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The variations of large-scale climatic controls and surface responses through the annual cycle during strong positive (El Niño) and negative (La Niña) phase ENSO events are analyzed to assess the within-year and among-year variations of climate anomalies. Data from the NCEP–NCAR reanalysis project are presented as small-multiple maps to illustrate the spatial and temporal variability in North American climate associated with extreme phases of ENSO. Temperature, mean sea level pressure, 500-mb geopotential heights, and 850-mb specific humidity have composite-anomaly patterns that exhibit the greatest degree of spatial and temporal coherence. In general, the composite-anomaly patterns for El Niño and La Niña events are of opposite sign, with stronger, more spatially coherent anomalies occurring during El Niño events than during La Niña events. However, the strength and coherency of the precipitation anomaly patterns are reduced in the interior intermountain west during both positive and negative phase of ENSO. The variations in precipitation anomalies are compared to the 500-mb omega and 850-mb specific humidity composite-anomaly patterns, which provide information on the controls of precipitation by large-scale vertical motions and moisture availability thus providing information on the specific mechanisms associated with precipitation variability during ENSO events. [ABSTRACT FROM AUTHOR]

The atmospheric moisture transport processes are of great importance to the occurrence and intensity of precipitation extremes. In this paper, we review the linkage between processes, including the large‐scale atmospheric circulation, atmospheric moisture transport, and extreme precipitation events. We first summarize the thermodynamic and dynamic processes and moisture transport trackings for historical precipitation extremes. We then focus on the contribution of three major atmospheric moisture transport pathways, that is, atmospheric rivers, low‐level jets, and tropical cyclones, to the occurrence and intensity of regional precipitation extremes. Studies on large‐scale atmospheric circulation driving water vapor transport for precipitation extremes over East Asia and North America were specifically reviewed for the understanding of physical mechanisms and predictability of moisture transport and extreme precipitation events. We then pay more attention to the effects of global warming on atmospheric moisture transport, and thus regional precipitation extremes from the perspectives of thermodynamic and dynamic changes of the atmosphere. In the end, we summarize future research challenges on the physical mechanisms of atmospheric moisture transport that are associated with regional precipitation extremes, especially under a warming climate. This article is categorized under: Science of Water > Water ExtremesScience of Water > Hydrological Processes [ABSTRACT FROM AUTHOR]

An important goal of the Climate Variability and Predictability (CLIVAR) research on the American monsoon systems is to determine the sources and limits of predictability of warm season precipitation, with emphasis on weekly to interannual time scales. This paper reviews recent progress in the understanding of the American monsoon systems and identifies some of the future challenges that remain to improve warm season climate prediction. Much of the recent progress is derived from complementary international programs in North and South America, namely, the North American Monsoon Experiment (NAME) and the Monsoon Experiment South America (MESA), with the following common objectives: 1) to understand the key components of the American monsoon systems and their variability, 2) to determine the role of these systems in the global water cycle, 3) to improve observational datasets, and 4) to improve simulation and monthly-to-seasonal prediction of the monsoons and regional water resources. Among the recent observational advances highlighted in this paper are new insights into moisture transport processes, description of the structure and variability of the South American low-level jet, and resolution of the diurnal cycle of precipitation in the core monsoon regions. NAME and MESA are also driving major efforts in model development and hydrologic applications. Incorporated into the postfield phases of these projects are assessments of atmosphere–land surface interactions and model-based climate predictability experiments. As CLIVAR research on American monsoon systems evolves, a unified view of the climatic processes modulating continental warm season precipitation is beginning to emerge. [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]

The U.S. Climate Reference Network (USCRN) was deployed between 2001 and 2008 for the purpose of yielding high-quality and temporally stable in situ climate observations in pristine environments over the twenty-first century. Given this mission, USCRN stations are engineered to operate largely autonomously with great reliability and accuracy. A triplicate approach is used to provide redundant measurements of temperature and precipitation at each location, allowing for observations at a specific time to be compared for quality control. This approach has proven to be robust in the most extreme environments, from extreme cold (−49°C) to extreme heat (++52°C), in areas of heavy precipitation (4700 mm yr−1), and in locations impacted by strong winds, freezing rain, and other hazards. In addition to a number of stations enduring extreme winter environments in Alaska and the northern United States, seven of the USCRN stations are located at elevations over 2000 m, including stations on Mauna Loa, Hawaii (3407 m) and on Niwot Ridge above Boulder, Colorado (2996 m). The USCRN temperature instruments and radiation shield have also been installed and run successfully at a station on the Quelccaya Ice Cap in Peru (5670 m). This paper reviews the performance of the USCRN station network during its brief lifetime and the potential utility of its triplicate temperature instrument configuration for measuring climate change at elevation. [ABSTRACT FROM AUTHOR]

