ecosystems may lead to the uncertainties of model predictions. To reduce simulation uncertainties due to inaccurate model parameters, the Markov Chain Monte Carlo (MCMC) method was applied in this study to improve the estimations of four key parameters used in the process‐based ecosystem model of TRIPLEX‐FLUX. These four key parameters include a maximum photosynthetic carboxylation rate of 25°C (Vmax), an electron transport (Jmax) light‐saturated rate within the photosynthetic carbon reduction cycle of leaves, a coefficient of stomatal conductance (m), and a reference respiration rate of 10°C (R10). Seven forest flux tower sites located across North America were used to investigate and facilitate understanding of the daily variation in model parameters for three deciduous forests, three evergreen temperate forests, and one evergreen boreal forest. Eddy covariance CO 2 exchange measurements were assimilated to optimize the parameters in the year 2006. After parameter optimization and adjustment took place, net ecosystem production prediction significantly improved (by approximately 25%) compared to the CO 2 flux measurements taken at the seven forest ecosystem sites. Results suggest that greater seasonal variability occurs in broadleaf forests in respect to the selected parameters than in needleleaf forests. This study also demonstrated that the model‐data fusion approach by incorporating MCMC method is able to better estimate parameters and improve simulation accuracy for different ecosystems located across North America.