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A better understanding of the interannual variability in temperature and precipitation datasets used as forcing fields for hydrologic models will lead to a more complete description of hydrologic model uncertainty, in turn helping scientists study the larger goal of how the Arctic terrestrial systemis responding to global change. Accordingly, this paper investigates temporal and spatial variability in monthly mean (1992--2000) temperature and precipitation datasets over the Western Arctic Linkage Experiment (WALE) study region. The six temperature datasets include 1) the fifth-generation Pennsylvania State University--National Center for Atmospheric Research MesoscaleModel (MM5); 2) the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40); 3) the Advanced Polar Pathfinderall-sky temperatures (APP); 4) National Centers for Environmental Prediction--National Center for Atmospheric Research (NCEP--NCAR) reanalyses (NCEP1); 5) the Climatic Research Unit/University of East Anglia CRUTEM2v (CRU); and 6) the Matsuura and Wilmott 0.5° × 0.5° Global Surface Air Temperature and Precipitation (MW). Comparisons of monthly precipitation are examined for MM5, ERA-40, NCEP1, CRU, and MW. Results of the temporal analyses indicate significant differences between at least two datasets (for either temperature or precipitation) in almost every month. The largest number of significant differences for temperature occurs in October, when there are five separate groupings; for precipitation, there are four significantly different groupings from March through June, and again in December. Spatial analyses of June temperatures indicate that the greatest dissimilarity is concentrated in the central portion of the study region, with the NCEP1 and APP datasets showing the greatest differences. In comparison, the spatial analysis of June precipitation datasets suggests that the largest dissimilarity is concentrated in the eastern portion of the study region. These results indicate that the choice of forcing datasets likely will have a significant effecton the output from hydrologic models, and several different datasets should beused for a robust hydrologic assessment. [ABSTRACT FROM AUTHOR]

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]

Projected climatic warming has direct implications for future disturbance regimes, particularly fire-dominated ecosystems at high latitudes, where climate warming is expected to be most dramatic. It is important to ascertain the potential range of climate change impacts on terrestrial ecosystems, which is relevant to making projections of the response of the Earth system and to decisions by policymakers and land managers. Computer simulation models that explicitly model climate–fire relationships represent an important research tool for understanding and projecting future relationships. Retrospective model analyses of ecological models are important for evaluating how to effectively couple ecological models of fire dynamics with climate system models. This paper uses a transient landscape-level model of vegetation dynamics, Alaskan Frame-based Ecosystem Code (ALFRESCO), to evaluate the influence of different driving datasets of climate on simulation results. Our analysis included the use of climate data based on first-order weather station observations from the Climate Research Unit (CRU), a statistical reanalysis from the NCEP–NCAR reanalysis project (NCEP), and the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5). Model simulations of annual area burned for Alaska and western Canada were compared to historical fire activity (1950–2000). ALFRESCO was only able to generate reasonable simulation results when driven by the CRU climate data. Simulations driven by the NCEP and MM5 climate data produced almost no annual area burned because of substantially colder and wetter growing seasons (May–September) in comparison with the CRU climate data. The results of this study identify the importance of conducting retrospective analyses prior to coupling ecological models of fire dynamics with climate system models. The authors’ suggestion is to develop coupling methodologies that involve the use of anomalies from future climate model simulations to alter the climate data of more trusted historical climate datasets. [ABSTRACT FROM AUTHOR]

Isoprene is emitted from vegetation to the atmosphere in significant quantities, and it plays an important role in the reactions that control tropospheric oxidant concentrations. As future climatic and land-cover changes occur, the spatial and temporal variations, as well as the magnitude of these biogenic isoprene emissions, are expected to change. This paper presents a study of the change in biogenic isoprene emissions that would result from both anthropogenic land-cover and climate-driven changes. Annual global isoprene emissions were estimated to be 522 Tg yr-1 under current climatological and land-cover conditions. When climate-driven land-cover changes are predicted, but climate does not change, total global emissions did not change significantly, although regional impacts were important. However, the use of future temperature and land-cover drivers to estimate isoprene emissions produced a global estimate of 889 Tg yr-1. Anthropogenic land-cover changes, such as urbanization and changes of natural vegetation to plantation forests, can also have substantial impacts on isoprene emissions (i.e., up to 717 Tg yr-1, a 37% increase, when land-cover changes but temperature remains at current-day values). The Model for Ozone and Related Tracers, version 2 (MOZART-2) was run with the different isoprene emission scenarios to simulate the potential changes in global atmospheric chemical composition. The simulated regional surface ozone concentrations changed as much as -9 to 55 ppbv under certain emission and climate scenarios. These results were used to evaluate changes in the ozone production chemistry under different emission scenarios. As expected, the impacts of changing isoprene emissions are regionally dependent, with large changes in China, the Amazon, and the United States. [ABSTRACT FROM AUTHOR]

