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Dynamical downscaling (DD) consists in using archives of Coupled Global Climate Models (CGCM) simulations as the atmospheric and sea-surface boundary conditions (BC) to drive nested, Regional Climate Model (RCM) simulations. Biases in the CGCM-generated driving BC, however, can have detrimental impacts on RCM performance. It is well documented for the historical period that CGCM-simulated sea-surface temperatures (SST) suffer substantial biases, especially important near coastal regions. Assuming that these SST biases are time-invariant, they could in principle be subtracted from century-long CGCM projections before being used to drive RCMs. This paper investigates the performance of a 3-step DD approach as follows. The CGCM-simulated sea-surface temperatures (SST) are first empirically corrected by subtracting their systematic biases; the corrected SST are then used as ocean surface BC for an atmosphere-only GCM (AGCM) simulation; finally this AGCM simulation provides the atmospheric lateral BC to drive an RCM simulation. This is what we refer to as the 3-step approach CGCM–AGCM–RCM of DD, which can be compared to the traditional 2-step approach CGCM–RCM consisting of driving an RCM simulation directly by CGCM-generated BC. In this paper we compare the results obtained with the two approaches, for present and future climates under RCP8.5, using the fifth-generation Canadian Regional Climate Model (CRCM5) with a grid mesh of 0.22° over the North American CORDEX domain, driven by two CMIP5 models: the Canadian Earth System Model of the Canadian Centre for Climate modelling and analysis (CanESM2) and the Earth System Model of the Max-Planck-Institut für Meteorologie (MPI-ESM-MR). The results show that, in current climate, the seasonal-mean 2-m temperature fields simulated with the 3-step DD have generally smaller biases with respect to the observations than those simulated with the 2-step DD; in fact the performance of the 3-step DD simulations often approaches that of the reanalyses-driven simulation. For the seasonal-mean precipitation field, however, the differences between the two DD methods are not conclusive. Differences between the projected climate changes with the two DD methods vary substantially depending upon the variable being considered. Differences are particularly important for temperature: over the bulk of the North American continent, the 3-step DD projects more warming in winter and less in summer. This result highlights the nonlinearities of the climate system, and constitutes an additional measure of uncertainty with DD. [ABSTRACT FROM AUTHOR]

Orographic precipitation and snowpack provide a vital water resource for the western U.S., while convective precipitation accounts for a significant part of annual precipitation in the eastern U.S. As a result, water managers are keenly interested in their fate under climate change. However, previous studies of water cycle changes in the U.S. have been conducted with climate models of relatively coarse resolution, leading to potential misrepresentation of key physical processes. This paper presents results from a high-resolution climate change simulation that permits convection and resolves mesoscale orography at 4-km grid spacing over much of North America using the Weather Research and Forecasting (WRF) model. Two 13-year simulations were performed, consisting of a retrospective simulation (October 2000-September 2013) with initial and boundary conditions from ERA-interim and a future climate sensitivity simulation with modified reanalysis-derived initial and boundary conditions through adding the CMIP5 ensemble-mean high-end emission scenario climate change. The retrospective simulation is evaluated by validating against Snowpack Telemetry (SNOTEL) and an ensemble of gridded observational datasets. It shows overall good performance capturing the annual/seasonal/sub-seasonal precipitation and surface temperature climatology except for a summer dry and warm bias in the central U.S. In particular, the WRF seasonal precipitation agrees with SNOTEL observations within a few percent over the mountain ranges, providing confidence in the model's estimation of western U.S. seasonal snowfall and snowpack. The future climate simulation forced with warmer and moister perturbed boundary conditions enhances annual and winter-spring-fall seasonal precipitation over most of the contiguous United States (CONUS), but suppresses summertime precipitation in the central U.S. The WRF-downscaled climate change simulations provide a high-resolution dataset (i.e., High-Resolution CONUS downscaling, HRCONUS) to the community for studying one possible scenario of regional climate changes and impacts. [ABSTRACT FROM AUTHOR]

Surface wind speed is a key climatic variable of interest in many applications, including assessments of storm-related infrastructure damage and feasibility studies of wind power generation. In this work and a companion paper (van der Kamp et al. ), the relationship between local surface wind and large-scale climate variables was studied using multiple regression analysis. The analysis was performed using monthly mean station data from British Columbia, Canada and large-scale climate variables (predictors) from the NCEP-2 reanalysis over the period 1979-2006. Two regression-based methodologies were compared. The first relates the annual cycle of station wind speed to that of the large-scale predictors at the closest grid box to the station. It is shown that the relatively high correlation coefficients obtained with this method are attributable to the dominant influence of region-wide seasonality, and thus contain minimal information about local wind behaviour at the stations. The second method uses interannually varying data for individual months, aggregated into seasons, and is demonstrated to contain intrinsically local information about the surface winds. The dependence of local wind speed upon large-scale predictors over a much larger region surrounding the station was also explored, resulting in 2D maps of spatial correlations. The cross-validated explained variance using the interannual method was highest in autumn and winter, ranging from 30 to 70% at about a dozen stations in the region. Reasons for the limited predictive skill of the regressions and directions for future progress are reviewed. [ABSTRACT FROM AUTHOR]