Little guidance is available to assist wetland managers in developing climate adaptation plans. To facilitate development of recommendations for adaptation strategies, it is essential to first determine if or how wetland managers are addressing these challenges. We used an online survey to solicit feedback from wetland managers and biologists in the Southern Great Plains of North America to gain information on perceptions of wetland managers regarding climate change; assess how the effects of climate change are being addressed through management; and identify barriers to implementing climate change adaptation. The majority of wetland managers (63%) agreed they are currently experiencing effects of climate change in wetlands, and most respondents (76%) reported that changes in the timing of water availability throughout the year was the most likely impact. Managers reported using a diversity of approaches in managing for changing precipitation, with management of native and invasive plant species being the two most common practices. Lack of funding and personnel were the most commonly identified factors limiting manager's response to changing precipitation patterns. In addition, >50% of managers indicated uncertainty about the effects of climate change on wetlands as a barrier to management, which may relate to limited access to peer-reviewed science. While most of the management practices reported were short-term measures and may not reflect long-term adaptation for climate change, the fact that many managers are considering climate change in their management suggests that there is considerable opportunities to continue developing capacity for climate change adaptation in the region. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim The network structure of food webs plays an important role in the maintenance of diversity and ecosystem functioning in ecological communities. Previous research has found that ecosystem size, resource availability, assembly history and biotic interactions can potentially drive food web structure. However, the relative influence of climatic variables that drive broad-scale biogeographic patterns of species richness and composition has not been explored for food web structure. In this study, we assess the influence of broad-scale climatic variables in addition to known drivers of food web structure on replicate observations of a single aquatic food web, sampled from the leaves of the pitcher plant ( Sarracenia purpurea), at different geographic sites across a broad latitudinal and climatic range. Location Using standardized sampling methods, we conducted an extensive 'snapshot' survey of 780 replicated aquatic food webs collected from the leaves of the pitcher plant S. purpurea at 39 sites from northern Florida to Newfoundland and westward to eastern British Columbia. Methods We examined correlations of 15 measures of food web structure at the pitcher and site scales with geographic variation in temperature and precipitation, concentrations of nutrients from atmospheric nitrogen deposition, resource availability, ecosystem size and the abundance of the pitcher plant mosquito ( Wyeomyia smithii), a potential keystone species. Results At the scale of a single pitcher plant leaf, linkage density, species richness, measures of chain length and the proportion of omnivores in a web all increased with pitcher volume. Linkage density and species richness were greater at high-latitude sites, which experience low mean temperatures and precipitation and high annual variation in both of these variables. At the site scale, variation in 8 of the 15 food web metrics decreased at higher latitudes, and variation in measures of chain length increased with the abundance of mosquitoes. Main conclusions Ecosystem size and climatic variables related to latitude were most strongly correlated with network structure of the Sarracenia food web. However, in spite of large sample sizes, thorough standardized sampling and the large geographic extent of the survey, even the best-fitting models explained less than 40% of the variation in food web structure. In contrast to biogeographic patterns of species richness, food web structure was largely independent of broad-scale climatic variables. The large proportion of unexplained variance in our analyses suggests that stochastic assembly may be an important determinant of local food web structure. [ABSTRACT FROM AUTHOR]

Abstract: Climate models provide estimates of climatic change over periods of time in the ancient past. Macrophysical climate models (MCM) differ from the more widely used general circulation models (GCM), in that MCMs provide temporally high-resolution (~100years) and site-specific estimations of monthly values of climate variables such as temperature and precipitation. In this paper, seasonal changes in climate variables are modeled for six 14C-dated fossil localities in North America. Five of these localities represent the time of maximum extent of ice during the most recent glacial episode, the Full Glacial (25+–15ka), including one at the peak of the Last Glacial Maximum (17–15ka). The other locality represents the time as the ice began to recede, the Late Glacial (15–11ka). Seasonal variations in temperature and precipitation modeled by MCM are herein compared with interpretations of seasonal variation based upon oxygen isotopes from serially sampled hypsodont teeth (mostly Equus and Bison) collected from each of these localities. Additionally, the MCM-modeled seasonal variations are used to predict the expected abundances of different plant functional groups (PFG) during those times, especially C3 and C4 functional groups, using modern relationships. These predictions are compared with carbon isotopic values from the same teeth. The importance of atmospheric pCO2 for the relative abundance of plants utilizing the C4 metabolic pathway is discussed, given that glacial episodes are known to have been times of lower atmospheric pCO2. Interpretations of seasonal variability and the relative abundance of C3 versus C4 vegetation based upon isotopes from tooth enamel are in broad agreement with predictions using the MCM and the modern distribution of PFGs with climate variables. The influence of pCO2 on the distribution of C4 vegetation during glacial times appears to be negligible. [Copyright &y& Elsevier]

This paper combines a wide‐area assessment of forecast changes in wintertime synoptic conditions over western North America with a meso‐scale alpine hydrometeorology model to evaluate the impacts of forecast climate change on snowpack conditions in an alpine watershed. The synoptic analysis was used to generate long‐term climate time series scenarios using the Canadian Centre for Climate Modelling and Analysis first‐generation coupled general circulation model (GCM). The alpine hydrometeorology model SIMGRID is used to predict changes in wintertime precipitation at the watershed scale. The SNOPAC model is a simple snow model that predicts the overall snow accumulation throughout a watershed based on the output from SIMGRID. A vapour transfer model has been incorporated into the SNOPAC model to estimate snow volumes more accurately. The model is applied to a small alpine watershed in the southern Canadian Rockies. The synoptic analysis and GCM output forecasts a modest increase in both winter precipitation and temperatures in the study area. The hypothesis herein is that the increase in winter precipitation due to synoptic conditions will not compensate for regional changes in the rain‐to‐snow ratios. The net result will be a decline in winter accumulations of precipitation as snow, and hence an expected decline in spring runoff. Copyright © 2005 Royal Meteorological Society. [ABSTRACT FROM AUTHOR]

Climate simulations often need to be adjusted (i.e., corrected) before any climate change impacts studies. However usual bias correction approaches do not differentiate the bias from the different uncertainties of the climate simulations: scenario uncertainty, model uncertainty and internal variability. In particular, in the case of a multi-run ensemble of simulations (i.e., multiple runs of one model), correcting, as usual, each member separately, would mix up the model biases with its internal variability. In this study, two ensemble bias correction approaches preserving the internal variability of the initial ensemble are proposed. These "Ensemble bias correction" (EnsBC) approaches are assessed and compared to the approach where each ensemble member is corrected separately, using precipitation and temperature series at two locations in North America from a multi-member regional climate ensemble. The preservation of the internal variability is assessed in terms of monthly mean and hourly quantiles. Besides, the preservation of the internal variability in a changing climate is evaluated. Results show that, contrary to the usual approach, the proposed ensemble bias correction approaches adequately preserve the internal variability even in changing climate. Moreover, the climate change signal given by the original ensemble is also conserved by both approaches. [ABSTRACT FROM AUTHOR]