Understory fires, which burn the floor of standing forests, are one of the most important types of forest impoverishment in the Amazon, especially during the severe droughts of El Niño–Southern Oscillation (ENSO) episodes. However, the authors are aware of no estimates of the areal extent of these fires for the Brazilian Amazon and, hence, of their contribution to Amazon carbon fluxes to the atmosphere. In this paper, the area of forest understory fires for the Brazilian Amazon region is calculated during an El Niño (1998) and a non–El Niño (1995) year based on forest fire scars mapped with satellite images for three locations in eastern and southern Amazonia, where deforestation is concentrated. The three study sites represented a gradient of both forest types and dry season severity. The burning scar maps were used to determine how the percentage of forest that burned varied with distance from agricultural clearings. These spatial functions were then applied to similar forest/climate combinations outside of the study sites to derive an initial estimate for the Brazilian Amazon. Ninety-one percent of the forest area that burned in the study sites was within the first kilometer of a clearing for the non-ENSO year and within the first four kilometers for the ENSO year. The area of forest burned by understory forest fire during the severe drought (ENSO) year (3.9 × 106 ha) was 13 times greater than the area burned during the average rainfall year (0.2 × 106 ha), and twice the area of annual deforestation. Dense forest was, proportionally, the forest type most affected by understory fires during the El Niño year, while understory fires were concentrated in transitional forests during the year of average rainfall. The estimate here of aboveground tree biomass killed by fire ranged from 0.049 to 0.329 Pg during the ENSO and from 0.003 to 0.021 Pg during the non-ENSO year. [ABSTRACT FROM AUTHOR]

Complex environmental gradients in the White and Inyo Mountains in eastern California produce striking variations in vegetation assemblages over short distances. Vegetation composition is dominated by elevational gradients of temperature and precipitation, but local modifications by geologic substrate, potential insolation, slope, and topographic position create finescale mosaics. Digital elevation models, geologic maps, and field data were used to map current species distributions over 6220 km2 (622 000 ha) of the White and Inyo Mountains. Species–environment relationships of 88 plant species were modeled at a scale of 54 m using canonical correspondence analysis (CCA). CCA models were calibrated from 434 field plots and evaluated with 216 plots using kappa statistics. Vegetation responses to temperature increases of 1°–6°C were modeled by shifting species tolerances along the elevational gradient according to a standard lapse rate [3°C (500 m)-1] while all other factors were kept constant. Ranges of midelevations species tended to fragment onto local peaks, whereas the ranges of many desert species merged across a major pass. In several cases, local geologic features were identified as obstacles to species’ upslope migration. As modeled temperatures increase, species contract to small populations around White Mountain Peak (4342 m) and its north-facing slopes. It is predicted that 10 of 18 modeled alpine and subalpine species will become locally extinct if temperatures increase by 6°C. These scenarios provide a detailed set of hypotheses on the structure of current species ranges and their ability to persist through rapid climate change. [ABSTRACT FROM AUTHOR]

Accurate estimates of the spatial and temporal variation in terrestrial water and energy fluxes and mean states are important for simulating regional hydrology and biogeochemistry in high-latitude regions. Furthermore, it is necessary to develop high-resolution hydroclimatological datasets at finer spatial resolutions than are currently available from global analyses. This study uses a regional climate model (RCM) to develop a hydroclimatological dataset for hydrologic and ecological application in the Western Arctic. The fifth-generation Penn State–NCAR Mesoscale Model (MM5) forced by global reanalysis products at the boundaries is used to perform 12 yr of simulation (1990 through 2001) over the Western Arctic. An analysis that compares the RCM simulations with independent observationally derived data sources is conducted to evaluate the temporal and spatial distribution of the mean states, variability, and trends during the period of simulation. The RCM simulation of sea level pressure agrees well with the reanalysis in terms of mean states, seasonality, and interannual variability. The RCM also simulates major spatial patterns of the observed climatology of surface air temperature (SAT), but RCM SAT is generally colder in the summertime and warmer in the wintertime in comparison with other datasets. Although there are biases in the mean state of SAT, the RCM simulations of the seasonal and interannual variability of SAT are similar to variability in observationally derived datasets. The RCM also simulates general spatial patterns of observed rainfall, but the modeled mean state of precipitation is characterized by large biases relative to observationally derived datasets. In particular, the RCM tends to overestimate coastal region precipitation but underestimates precipitation in the interior of the Western Arctic. The Arctic terrestrial surface climate trends for the period of 1992 to 2001 of the RCM are similar to those derived from observations, with sea level pressure decreasing 0.15 hPa decade-1, SAT increasing 0.10°C decade-1, and precipitation decreasing slightly in the RCM simulations. In summary, the RCM dataset produced in this study represents an improvement over data currently available from large-scale global reanalysis and provides a consistent meteorological forcing dataset for hydrologic and ecological applications. [ABSTRACT FROM AUTHOR]