Large-scale climate response to the spatial and temporal changes of anthropogenic aerosols are investigated in comparison with greenhouse gas (GHG) forcing using Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations during 1930–2010. Globally, increasing anthropogenic aerosols in the Northern Hemisphere (NH) since the industrial revolution generates a North–South interhemispherically asymmetric climate response pattern. But this feature only dominates the historical climate change early in the twentieth century. In the second half of the twentieth century, anthropogenic aerosol emissions increase monotonically in Asia, but increase first and then decrease rapidly over Europe and North America. The shift of aerosol emissions from the western mid-latitude NH to the eastern low-latitude NH induces distinct climate response patterns compared with its global increase effect, anchoring an equatorial symmetric tropical sea surface temperature (SST) cooling and precipitation decrease, which resembles that in the GHG-induced response patterns with sign reversed. After the mid-1970s, with declining aerosol emissions over Europe and North America and increasing emissions in Asia, anthropogenic aerosol forcing generates a northward recovery of the tropical rainfall with little response in the tropical SST anomalies due to the cancellation effect of the distinct aerosol emissions conditions between the western and the eastern NH. While GHG forcing dominates observed climate change in the twentieth century, the distinct climate response patterns to the spatial and temporal evolutions of anthropogenic aerosol forcing highlight its important role in shaping the regional climate changes. [ABSTRACT FROM AUTHOR]

Convection-permitting models (CPM) with at least 4 km horizontal grid spacing enable the cumulus parameterization to be switched off and thus simulate convective processes more realistically than coarse resolution models. This study investigates if a North American scale CPM can reproduce the observed warm season precipitation diurnal cycle on a climate scale. Potential changes in the precipitation diurnal cycle characteristics at the end of the twenty first century are also investigated using the pseudo global warming approach under a high-end anthropogenic emission scenario (RCP8.5). Simulations are performed with the Advanced Research Weather Research and Forecasting (ARW-WRF) model with 4-km horizontal grid spacing. Results from the WRF historical run (2001–2013) are evaluated against hourly precipitation from 2903 weather stations and a gridded hourly precipitation product in the U.S. The magnitude and timing of the diurnal cycle peak are realistically simulated in most of the U.S. and southern Canada. The model also captures the transition from afternoon precipitation peaks eastward of the Rocky Mountains to night peaks in the central U.S., which is related to propagating mesoscale convective systems. However, the historical climate simulation does not capture the observed early morning peaks in the central U.S. and overestimates the magnitude of the diurnal precipitation peak in the southeast region. In the simulation of the future climate, both the precipitation amount of the diurnal cycle and precipitation intensity increase throughout the domain, along with an increase in precipitation frequency in the northern region of the domain in May. These increases indicate a clear intensification of the hydrologic cycle during the warm season with potential impacts on future water resources, agriculture, and flooding. [ABSTRACT FROM AUTHOR]

Climate downscaling using regional climate models (RCMs) has been widely used to generate local climate change information needed for climate change impact assessments and other applications. Six-hourly data from individual simulations by global climate models (GCMs) are often used as the lateral forcing for the RCMs. However, such forcing often contains both internal variations and externally-forced changes, which complicate the interpretation of the downscaled changes. Here, we describe a new approach to construct representative forcing for RCM-based climate downscaling and discuss some related issues. The new approach combines the transient weather signal from one GCM simulation with the monthly mean climate states from the multi-model ensemble mean for the present and future periods, together with a bias correction term. It ensures that the mean climate differences in the forcing data between the present and future periods represent externally-forced changes only and are representative of the multi-model ensemble mean, while changes in transient weather patterns are also considered based on one select GCM simulation. The adjustments through the monthly fields are comparable in magnitude to the bias correction term and are small compared with the variations in 6-hourly data. Any inconsistency among the independently adjusted forcing fields is likely to be small and have little impact. For quantifying the mean response to future external forcing, this approach avoids the need to perform RCM large ensemble simulations forced by different GCM outputs, which can be very expensive. It also allows changes in transient weather patterns to be included in the lateral forcing, in contrast to the Pseudo Global Warming (PGW) approach, in which only the mean climate change is considered. However, it does not address the uncertainty associated with internal variability or inter-model spreads. The simulated transient weather changes may also be unrepresentative of other models. This new approach has been applied to construct the forcing data for the second phase of the WRF-based downscaling over much of North America with 4 km grid spacing. [ABSTRACT FROM AUTHOR]

Recently, there has been increasing evidence that Arctic warming and extreme cold events over the northern continents are intimately related. Here, we examine how well current climate models simulate the observed relationship between Arctic warming and extratropical cold winters based on historical simulations of the Coupled Model Intercomparison Project Phase 5 (CMIP5). It is shown that most climate models simulate the observed relation reasonably well. In the models, the regional centers of the observed Arctic warming such as the Barents–Kara Seas and the East Siberian–Chukchi Seas are closely associated with the cold winters over East Asia and North America, respectively. However, we also found significant diversity among models. Analyses from the inter-model diversity suggest that atmospheric teleconnection patterns, such as the eastward expansion of the surface high and downstream development of the upper-level cyclonic flow, are keys to the link between Arctic variation and extratropical climate. Temperature budget analysis reveals that these two lower- and upper-level circulations contribute to the leading anomalous cold advection into the downstream regions. [ABSTRACT FROM AUTHOR]