• Future change in extreme droughts over 5797 North American watersheds was studied. • Two climate model large ensembles were used to assess the change of frequency. • Changes in meteorological droughts are mostly correlated to mean precipitation. • Large increases in the frequency of hydrological droughts are observed over NA. • Projected changes in future extreme droughts get worse for longer return periods. This paper describes projected frequency changes in extreme summer meteorological and hydrological droughts over North American catchments. It uses two large ensemble climate models (50-member CanESM2 and 40-member CESM1) under the RCP 8.5 scenario to robustly assess frequency changes up to the 100-year drought, relative to the 1980–2009 reference period. Meteorological droughts, linked solely to precipitation deficit, are represented by the 1-month Standardized Precipitation Index (SPI), whereas hydrological droughts are characterized by the 1-month Streamflow Drought Index (SDI), based on hydrological simulation using a lumped hydrological model. Results show widely different patterns for future changes in extreme meteorological versus hydrological droughts. Future meteorological droughts show patterns of increasing and decreasing frequency that roughly match future expected changes of mean summer precipitation, although some regions are nonetheless projected to see more frequent extreme meteorological droughts despite increases in mean summer precipitation. The frequency changes for the 100-year meteorological droughts can be quite severe, with up to a 20-fold increase observed over some watersheds. On the other hand, hydrological droughts, which combine the effect of precipitation and temperature changes, show a mostly uniform pattern of large to very large increases in drought frequency. This shows that the projected temperature increase is a main driver of future extreme hydrological droughts, enough to overcome the projected increase in mean summer precipitation for many North American catchments. Projected changes in both meteorological and hydrological droughts get consistently worse for the longer considered return periods. In other words, frequency changes for the 100-year droughts are more significant than those expected for the 2- and 20-year droughts. This gradual worsening toward larger extremes has potentially large societal and economic impacts. The large projected increases in the frequency of extreme hydrological drought frequency (up to 27 times) are likely to severely stress water management systems across North America. [ABSTRACT FROM AUTHOR]

The Hydrometeorological Sandbox - École de technologie supérieure (HYSETS) is a rich, comprehensive and large-scale database for hydrological modelling covering 14425 watersheds in North America. The database includes data covering the period 1950–2018 depending on the type and source of data. The data include a wide array of hydrometeorological data required to perform hydrological and climate change impact studies: (1) watershed properties including boundaries, area, elevation slope, land use and other physiographic information; (2) hydrometric gauging station discharge time-series; (3) precipitation, maximum and minimum daily air temperature time-series from weather station records and from (4) the SCDNA infilled gauge meteorological dataset; (5) the NRCan and Livneh gridded interpolated products' meteorological data; (6) ERA5 and ERA5-Land reanalysis data; and (7) the SNODAS and ERA5-Land snow water equivalent estimates. All data have been processed and averaged at the watershed scale, and provides a solid basis for hydrological modelling, climate change impact studies, model calibration assessment, regionalization method evaluation and essentially any study requiring access to large amounts of spatiotemporally varied hydrometeorological data. Measurement(s) elevation • temperature • hydrological precipitation process • Fluid Discharge • climate • physiographic feature Technology Type(s) digital curation Sample Characteristic - Environment watershed Sample Characteristic - Location North America Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12600281 [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]

In the context of climate change and projected increase in global temperature, the atmosphere's water holding capacity is expected to increase at the Clausius-Clapeyron (C-C) rate by about 7% per 1 °C warming. Such an increase may lead to more intense extreme precipitation events and thus directly affect the probable maximum precipitation (PMP), a parameter that is often used for dam safety and civil engineering purposes. We therefore use a statistically motivated approach that quantifies uncertainty and accounts for nonstationarity, which allows us to determine the rate of change of PMP per 1 °C warming. This approach, which is based on a bivariate extreme value model of precipitable water (PW) and precipitation efficiency (PE), provides interpretation of how PW and PE may evolve in a warming climate. Nonstationarity is accounted for in this approach by including temperature as a covariate in the bivariate extreme value model. The approach is demonstrated by evaluating and comparing projected changes to 6-hourly PMP from two Canadian regional climate models (RCMs), CanRCM4 and CRCM5, over North America. The main results suggest that, on the continental scale, PMP increases in these models at a rate of approximately 4% per 1 °C warming, which is somewhat lower than the C-C rate. At the continental scale, PW extremes increase on average at the rate of 5% per 1 °C near surface warming for both RCMs. Most of the PMP increase is caused by the increase in PW extremes with only a minor contribution from changes in PE extremes. Nevertheless, substantial deviations from the average rate of change in PMP rates occur in some areas, and these are mostly caused by sensitivity of PE extremes to near surface warming in these regions. [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]