Drylands are one of the most sensitive areas to climate change. Many previous studies assessed the impact of 1.5 °C and 2 °C warming targets using transient warming scenarios by representative concentration pathways of CMIP5. Here we compared the climate changes over global drylands in transient and stabilized 1.5 °C and 2 °C warmer worlds using Community Earth System Model simulations. The projections indicate a warming of 2.3 °C (1.6 °C) over drylands could occur in a stabilized 2 °C (1.5 °C) warmer world by the end of this century. The warming in drier regions is higher and the hyper-arid areas would experience warming of 2.4 °C (1.8 °C). Comparing the 2 °C to 1.5 °C warming targets, the additional 0.5 °C warming will lead to ~ 1.0 °C warming in drylands of Eurasia and North America. Responding to the 2 °C warming, the increased precipitation (21.8–42.6 mm/year) is not enough to offset the increased PET (88.3–101.7 mm/year) over drylands, resulting in the drylands expansion, and the additional 0.5 °C global warming will aggravate the drought in drylands in southern North America and North Africa. Compared to the stabilized 2 °C warming target, controlling the global warming to within 1.5 °C will reduce the warming in drylands by 0.7 °C, and reduce the drylands expansion relative to 1961–1990 by ~ 44%. Compared to the stabilized warming scenarios, the temperature response and drylands area coverage increase are higher in the transient warming scenarios, but the difference of temperature caused by additional 0.5 °C global warming and the precipitation increase in drylands are lower. [ABSTRACT FROM AUTHOR]

Previous studies have demonstrated that atmospheric diabatic heating over the Tibetan Plateau (TP) exerts significant influences on the "upstream" climate of the Atlantic-African-European sector in boreal summer. Using the NCAR Community Earth System Model, this study demonstrates that the TP-induced change in North Atlantic sea surface temperature (SST) including evident warming over the mid-latitude North Atlantic and cooling over the south can in turn modulate the above TP impact. Compared with the TP heating experiment without Atlantic SST variation, anomalous wave train pattern appears with north-northeastward downstream influences when the change in Atlantic SST is considered. The wave train pattern is characterized by three positive centers over the North Atlantic, the Arctic Ocean, and east of Japan, and four negative centers over northeastern North America, North Europe, the mid-Atlantic, and the northwestern Pacific. It intensifies the northern portions of the TP-induced tropospheric anticyclones over the extratropical North Atlantic and the cyclones over northeastern North America and North Europe. Correspondingly, precipitation decreases over the northwestern Atlantic but increases over northeastern North America and North Europe. Due to the easterly anomalies on the southern side of the weakened thermal low over subtropical Africa, precipitation over the Sahel decreases, indicating a weakening of TP-induced precipitation dipole over the tropical eastern Atlantic and West Africa when the Atlantic SST influence is considered. Overall, the modulation of Atlantic SST variation accounts for above 20 percent of the upstream climate signals induced by the TP thermal effect. [ABSTRACT FROM AUTHOR]

The Asian-Bering-North American (ABNA) teleconnection index is constructed from the normalized 500-hPa geopotential field by excluding the Pacific-North American pattern contribution. The ABNA pattern features a zonally elongated wavetrain originating from North Asia and flowing downstream across Bering Sea and Strait towards North America. The large-scale teleconnection is a year-round phenomenon that displays strong seasonality with the peak variability in winter. North American surface temperature and temperature extremes, including warm days and nights as well as cold days and nights, are significantly controlled by this teleconnection. The ABNA pattern has an equivalent barotropic structure in the troposphere and is supported by synoptic-scale eddy forcing in the upper troposphere. Its associated sea surface temperature anomalies exhibit a horseshoe-shaped structure in the North Pacific, most prominent in winter, which is driven by atmospheric circulation anomalies. The snow cover anomalies over the West Siberian plain and Central Siberian Plateau in autumn and spring and over southern Siberia in winter may act as a forcing influence on the ABNA pattern. The snow forcing influence in winter and spring can be traced back to the preceding season, which provides a predictability source for this teleconnection and for North American temperature variability. The ABNA associated energy budget is dominated by surface longwave radiation anomalies year-round, with the temperature anomalies supported by anomalous downward longwave radiation and damped by upward longwave radiation at the surface. [ABSTRACT FROM AUTHOR]

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]

A 20-km regional climate model (RCM) dynamically downscaled the Community Climate System Model version 4 (CCSM4) to compare 32-year historical and future 'end-of-the-century' climatologies of the North American Monsoon (NAM). CCSM4 and other phase 5 Coupled Model Intercomparison Project models have indicated a delayed NAM and overall general drying trend. Here, we test the suggested mechanism for this drier NAM where increasing atmospheric static stability and reduced early-season evapotranspiration under global warming will limit early-season convection and compress the mature-season of the NAM. Through our higher resolution RCM, we found the role of accelerated evaporation under a warmer climate is likely understated in coarse resolution models such as CCSM4. Improving the representation of mesoscale interactions associated with the Gulf of California and surrounding topography produced additional surface evaporation, which overwhelmed the convection-suppressing effects of a warmer troposphere. Furthermore, the improved land-sea temperature gradient helped drive stronger southerly winds and greater moisture transport. Finally, we addressed limitations from inherent CCSM4 biases through a form of mean bias correction, which resulted in a more accurate seasonality of the atmospheric thermodynamic profile. After bias correction, greater surface evaporation from average peak GoC SSTs of 32 °C compared to 29 °C from the original CCSM4 led to roughly 50 % larger changes to low-level moist static energy compared to that produced by the downscaled original CCSM4. The increasing destabilization of the NAM environment produced onset dates that were one to 2 weeks earlier in the core of the NAM and northern extent, respectively. Furthermore, a significantly more vigorous NAM signal was produced after bias correction, with >50 mm month increases to the June-September precipitation found along east and west coasts of Mexico and into parts of Texas. A shift towards more extreme daily precipitation was found in both downscaled climatologies, with the bias-corrected climatology containing a much more apparent and extreme shift. [ABSTRACT FROM AUTHOR]

Inland-penetrating atmospheric rivers (ARs) affect the United States Southwest and significantly contribute to cool season precipitation. In this study, we examine the results from an ensemble of dynamically downscaled simulations from the North American Regional Climate Change Assessment Program (NARCCAP) and their driving general circulation models (GCMs) in order to determine statistically significant changes in the intensity of the cool season ARs impacting Arizona and the associated precipitation. Future greenhouse gas emissions follow the A2 emission scenario from the Intergovernmental Panel on Climate Change Fourth Assessment Report simulations. We find that there is a consistent and clear intensification of the AR-related water vapor transport in both the global and regional simulations which reflects the increase in water vapor content due to warmer atmospheric temperatures, according to the Clausius-Clapeyron relationship. However, the response of AR-related precipitation intensity to increased moisture flux and column-integrated water vapor is weak and no significant changes are projected either by the GCMs or the NARCCAP models. This lack of robust precipitation variations can be explained in part by the absence of meaningful changes in both the large-scale water vapor flux convergence and the maximum positive relative vorticity in the GCMs. Additionally, some global models show a robust decrease in relative humidity which may also be responsible for the projected precipitation patterns. [ABSTRACT FROM AUTHOR]

Explosive cyclones are rapidly intensifying low pressure systems generating severe wind speeds and heavy precipitation primarily in coastal and marine environments. This study presents the first analysis on how explosive cyclones respond to climate change in the extratropics of the Northern Hemisphere. An objective-feature tracking algorithm is used to identify and track cyclones from 23 CMIP5 climate models for the recent past (1981-1999) and future (2081-2099). Explosive cyclones are projected to shift northwards by about $$2.2^\circ$$ latitude on average in the northern Pacific, with fewer and weaker events south of $$45^\circ \hbox {N}$$ , and more frequent and stronger events north of this latitude. This shift is correlated with a poleward shift of the jet stream in the inter-model spread ( $$R=0.56$$ ). In the Atlantic, the total number of explosive cyclones is projected to decrease by about 17 % when averaging across models, with the largest changes occurring along North America's East Coast. This reduction is correlated with a decline in the lower-tropospheric Eady growth rate ( $$R=0.51$$ ), and is stronger for models with smaller frequency biases ( $$R=-0.65$$ ). The same region is also projected to experience a small intensification of explosive cyclones, with larger vorticity values for models that predict stronger increases in the speed of the jet stream ( $$R=0.58$$ ). This strengthening of the jet stream is correlated with an enhanced sea surface temperature gradient in the North Atlantic ( $$R=-0.63$$ ). The inverse relationship between model bias and projection, and the role of model resolution are discussed. [ABSTRACT FROM AUTHOR]

A multi-millennial simulation with a coupled global climatic model has been used to investigate extreme rainfall events, mainly droughts, over North America. A rainfall index, based on the US Dust Bowl region, was used to generate a time series from which the extreme events could be identified. A very wide range of drought and pluvial multiyear sequences was obtained, all attributable to internal climatic variability. This time series reproduced the basic characteristics of the corresponding observed time series. Composites of years with negative rainfall anomalies over North America from the simulation replicated the observed rainfall composite for the Dust Bowl era, both in spatial character and intensity. Examination of individual years of a simulated composite revealed not only a wide range of rainfall anomaly patterns, dominated by drought conditions, but also ENSO distributions that included El Niño events as well as the expected La Niña events. Composites for pluvial conditions over North America were associated with composited El Niño events, as expected. Correlation of the simulated Dust Bowl rainfall with global surface temperatures identified a principal connection with the ENSO region. No systematic relationship was obtained in the simulation between the Atlantic multidecadal oscillation and Dust Bowl region rainfall, with the simulated oscillation having a much more variable periodicity than that found in the limited observations. However, a marked connection was found for SST anomalies adjacent to the northeast coast of North America, but this appears to be forced by ENSO events. A scatter diagram of NINO3.4 SST anomalies with the Dust Bowl region rainfall anomalies, for observations and the simulation, revealed inconsistencies between the occurrence of an ENSO event and the 'expected' rainfall anomaly. This, and other analysis, resulted in the conclusion that annual or longer term rainfall predictions over North America, with any systematic confidence, are unlikely because of stochastic influences inherent in the climatic system associated with internal climatic variability. [ABSTRACT FROM AUTHOR]