We have constructed a fire weather climatology over North America from 1979 to 2015 using the North American Regional Reanalysis dataset and the Canadian Fire Weather Index (FWI) System. We tested for the presence of trends in potential fire season length, based on a meteorological definition, and extreme fire weather using the non-parametric Theil-Sen slope estimator and Mann-Kendall test. Applying field significance testing (i.e. joint significance of multiple tests) allowed the identification of the locations of significant trends, taking into account spatial correlations. Fire season length was found to be increasing over large areas of North America, especially in eastern Canada and the south-western US, which is consistent with a later fire season end and an earlier fire season start. Both positive and negative trends in potential fire spread days and the 99th percentile of FWI occurred in Canada and the contiguous United States, although the trends of largest magnitude and statistical significance were mostly positive. In contrast, the proportion of trends with significant decreases in these variables were much lower, indicating an overall increase in extreme fire weather. The smaller proportion of significant positive trends found over Canada reflects the truncation of the time series, necessary because assimilation of precipitation observations over Canada ceased in the reanalysis post-2002. [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]

Using an extensive network of occurrence records for 293 plant species collected over the past 40 years across a climatically diverse geographic section of western North America, we find that plant species distributions were just as likely to shift upwards (i.e., towards higher elevations) as downward (i.e., towards lower elevations)–despite consistent warming across the study area. Although there was no clear directional response to climate warming across the entire study area, there was significant region- to region- variation in responses (i.e. from as many as 73% to as few as 32% of species shifting upward). To understand the factors that might be controlling region-specific distributional shifts of plant species, we explored the relationship between the direction of change in distribution limits and the nature of recent climate change. We found that the direction that distribution limits shifted was explained by an interaction between the rate of change in local summer temperatures and seasonal precipitation. Specifically, species were more likely to shift upward at their upper elevational limit when minimum temperatures increased and snowfall was unchanging or declined at slower rates (<0.5 mm/year). This suggests that both low temperature and water availability limit upward shifts at upper elevation limits. By contrast, species were more likely to shift upwards at their lower elevation limit when maximum temperatures increased, but also shifted upwards under conditions of cooling temperatures when precipitation decreased. This suggests increased water stress may drive upward shifts at lower elevation limits. Our results suggest that species’ elevational distribution shifts are not predictable by climate warming alone but depend on the interaction between seasonal temperature and precipitation change. [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]

Climate change/variability accompanied by anthropogenic activities can alter the runoff response of landscapes. In this study we investigate the integrated impacts of precipitation change/variability and landscape changes, specifically wetland drainage practices, on streamflow regimes in wetland-dominated landscapes in the Assiniboine and Saskatchewan River basins of the North American Prairies. Precipitation and streamflow metrics were examined for gradual (trend type) and abrupt (shift type) changes using the modified Mann-Kendall trend test and a Bayesian change point detection methodology. Results of statistical analyses indicate that precipitation metrics did not experience statistically significant increasing or decreasing changes and there was no statistical evidence of streamflow regime change over the study area except for one of the smaller watersheds. The absence of widespread streamflow and precipitation changes suggests that wetland drainage did not lead to detectable changes in streamflow metrics over most of the Canadian portion of the Prairies between 1967 and 2007.Editor Z.W. Kundzewicz Associate editor None assigned [ABSTRACT FROM AUTHOR]

The Prairie Pothole Region (PPR) is the most important waterfowl production area in North America. However, waterfowl populations there are predicted to decline because of climate-related drying of wetlands. Consequently, changes in the geographic focus of PPR waterfowl conservation have been recommended, which could have long-lasting and costly impacts. We used a 40-year dataset of pond counts collected in the PPR to test hypotheses about climate-related drying. We assessed May (1974–2013) and July (1974–2003) pond numbers in 20 waterfowl survey strata to determine if trends in pond numbers were consistent with predictions of drying. We also assessed trends in precipitation and temperature for the 20 strata and developed models describing May pond numbers from 1974 through 2010 as a function of precipitation, temperature, the previous year’s pond numbers, and location. None of the 20 strata showed significant declines in May pond numbers, although seven strata showed increases over time. July pond numbers declined significantly in one stratum, and increased in seven strata. An index to hydroperiod showed significant increasing trends in three strata, and no strata had decreasing trends. Precipitation increased significantly in two strata and decreased in two from 1974 to 2010; no strata showed significant changes in temperature. The best linear model described pond numbers within all strata as a function of precipitation, temperature, the previous year’s pond numbers, and the latitude and longitude of the stratum, and explained 62% of annual variation in pond numbers. We hypothesize that direct effects of climate change on prairie pothole wetlands and waterfowl may be overshadowed by indirect effects such as intensified land use and increased pressure to drain wetlands. We recommend that an adaptive, data-driven approach be used to resolve uncertainties regarding direct and indirect effects of climate change on prairie wetlands and waterfowl, and guide future conservation efforts. [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 prairie pothole region (PPR) in the north-central United States and south-central Canada constitutes the most important waterfowl breeding area in North America. Projected long-term changes in precipitation and temperature may alter the drivers of waterfowl abundance: wetland availability and emergent vegetation cover. Previous studies have focused on isolated wetland dynamics, but the implications of changing precipitation on managed, river-fed wetlands have not been addressed. Using a structured decision making (SDM) approach, we derived optimal water management actions for 20 years at four river-fed National Wildlife Refuges (NWRs) in North and South Dakota under contrasting increasing/decreasing (+/−0.4 %/year) inflow scenarios derived from empirical trends. Refuge pool depth is manipulated by control structures. Optimal management involves setting control structure heights that have the highest probability of providing a desired mix of waterfowl habitat, given refuge capacities and inflows. We found optimal seasonal control structure heights for each refuge were essentially the same under increasing and decreasing inflow trends of 0.4 %/year over the next 20 years. Results suggest managed pools in the NWRs receive large inflows relative to their capacities. Hence, water availability does not constrain management; pool bathymetry and management tactics can be greater constraints on attaining management objectives than climate-mediated inflow. We present time-dependent optimal seasonal control structure heights for each refuge, which are resilient to the non-stationary precipitation scenarios we examined. Managers can use this information to provide a desired mixture of wildlife habitats, and to re-assess management objectives in reserves where pool bathymetry prevents attaining the currently stated objectives. [ABSTRACT FROM AUTHOR]