This study analyzes areal changes and regional climate variations in global semi-arid regions over 61 years (1948-2008) and investigates the dynamics of global semi-arid climate change. The results reveal that the largest expansion of drylands has occurred in semi-arid regions since the early 1960s. This expansion of semi-arid regions accounts for more than half of the total dryland expansion. The area of semi-arid regions in the most recent 15 years studied (1990-2004) is 7 % larger than that during the first 15 years (1948-1962) of the study period; this expansion totaled 0.4 × 10 and 1.2 × 10 km within the American continents and in the Eastern Hemisphere, respectively. Although semi-arid expansion occurred in both regions, the shifting patterns of the expansion are different. Across the American continents, the newly formed semi-arid regions developed from arid regions, in which the climate became wetter. Conversely, in the continental Eastern Hemisphere, semi-arid regions replaced sub-humid/humid regions, in which the climate became drier. The climate change in drying semi-arid regions over East Asia is primarily dominated by a weakened East Asian summer monsoon, while the wetting of semi-arid regions over North America is primarily controlled by enhanced westerlies. [ABSTRACT FROM AUTHOR]

Using observational pentad data of the recent 34 Northern Hemisphere extended winters, subseasonal variability of surface air temperature (SAT) over North America is analyzed. The four leading modes of subseasonal SAT variability, that are identified with an empirical orthogonal function (EOF) analysis, account for about 60% of the total variance. The first (EOF1) and second (EOF2) modes are independent of other modes, and thus are likely controlled by distinct processes. The third (EOF3) and fourth (EOF4) modes, however, tend to have a phase shift to each other in space and time, indicating that part of their variability is related to a common process and represent a propagating pattern over North America. Lagged regression analysis is conducted to identify the precursors of large-scale atmospheric circulation for each mode a few pentads in advance, and to understand the processes that influence the subseasonal SAT variability and the predictability signal sources. EOF1 is found to be closely related to the Pacific-North American (PNA) circulation pattern and at least part of its variability is preceded by the East Asian cold surge. The cold surge leads to low-level convergence and enhanced convection in the tropical central Pacific which in turn induces the PNA. EOF2 tends to oscillate at a period of about 70 days, and is influenced by the low-frequency component of the Madden-Julian Oscillation (MJO). On the other hand, EOF3 and EOF4 are connected to the high-frequency part of the MJO which has a period range of 30-50 days. These findings would help understanding the mechanisms of subseasonal surface air temperature variability in North America and improving weather predictions on a subseasonal time scale. [ABSTRACT FROM AUTHOR]

Climate change is expected to alter the mean and variability of future spring and summer drought and wet conditions during the twenty-first century across North America, as characterized by the Standardized Precipitation Index (SPI). Based on Coupled Model Intercomparison Project phase 5 simulations, statistically significant increases are projected in mean spring SPI over the northern part of the continent, and drier conditions across the southwest. Dry conditions in summer also increase, particularly throughout the central Great Plains. By end of century, greater changes are projected under a higher radiative forcing scenario (RCP 8.5) as compared to moderate (RCP 6.0) and lower (RCP 4.5). Analysis of projected changes standardized to a range of global warming thresholds from +1 to +4 °C reveals a consistent spatial pattern of wetter conditions in the northern and drier conditions in the southwestern part of the continent in spring that intensifies under increased warming, suggesting that the magnitude of projected changes in wetness and drought may scale with global temperature. For many regions, SPI interannual variability is also projected to increase (even for regions that are projected to become drier), indicating that climate may become more extreme under greater warming, with increased frequency of both extreme dry and wet seasons. Quantifying the direction and magnitude of projected future trends from global warming is key to informing strategies to mitigate human influence on climate and help natural and managed resources adapt. [ABSTRACT FROM AUTHOR]

The interdecadal and the interannual variability of the global monsoon (GM) precipitation over the area which is chosen by the definition of Wang and Ding (Geophys Res Lett 33: L06711, ) are investigated. The recent increase of the GM precipitation shown in previous studies is in fact dominant during local summer. It is evident that the GM monsoon precipitation has been increasing associated with the positive phase of the interdecadal Pacific oscillation in recent decades. Against the increasing trend of the GM summer precipitation in the Northern Hemisphere, its interannual variability has been weakened. The significant change-point for the weakening is detected around 1993. The recent weakening of the interannual variability is related to the interdecadal changes in interrelationship among the GM subcomponents around 1993. During P1 (1979-1993) there is no significant interrelationship among GM subcomponents. On the other hand, there are significant interrelationships among the Asian, North American, and North African summer monsoon precipitations during P2 (1994-2009). It is noted that the action center of the interdecadal changes is the Asian summer (AS) monsoon system. It is found that during P2 the Western North Pacific summer monsoon (WNPSM)-related variability is dominant but during P1 the ENSO-related variability is dominant over the AS monsoon region. The WNPSM-related variability is rather related to central-Pacific (CP) type ENSO rather than the eastern-Pacific (EP) type ENSO. Model experiments confirm that the CP type ENSO forcing is related to the dominant WNPSM-related variability and can be responsible for the significant interrelationship among GM subcomponents. [ABSTRACT FROM AUTHOR]

The fifth-generation Canadian Regional Climate Model (CRCM5) was used to dynamically downscale two Coupled Global Climate Model (CGCM) simulations of the transient climate change for the period 1950–2100, over North America, following the CORDEX protocol. The CRCM5 was driven by data from the CanESM2 and MPI-ESM-LR CGCM simulations, based on the historical (1850–2005) and future (2006–2100) RCP4.5 radiative forcing scenario. The results show that the CRCM5 simulations reproduce relatively well the current-climate North American regional climatic features, such as the temperature and precipitation multiannual means, annual cycles and temporal variability at daily scale. A cold bias was noted during the winter season over western and southern portions of the continent. CRCM5-simulated precipitation accumulations at daily temporal scale are much more realistic when compared with its driving CGCM simulations, especially in summer when small-scale driven convective precipitation has a large contribution over land. The CRCM5 climate projections imply a general warming over the continent in the 21st century, especially over the northern regions in winter. The winter warming is mostly contributed by the lower percentiles of daily temperatures, implying a reduction in the frequency and intensity of cold waves. A precipitation decrease is projected over Central America and an increase over the rest of the continent. For the average precipitation change in summer however there is little consensus between the simulations. Some of these differences can be attributed to the uncertainties in CGCM-projected changes in the position and strength of the Pacific Ocean subtropical high pressure. [ABSTRACT FROM AUTHOR]

In this study, an ensemble of four multi-year climate simulations is performed with the regional climate model ALADIN to evaluate its ability to simulate the climate over North America in the CORDEX framework. The simulations differ in their driving fields (ERA-40 or ERA-Interim) and the nudging technique (with or without large-scale nudging). The validation of the simulated 2-m temperature and precipitation with observationally-based gridded data sets shows that ALADIN performs similarly to other regional climate models that are commonly used over North America. Large-scale nudging improves the temporal correlation of the atmospheric circulation between ALADIN and its driving field, and also reduces the warm and dry summer biases in central North America. The differences between the simulations driven with different reanalyses are small and are likely related to the regional climate model's induced internal variability. In general, the impact of different driving fields on ALADIN is smaller than that of large-scale nudging. The analysis of the multi-year simulations over the prairie and the east taiga indicates that the ALADIN 2-m temperature and precipitation interannual variability is similar or larger than that observed. Finally, a comparison of the simulations with observations for the summer 1993 shows that ALADIN underestimates the flood in central North America mainly due to its systematic dry bias in this region. Overall, the results indicate that ALADIN can produce a valuable contribution to CORDEX over North America. [ABSTRACT FROM AUTHOR]

In recent decades, the need of future climate information at local scales have pushed the climate modelling community to perform increasingly higher resolution simulations and to develop alternative approaches to obtain fine-scale climatic information. In this article, various nested regional climate model (RCM) simulations have been used to try to identify regions across North America where high-resolution downscaling generates fine-scale details in the climate projection derived using the 'delta method'. Two necessary conditions were identified for an RCM to produce added value (AV) over lower resolution atmosphere-ocean general circulation models in the fine-scale component of the climate change (CC) signal. First, the RCM-derived CC signal must contain some non-negligible fine-scale information-independently of the RCM ability to produce AV in the present climate. Second, the uncertainty related with the estimation of this fine-scale information should be relatively small compared with the information itself in order to suggest that RCMs are able to simulate robust fine-scale features in the CC signal. Clearly, considering necessary (but not sufficient) conditions means that we are studying the 'potential' of RCMs to add value instead of the AV, which preempts and avoids any discussion of the actual skill and hence the need for hindcast comparisons. The analysis concentrates on the CC signal obtained from the seasonal-averaged temperature and precipitation fields and shows that the fine-scale variability of the CC signal is generally small compared to its large-scale component, suggesting that little AV can be expected for the time-averaged fields. For the temperature variable, the largest potential for fine-scale added value appears in coastal regions mainly related with differential warming in land and oceanic surfaces. Fine-scale features can account for nearly 60 % of the total CC signal in some coastal regions although for most regions the fine scale contributions to the total CC signal are of around ∼5 %. For the precipitation variable, fine scales contribute to a change of generally less than 15 % of the seasonal-averaged precipitation in present climate with a continental North American average of ∼5 % in both summer and winter seasons. In the case of precipitation, uncertainty due to sampling issues may further dilute the information present in the downscaled fine scales. These results suggest that users of RCM simulations for climate change studies in a delta method framework have little high-resolution information to gain from RCMs at least if they limit themselves to the study of first-order statistical moments. Other possible benefits arising from the use of RCMs-such as in the large scale of the downscaled fields- were not explored in this research. [ABSTRACT FROM AUTHOR]