Producing reliable estimates of changes in precipitation at local and regional scales remains an important challenge in climate science. Statistical downscaling methods are often utilized to bridge the gap between the coarse resolution of general circulation models (GCMs) and the higher resolutions at which information is required by end users. As the skill of GCM precipitation, particularly in simulating temporal variability, is not fully understood, statistical downscaling typically adopts a perfect prognosis (PP) approach in which high-resolution precipitation projections are based on real-world statistical relationships between large-scale atmospheric predictors and local-scale precipitation. Using a nudged simulation of the ECHAM5 GCM, in which the large-scale weather states are forced toward observations of large-scale circulation and temperature for the period 1958-2001, previous work has shown ECHAM5 skill in simulating temporal variability of precipitation to be high in many parts of the world. Here, the same nudged simulation is used in an alternative downscaling approach, based on model output statistics (MOS), in which statistical corrections are derived for simulated precipitation. Cross-validated MOS corrections based on maximum covariance analysis (MCA) and principal component regression (PCR), in addition to a simple local scaling, are shown to perform strongly throughout much of the extratropics. Correlation between downscaled and observed monthly-mean precipitation is as high as 0.8-0.9 in many parts of Europe, North America, and Australia. For these regions, MOS clearly outperforms PP methods that use temperature and circulation as predictors. The strong performance of MOS makes such an approach to downscaling attractive and potentially applicable to climate change simulations. [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 North America (NA), trends in summer surface air temperatures vary on decadal time scales, and some regions have temperature trends that exhibit a lack of warming in 1982-2009. From a surface energy balance perspective, the summer mean daily maximum temperature change can be affected by changes in solar heating that are associated with cloud cover change and changes in surface evaporative cooling caused by different precipitation and land surface wetness, but little is known about regional cloud cover and precipitation feedbacks to decadal temperature trends. Changes in cloudiness and precipitation and their connections with summer mean daily maximum temperature variations in NA were investigated using observation-based products of temperature and precipitation and satellite-derived cloud cover and radiation products. Results show that summer mean daily maximum temperature variance is largely explained by changes in cloud cover and precipitation. Cloud cover effect dominates at the high and middle latitudes of NA, and precipitation is a more dominant factor in the southern United States. The results indicate that cloud cover is either the major indicator of the summer mean daily maximum temperature changes (the effect) or the important local factor influencing the changes (the cause). Cloud cover is negatively correlated with mean daily maximum temperature variation in spring and autumn at the middle latitudes of NA but not at the high latitudes. [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]

In examining intense precipitation over the central United States, the authors consider only days with precipitation when the daily total is above 12.7 mm and focus only on these days and multiday events constructed from such consecutive precipitation days. Analyses show that over the central United States, a statistically significant redistribution in the spectra of intense precipitation days/events during the past decades has occurred. Moderately heavy precipitation events (within a 12.7-25.4 mm day−1 range) became less frequent compared to days and events with precipitation totals above 25.4 mm. During the past 31 yr (compared to the 1948-78 period), significant increases occurred in the frequency of 'very heavy' (the daily rain events above 76.2 mm) and extreme precipitation events (defined as daily and multiday rain events with totals above 154.9 mm or 6 in.), with up to 40%% increases in the frequency of days and multiday extreme rain events. Tropical cyclones associated with extreme precipitation do not significantly contribute to the changes reported in this study. With time, the internal precipitation structure (e.g., mean and maximum hourly precipitation rates within each preselected range of daily or multiday event totals) did not noticeably change. Several possible causes of observed changes in intense precipitation over the central United States are discussed and/or tested. [ABSTRACT FROM AUTHOR]

The predictability of North American climate is diagnosed by taking into account both forced climate change and natural decadal-scale climate variability over the next decade. In particular, the 'signal' in North American surface air temperature and precipitation over 2011-20 associated with the expected change in boundary conditions related to future anthropogenic greenhouse gas (GHG) forcing, as well as the 'noise' around that signal due to internally generated ocean-atmosphere variability, is estimated. The structural uncertainty in the estimate of decadal predictability is diagnosed by examining the sensitivity to plausible scenarios for the GHG-induced change in boundary forcing, the model dependency of the forced signals, and the dependency on methods for estimating internal decadal noise. The signal-to-noise analysis by the authors is thus different from other published decadal prediction studies, in that this study does not follow a trajectory from a particular initial state but rather considers the statistics of internal variability in comparison with the GHG signal. The 2011-20 decadal signal is characterized by surface warming over the entire North American continent, precipitation decreases over the contiguous United States, and precipitation increases over Canada relative to 1971-2000 climatological conditions. The signs of these forced responses are robust across different sea surface temperature (SST) scenarios and the different models employed, though the amplitude of the response differs. The North American decadal noise is considerably smaller than the signal associated with boundary forcing, implying a potential for high forecast skill for 2011-20 North American climate even for prediction methods that do not attempt to initialize climate models. However, the results do suggest that initialized decadal predictions, which seek to forecast externally forced signals and also constrain the internal variability, could potentially improve upon uninitialized methods in regions where the external signal is small relative to internal variability. [ABSTRACT FROM AUTHOR]