Monthly snow water equivalent (SWE) station observations and gridded temperature data are used to identify mechanisms by which warming affects the temporal and geographical structure of changes in western North American mountain snowpack. We first exploit interannual variability to demonstrate the sensitivity of snowpack to temperature during the various phases of the snow season. We show that mechanisms whereby temperature affects snowpack emerge in the mid to late portion of the snow season (March through May), but are nearly absent during the earliest phase (February), when temperatures are generally well below freezing. The mid to late snow season is precisely when significant loss of snowpack is seen at nearly all locations over the past few decades, both through decreases in snow accumulation and increases in snowmelt. At locations where April 1st SWE has been increasing over the past few decades, the increase is entirely due to a significant enhancement of accumulation during the earliest phase of the snow season, when the sensitivity analysis indicates that temperature is not expected to affect snowpack. Later in the snow season, these stations exhibit significant snowpack loss comparable to the other stations. Based on this analysis, it is difficult to escape the conclusion that recent snowpack changes in western North America are caused by regional-scale warming. Given predictions of future warming, a further reduction in late season snowpack and advancement in the onset of snowmelt should be expected in the coming decades throughout the region. [ABSTRACT FROM AUTHOR]

The influence of prescribed changes in vegetation on the climate of the North American monsoon region is examined using the National Center for Atmospheric Research Community Climate System Model Version 3.5 (NCAR CCSM3.5). Initial value ensemble experiments are performed in which the vegetation cover fraction over the North American monsoon region is reduced by 0.2 and the intra-annual climatic response is assessed probabilistically in each one-year ensemble experiment. Changes in the surface radiation budget include decreases in sensible and latent heat fluxes and increases in upward longwave and downward shortwave radiation fluxes, with small net changes in surface albedo. The climatic responses to reduced vegetation cover fraction include year-round increases in ground and surface air temperature, a dampened hydrologic cycle with decreased springtime evaporation, springtime and autumnal precipitation, and autumnal cloud cover, and enhanced atmospheric subsidence in late autumn. Decreased vegetation shifts the monsoon season over the Southwest United States earlier in the year. Within the North American monsoon region, the most robust vegetation feedbacks to climate are found over woody landscapes. [ABSTRACT FROM AUTHOR]

Research on the forcing of drought and pluvial events over North America is dominated by general circulation model experiments that often have operational limitations (e.g., computational expense, ability to simulate relevant processes, etc). We use a statistically based modeling approach to investigate sea surface temperature (SST) forcing of the twentieth century pluvial (1905-1917) and drought (1932-1939, 1948-1957, 1998-2002) events. A principal component (PC) analysis of Palmer Drought Severity Index (PDSI) from the North American Drought Atlas separates the drought variability into five leading modes accounting for 62% of the underlying variance. Over the full period spanning these events (1900-2005), the first three PCs significantly correlate with SSTs in the equatorial Pacific (PC 1), North Pacific (PC 2), and North Atlantic (PC 3), with spatial patterns (as defined by the empirical orthogonal functions) consistent with our understanding of North American drought responses to SST forcing. We use a large ensemble statistical modeling approach to determine how successfully we can reproduce these drought/pluvial events using these three modes of variability. Using Pacific forcing only (PCs 1-2), we are able to reproduce the 1948-1957 drought and 1905-1917 pluvial above a 95% random noise threshold in over 90% of the ensemble members; the addition of Atlantic forcing (PCs 1-2-3) provides only marginal improvement. For the 1998-2002 drought, Pacific forcing reproduces the drought above noise in over 65% of the ensemble members, with the addition of Atlantic forcing increasing the number passing to over 80%. The severity of the drought, however, is underestimated in the ensemble median, suggesting this drought intensity can only be achieved through internal variability or other processes. Pacific only forcing does a poor job of reproducing the 1932-1939 drought pattern in the ensemble median, and less than one third of ensemble members exceed the noise threshold (28%). Inclusion of Atlantic forcing improves the ensemble median drought pattern and nearly doubles the number of ensemble members passing the noise threshold (52%). Even with the inclusion of Atlantic forcing, the intensity of the simulated 1932-1939 drought is muted, and the drought itself extends too far into the southwest and southern Great Plains. To an even greater extent than the 1998-2002 drought, these results suggest much of the variance in the 1932-1939 drought is dependent on processes other than SST forcing. This study highlights the importance of internal noise and non SST processes for hydroclimatic variability over North America, complementing existing research using general circulation models. [ABSTRACT FROM AUTHOR]

Due to the chaotic and nonlinear nature of the atmospheric dynamics, it is known that small differences in the initial conditions (IC) of models can grow and affect the simulation evolution. In this study, we perform a quantitative diagnostic budget calculation of the various diabatic and dynamical contributions to the time evolution and spatial distribution of internal variability (IV) in simulations with the nested Canadian Regional Climate Model. We establish prognostic budget equations of the IV for the potential temperature and the relative vorticity fields. For both of these variables, the IV equations present similar terms, notably terms relating to the transport of IV by ensemble-mean flow and to the covariance of fluctuations acting on the gradient of the ensemble-mean state. We show the skill of these equations to diagnose the IV that took place in an ensemble of 20 3-month (summer season) simulations that differed only in their IC. Our study suggests that the dominant terms responsible for the large increase of IV are either the covariance term involving the potential temperature fluctuations and diabatic heating fluctuations, or the covariance of inter-member fluctuations acting upon ensemble-mean gradients. Our results also show that, on average, the third-order terms are negligible, but they can become important when the IV is large. [ABSTRACT FROM AUTHOR]