Global climate models are constantly being upgraded, but it is often not clear what these changes have on climate change impact projections. We used difference maps to directly compare downscaled projections of temperature and precipitation across North America for two versions (or generations) of three different Atmospheric-Ocean General Circulation Models (AOGCM)s. We found that AOGCM versions differed in their projections for the end of the current century by up to 4 °C for annual mean temperature and 60% for annual precipitation. To place these changes in an ecological context, we reanalyzed our work on shifts in tree climate envelopes (CEs) using the newer-generation AOGCM projections. Based on the updated AOGCMs, by the 2071-2100 period, tree CEs shifted up to 2.4 degrees further north or 2.6 degrees further south (depending on the AOGCM) and were about 10% larger in size. Despite considerable differences between versions of a given AOGCM, projections made by the newer version of each AOGCM were in general agreement, suggesting convergence across the three models studied here. Assessing the AOGCM outputs in this way provides insight into the magnitude and importance of change associated with AOGCM upgrades as they continue to evolve through time. [ABSTRACT FROM AUTHOR]

In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status May 2011), the ISMN contains data of 19 networks and more than 500 stations located in North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data. [ABSTRACT FROM AUTHOR]

Climate change impacts in Pacific Northwest Region of North America (PNW) are projected to include increasing temperatures and changes in the seasonality of precipitation (increasing precipitation in winter, decreasing precipitation in summer). Changes in precipitation are also spatially varying, with the northwestern parts of the region generally experiencing greater increases in cool season precipitation than the southeastern parts. These changes in climate are projected to cause loss of snowpack and associated streamflow timing shifts which will increase cool season (October--March) flows and decrease warm season (April--September) flows and water availability. Hydrologic extremes such as the 100 yr flood and extreme low flows are also expected to change, although these impacts are not spatially homogeneous and vary with mid-winter temperatures and other factors. These changes have important implications for natural ecosystems affected by water, and for human systems. The PNW is endowed with extensive water resources infrastructure and well-established and well-funded management agencies responsible for ensuring that water resources objectives (such as water supply, water quality, flood control, hydropower production, environmental services, etc.) are met. Likewise, access to observed hydrological, meteorological, and climatic data and forecasts is in general exceptionally good in the United States and Canada, and is often supported by federally funded programs that ensure that these resources are freely available to water resources practitioners, policy makers, and the general public. Access to these extensive resources support the argument that at a technical level the PNW has high capacity to deal with the potential impacts of natural climate variability on water resources. To the extent that climate change will manifest itself as moderate changes in variability or extremes, we argue that existing water resources infrastructure and institutional arrangements provide a reasonably solid foundation for coping with climate change impacts, and that the mandates of existing water resources policy and water resources management institutions are at least consistent with the fundamental objectives of climate change adaptation. A deeper inquiry into the underlying nature of PNW water resources systems, however, reveals significant and persistent obstacles to climate change adaptation, which will need to be overcome if effective use of the region's extensive water resources management capacity can be brought to bear on this problem. Primary obstacles include assumptions of stationarity as the fundamental basis of water resources system design, entrenched use of historical records as the sole basis for planning, problems related to the relatively short time scale of planning, lack of familiarity with climate science and models, downscaling procedures, and hydrologic models, limited access to climate change scenarios and hydrologic products for specific water systems, and rigid water allocation and water resources operating rules that effectively block adaptive response. Institutional barriers include systematic loss of technical capacity in many water resources agencies following the dam building era, jurisdictional fragmentation affecting response to drought, disconnections between water policy and practice, and entrenched bureaucratic resistance to change in many water management agencies. These factors, combined with a federal agenda to block climate change policy in the US during the Bush administration have (with some exceptions) contributed to widespread institutional "gridlock" in the PNW over the last decade or so despite a growing awareness of climate change as a significant threat to water management. In the last several years, however, significant progress has been made in surmounting some of these obstacles, and the region's water resources agencies at all levels of governance are making progress in addressing the fundamental challenges inherent in adapting to climate change. [ABSTRACT FROM AUTHOR]

The generalized extreme value (GEV) distribution is fitted to winter season daily maximum precipitation over North America, with indices representing El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), and the North Atlantic Oscillation (NAO) as predictors. It was found that ENSO and PDO have spatially consistent and statistically significant influences on extreme precipitation, while the influence of NAO is regional and is not field significant. The spatial pattern of extreme precipitation response to large-scale climate variability is similar to that of total precipitation but somewhat weaker in terms of statistical significance. An El Niño condition or high phase of PDO corresponds to a substantially increased likelihood of extreme precipitation over a vast region of southern North America but a decreased likelihood of extreme precipitation in the north, especially in the Great Plains and Canadian prairies and the Great Lakes/Ohio River valley. [ABSTRACT FROM AUTHOR]

The authors use singular spectrum analysis to investigate the relative magnitude of decadal to multidecadal (D2M) variability in annual and seasonal precipitation anomalies across North America. In most places, decadal (10–20 yr) or multidecadal (20–50 yr) variability makes up less than 10% of the total variance in either annual or seasonal precipitation, with interannual variability or secular trends having much greater importance. Decadal variability is most prominent (contributing 25%–30% of the total variance) in Minnesota and northern California during winter, and the central Rocky Mountains in autumn. Eastern Québec is the only major region where precipitation exhibits significant variance in the multidecadal band. Precipitation across much of Canada exhibits significant variance at extremely low frequencies (greater than 50 yr), but variability at these time scales cannot be separated from secular trends because of the limited length of instrumental climate records. Decadal signals in the discharge of the Sacramento River and, to a lesser degree, the Colorado River are coherent and in phase with similar signals in regional precipitation. Prominent D2M signals do not resemble the low-frequency components of major climate modes such as ENSO or the PDO, which suggests that this behavior is not a product of a simple linear translation of a single climate forcing. [ABSTRACT FROM AUTHOR]

We investigated changes in wildfire risk over the 1901−2002 (ad) period with an analysis of broad-scale patterns of July monthly drought code (MDC) variability on 28 forested ecoregions of the North American and Eurasian continents. The MDC is an estimate of the net effect of changes in evapotranspiration and precipitation on cumulative moisture depletion in soils, and is well correlated with annual fire statistics across the circumboreal (explaining 25–61% of the variance in regional area burned). We used linear trend and regime shift analyses to investigate (multi-) decadal changes in MDC and percentage area affected by drought, and kernel function for analysis of temporal changes in the occurrence rates of extreme drought years. Our analyses did not reveal widespread patterns of linear increases in dryness through time as a response to rising Northern Hemisphere land temperatures. Instead, we found heterogeneous patterns of drought severity changes that were inherent to the nonuniformly distributed impacts of climate change on dryness. Notably, significant trends toward increasing summer moisture in southeastern and southwestern boreal Canada were detected. The diminishing wildfire risk in these regions is coherent with widely reported decreases in area burned since about 1850, as reconstructed by dendrochronological dating of forest stands. Conversely, we found evidence for increasing percentage area affected by extreme droughts in Eurasia (+0.57% per decade; P<0.05) and occurrence rates of extreme drought years in Eurasian taiga (centered principally on the Okhotsk–Manchurian taiga, P=0.07). Although not statistically significant, temporal changes in occurrence rates are sufficiently important spatially to be paid further attention. The absence of a linear trend in MDC severity, in conjunction with the presence of an increase in the occurrence rate of extreme drought years, suggest that fire disturbance regimes in the Eurasian taiga could be shifting toward being increasingly pulse dependent. [ABSTRACT FROM AUTHOR]

Glaciers are direct recorders of climate history and have come to be regarded as emblematic of climate change. They respond to variations in both accumulation and ablation, which can have separate atmospheric controls, leading to some ambiguity in interpreting the causes of glacier changes. Both climate change and climate variability have characteristic spatial patterns and time scales. The focus of this study is the regional-scale response of glaciers to natural patterns of climate variability. Using the Pacific Northwest of North America as the setting, the authors employ a simple linear glacier model to study how the combination of patterns of melt-season temperature and patterns of annual accumulation produce patterns of glacier length variations. Regional-scale spatial correlations in glacier length variations reflect three factors: the spatial correlations in precipitation and melt-season temperature, the geometry of a glacier and how it determines the relative importance of temperature and precipitation, and the climatic setting of the glaciers (i.e., maritime or continental). With the self-consistent framework developed here, the authors are able to evaluate the relative importance of these three factors. The results also highlight that, in order to understand the natural variability of glaciers, it is critically important to know the small-scale patterns of climate in mountainous terrain. The method can be applied to any area containing mountain glaciers and provides a baseline expectation for natural glacier variation against which the effects of climate changes can be evaluated. [ABSTRACT FROM AUTHOR]

About 75% of 46 glaciers measured using repeat airborne altimetry in Alaska and northwestern Canada have been losing mass at an increasing rate from the mid-1990s to the middle of the first decade of the twenty-first century, relative to an earlier period beginning in the 1950s–70s. The remaining glaciers have been either gaining mass during the more recent period or continuing to lose mass, but at a decreasing rate. Temperature and precipitation data at 67 climate stations were examined to explain these changes. Nearly all significant changes in winter (October–April) and summer (May–September) air temperatures were positive (2.0° ± 0.8° and 1.0° ± 0.4°C) between 1950 and 2002, and all seasonally averaged values of freezing level heights (FLH) increased during the same time period. A small increase in precipitation was observed, but these changes were significant at only 17% of the stations. Regional glacier changes, modeled using mass balance sensitivities and climate station temperature and precipitation changes, agreed with observations to within the limits of reported errors. Seasonal variations in accumulation resulted in large uncertainties in the recent period mass variations. In nearly all regions, increasing summer temperatures accounted for most of the glacier mass losses. FLH variations show that the maritime glacier systems are more sensitive to variations in the mean position of the winter FLH than interior regions, suggesting that strong winter warming has affected these regions in addition to the summer changes. These measurements augment the increasingly strong evidence of late twentieth-century climate change in northwestern North America. [ABSTRACT FROM AUTHOR]

Global climate change models indicate that storm magnitudes will increase in many areas throughout southwest North America, which could result in up to a 25% increase in seasonal precipitation in the Big Bend region of the Chihuahuan Desert over the next 50 years. Seasonal precipitation is a key limiting factor regulating primary productivity, soil microbial activity, and ecosystem dynamics in arid and semiarid regions. As decomposers, soil microbial communities mediate critical ecosystem processes that ultimately affect the success of all trophic levels, and the activity of these microbial communities is primarily regulated by moisture availability. This research is focused on elucidating soil microbial responses to seasonal and yearly changes in soil moisture, temperature, and selected soil nutrient and edaphic properties in a Sotol Grassland in the Chihuahuan Desert at Big Bend National Park. Soil samples were collected over a 3-year period in March and September (2004–2006) at 0–15 cm soil depth from 12 3 × 3 m community plots. Bacterial and fungal carbon usage (quantified using Biolog 96-well micro-plates) was related to soil moisture patterns (ranging between 3.0 and 14%). In addition to soil moisture, the seasonal and yearly variability of soil bacterial activity was most closely associated with levels of soil organic matter, extractable NH4–N, and soil pH. Variability in fungal activity was related to soil temperatures ranging between 13 and 26 °C. These findings indicate that changes in soil moisture, coupled with soil temperatures and resource availability, drive the functioning of soil-microbial dynamics in these desert grasslands. Temporal patterns in microbial activity may reflect the differences in the ability of bacteria and fungi to respond to seasonal patterns of moisture and temperature. Bacteria were more able to respond to moisture pulses regardless of temperature, while fungi only responded to moisture pulses during cooler seasons with the exception of substantial increased magnitudes in precipitation occurring during warmer months. Changes in the timing and magnitude of precipitation will alter the proportional contribution of bacteria and fungi to decomposition and nitrogen mineralization in this desert grassland. [ABSTRACT FROM AUTHOR]