Through its various radiative effects and latent heat release, water plays a major role in the maintenance of climate. Therefore a better understanding of climate and climate changes requires a better understanding of the hydrological cycle. In this study we investigate the scale-decomposed atmospheric water budget over North America as simulated by the Canadian Regional Climate Model (CRCM) driven by the Canadian Coupled Global Climate Model (CGCM) under current conditions for 1961-1990 and the SRES A2 scenario for 2041-2070. A discrete cosine transform is applied to the atmospheric water budget variables in order to separate small scales that are resolved exclusively by the high-resolution CRCM, from larger scales resolved by both the CRCM and low-resolution driving CGCM. The moisture flux divergence is alternatively decomposed in terms of three scales of wind and humidity to provide nine interaction terms. Statistics of these fields are calculated for winter and summer seasons, and the local statistical significance of climate-change projections is tested. The contributions of each scale band to the water budget current climatology and to its evolution in a warmer climate are investigated, addressing the issue of the potential added value of smaller scales. Results show a time variability larger than the time mean for all variables, and a significant small-scale contribution to time variability, which is even dominant in summer, both in the current and future climates. Future climate exhibits an overall intensification of the hydrological cycle in winter, and more mixed changes in summer. Relative changes in the time mean and time variability appear comparable, and the contribution of each scale band to variability changes remains overall very consistent with their contribution to current climate variability. [ABSTRACT FROM AUTHOR]

A network of varve and dendrochronological time series that provide annual resolution of Boreal tree growth conditions and Arctic snow pack and melt variability were used to investigate the imprint of the Atlantic Multidecadal Oscillation (AMO) on continental hydroclimatic variability in northeastern and northern North America from 1550 to 1986 AD. The hydroclimatic proxies show a coherent, AMO-like spectral pattern active since the late sixteenth and the early eighteenth century in the Canadian Arctic and southeastern Boreal regions, respectively. Positive AMO phases are associated with more intense spring runoff in the Arctic and with longer growth season and increased summer moisture availability in the southeastern boreal forest. These results offer new insights about the widespread response of North American hydroclimate to low frequency changes in North Atlantic sea surface temperatures. [ABSTRACT FROM AUTHOR]

Supervolcanoes are large caldera systems that can expel vast quantities of ash, volcanic gases in a single eruption, far larger than any recorded in recent history. These super-eruptions have been suggested as possible catalysts for long-term climate change and may be responsible for bottlenecks in human and animal populations. Here, we consider the previously neglected climatic effects of a continent-sized ash deposit with a high albedo and show that a decadal climate forcing is expected. We use a coupled atmosphere-ocean General Circulation Model (GCM) to simulate the effect of an ash blanket from Yellowstone volcano, USA, covering much of North America. Reflectivity measurements of dry volcanic ash show albedo values as high as snow, implying that the effects of an ash blanket would be severe. The modeling results indicate major disturbances to the climate, particularly to oscillatory patterns such as the El Niño Southern Oscillation (ENSO). Atmospheric disruptions would continue for decades after the eruption due to extended ash blanket longevity. The climatic response to an ash blanket is not significant enough to instigate a change to stadial periods at present day boundary conditions, though this is one of several impacts associated with a super-eruption which may induce long-term climatic change. [ABSTRACT FROM AUTHOR]

The downscaling ability of a one-way nested regional climate model (RCM) is evaluated over a region subjected to strong surface forcing: the west of North America. The sensitivity of the results to the horizontal resolution jump and updating frequency of the lateral boundary conditions are also evaluated. In order to accomplish this, a perfect-model approach nicknamed the Big-Brother Experiment (BBE) was followed. The experimental protocol consists of first establishing a virtual-reality reference climate over a fairly large area by using the Canadian RCM with grid spacing of 45 km nested within NCEP analyses. The resolution of the simulated climate is then degraded to resemble that of operational general circulation models (GCM) or observation analyses by removing small scales; the filtered fields are then used to drive the same regional model, but over a smaller sub-area. This set-up permits a comparison between two simulations of the same RCM over a common region. The Big-Brother Experiment has been carried out for four winter months over the west coast of North America. The results show that complex topography and coastline have a strong positive impact on the downscaling ability of the one-way nesting technique. These surface forcings, found to be responsible for a large part of small-scale climate features, act primarily locally and yield good climate reproducibility. Precipitation over the Rocky Mountains region is a field in which such effect is found and for which the nesting technique displays significant downscaling ability. The best downscaling ability is obtained when the ratio of spatial resolution between the nested model and the nesting fields is less than 12, and when the update frequency is more than twice a day. Decreasing the spatial resolution jump from a ratio of 12 to six has more benefits on the climate reproducibility than a reduction of spatial resolution jump from two to one. Also, it is found that an update frequency of four times a day leads to a better downscaling than twice a day when a ratio of spatial resolution of one is used. On the other hand, no improvement was found by using high-temporal resolution when the driving fields were degraded in terms of spatial resolution. [ABSTRACT FROM AUTHOR]