Records of 1 April snow water equivalent (SWE) are examined here using multiple linear regression against reference time series of temperature and precipitation. This method permits 1) an examination of the separate roles of temperature and precipitation in determining the trends in SWE; 2) an estimation of the sensitivity of SWE to warming trends, and its distribution across western North America and as a function of elevation; and 3) inferences about responses of SWE to future warming. These results emphasize the sensitivity to warming of the mountains of northern California and the Cascades of Oregon and Washington. In addition, the contribution of modes of Pacific climate variability is examined and found to be responsible for about 10%–60% of the trends in SWE, depending on the period of record and climate index. [ABSTRACT FROM AUTHOR]

Intra- to multi-decadal (IMD) variation in terrestrial precipitation during 1901-98 was evaluated here by sampling annual precipitation rankings over 6-30 year moving time windows and converting those rankings to Mann-Whitney U statistics. Those U statistics were then used to identify the most significant concentrations of wet and dry years relative to a null hypothesis that assumes stationary climate variability. This time series analysis approach served as the basis of a climate survey method used to identify IMD precipitation regimes over continental areas, and was also used to evaluate IMD variation in time series of annual precipitation spatially averaged over those areas. These methods showed a highly significant incidence of wet years over North America during 1972-98, with 8 of the 10 wettest years of 1901-98 occurring during that 27-year period. A comparably significant incidence of late century wetness was also found over a northern Europe grid region, with 7 of the 10 wettest years occurring during 1978-98. Although significant wet and dry regimes were also found over other land areas in the last decades of the 20th century, the late century North American and northern European wet periods stood out as the most statistically significant found here during 1901-98. It is suggested that these recent wet periods are actually terrestrial evidence of a single multi-decadal precipitation mode extending across the North Atlantic, and the most observable evidence of an even broader pattern of recent North Atlantic climate change. [ABSTRACT FROM AUTHOR]

In 1997, during the late stages of production of NCEP-NCAR Global Reanalysis (GR), exploration of a regional reanalysis project was suggested by the GR project's Advisory Committee, “particularly if the RDAS [Regional Data Assimilation System] is significantly better than the global reanalysis at capturing the regional hydrological cycle, the diurnal cycle and other important features of weather and climate variability.” Following a 6-yr development and production effort, NCEP's North American Regional Reanalysis (NARR) project was completed in 2004, and data are now available to the scientific community. Along with the use of the NCEP Eta model and its Data Assimilation System (at 32-km-45-layer resolution with 3-hourly output), the hallmarks of the NARR are the incorporation of hourly assimilation of precipitation, which leverages leverages a comprehensive precipitation analysis effort, the use of a recent version of the Noah land surface model, and the use of numerous other datasets that are additional or improved compared to the GR. Following the practice applied to NCEP's GR, the 25-yr NARR retrospective production period (1979-2003) is augmented by the construction and daily execution of a system for near-real-time continuation of the NARR, known as the Regional Climate Data Assimilation System (R-CDAS). Highlights of the NARR results are presented: precipitation over the continental United States (CONUS), which is seen to be very near the ingested analyzed precipitation; fits of tropospheric temperatures and winds to rawinsonde observations; and fits of 2-m temperatures and 10-m winds to surface station observations. The aforementioned fits are compared to those of the NCEP-Department of Energy (DOE) Global Reanalysis (GR2). Not only have the expectations cited above been fully met, but very substantial improvements in the accuracy of temperatures and winds compared to that of GR2 are achieved throughout the troposphere. Finally, the numerous datasets produced are outlined and information is provided on the data archiving and present data availability. [ABSTRACT FROM AUTHOR]

Changes in timing or amount of precipitation may be of great consequence for carbon cycling in the Mixedgrass Prairie of N. America, because CO2 fixation and efflux are tightly coupled to soil water properties. The objective of our project was to quantify how ecosystem respiration ( Re) responds to experimental changes in winter and summer precipitation in a Mixedgrass Prairie using in situ field manipulations of snow depth and summer rain. Our study was conducted at the USDA-ARS High Plains Grasslands Research Station, west of Cheyenne, Wyoming. We installed three replicated 50 m snow fences to increase winter snow on the leeward side of the snow fence and experimentally manipulated summer precipitation by either increasing (+50%) or decreasing (−50%) precipitation amounts. We also measured ambient conditions. Re rates in May were around 2 g C m−2 d−1 for all treatments and increased to their greatest values in June, up to 10 g C m−2 d−1, with the ambient treatment having the largest flux rates. There were no treatment effects during the early summer, but by midsummer, Re rates were least in the reduced rainfall plots and greatest in the snow plots. Soil moisture and gross photosynthesis had strong influence on the daily Re rates, but soil temperature had little correlation with daily Re rates. In summary, the Re rates in this Mixedgrass Prairie are strongly influenced by changes in precipitation, especially winter snow accumulation. Thus, carbon cycle estimates under future climate change scenarios need to include not only the affects of changes in summer rain, but also, the consequences of deep snow in winter and itsȁ9 affect on carbon cycling processes in winter and subsequent summers. [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]