The potential role of the impacts of land-cover changes (LCCs) in the Australian climate is investigated within the context of increasing CO2 concentrations and temperature. Specifically, it is explored if possible scenarios for LCC can moderate or amplify CO2-induced changes in climate over Australia. The January climate of Australia is simulated under three different land-cover-change scenarios using a high-resolution regional climate model. The land-cover-change scenarios include a steady-state land cover that is equivalent to current land cover, a low-reforestation scenario that recovers approximately 25% of the trees replaced by grasslands within the last 200 yr, and a high-reforestation scenario that recovers at least 75% of the deforested regions. The model was driven by boundary conditions taken from transitory climate simulations from a general circulation model that included two climate scenarios based on two projected scenarios of CO2 concentration increase. The results show that reforestation has the potential to reduce the projected increase in Australian temperatures in 2050 and 2100 by as much as 40% and 20%, respectively. This cooling effect, however, is highly localized and occurs only in regions of reforestation. The results therefore hint that the potential of reforestation to moderate the impact of global warming may be significantly limited by the spatial scale of reforestation. In terms of deforestation, results show that any future land clearing can exacerbate the projected warming in certain regions of Australia. Carbon-related variables are also analyzed and results show that changes in net CO2 flux may be influenced more by soil respiration than by photosynthesis. The results herein encourage studies on the inclusion of land-cover-change scenarios in future climate change projection simulations of the Australian climate. [ABSTRACT FROM AUTHOR]

Changes in Earth’s climate in response to atmospheric greenhouse gas buildup impact the health of terrestrial ecosystems and the hydrologic cycle. The environmental conditions influential to plant and animal life are often mapped as ecoregions, which are land areas having similar combinations of environmental characteristics. This idea is extended to establish regions of similarity with respect to climatic characteristics that evolve through time using a quantitative statistical clustering technique called Multivariate Spatio-Temporal Clustering (MSTC). MSTC was applied to the monthly time series output from a fully coupled general circulation model (GCM) called the Parallel Climate Model (PCM). Results from an ensemble of five 99-yr Business-As-Usual (BAU) transient simulations from 2000 to 2098 were analyzed. MSTC establishes an exhaustive set of recurring climate regimes that form a “skeleton” through the “observations” (model output) throughout the occupied portion of the climate phase space formed by the characteristics being considered. MSTC facilitates direct comparison of ensemble members and ensemble and temporal averages since the derived climate regimes provide a basis for comparison. Moreover, by mapping all land cells to discrete climate states, the dynamic behavior of any part of the system can be studied by its time-varying sequence of climate state occupancy. MSTC is a powerful tool for model developers and environmental decision makers who wish to understand long, complex time series predictions of models. Strong predicted interannual trends were revealed in this analysis, including an increase in global desertification; a decrease in the cold, dry high-latitude conditions typical of North American and Asian winters; and significant warming in Antarctica and western Greenland. [ABSTRACT FROM AUTHOR]

Large-scale environmental, social, and economic impacts of recent weather and climate extremes are raising questions about whether the frequency and intensity of these extremes have been increasing. Here, the authors evaluate trends in climate extremes during the past half century using the U.S. High Plains as a case study. A total of eight different extreme indices and the standardized precipitation index (SPI) were evaluated using daily maximum and minimum temperature and precipitation data from 207 stations and 0.258 gridded data. The 1958-2010 time period was selected to exclude the 1950s and 2011 droughts. Results show general consistency between the station data and gridded data. The annual extreme temperature range (ETR) decreased significantly (p , 0.05) in ;54% of the High Plains, with a spatial mean rate of 20.78C decade21. Decreases in ETR result primarily from increases in annual lowest temperature in ;63% of the stations at a mean rate of ~0.9°C decade21, whereas increases in annual highest temperature were much less. Approximately 43% of the stations showed increasing warm nights (Tmin90) with a spatial mean rate of 0.5% decade21. Precipitation intensity generally did not vary significantly in most grid cells and stations. Significant decreasing trends in consecutive dry days (CDD) were restricted to 21% of the stations in the northern High Plains with a spatial mean of 20.8 days decade21. Areas experiencing severe dry periods (1-month SPI , 21.5) decreased over time from 8% to 4%. The number of dry months (SPI , 0) in each year also decreased. In summary, the ETR is decreasing and low temperatures are increasing. Precipitation extremes are generally not changing in the High Plains; however, high natural climatic variability in this semiarid region makes it difficult to assess climate extremes. [ABSTRACT FROM AUTHOR]

Hydrologic models often are applied to adjust projections of hydroclimatic change that come from climate models. Such adjustment includes climate-bias correction, spatial refinement (''downscaling''), and consideration of the roles of hydrologic processes that were neglected in the climate model. Described herein is a quantitative analysis of the effects of hydrologic adjustment on the projections of runoff change associated with projected twenty-first-century climate change. In a case study including three climate models and 10 river basins in the contiguous United States, the authors find that relative (i.e., fractional or percentage) runoff change computed with hydrologic adjustment more often than not was less positive (or, equivalently, more negative) than what was projected by the climate models. The dominant contributor to this decrease in runoff was a ubiquitous change in runoff (median −−11%%) caused by the hydrologic model''s apparent amplification of the climate-model-implied growth in potential evapotranspiration. Analysis suggests that the hydrologic model, on the basis of the empirical, temperature-based modified Jensen--Haise formula, calculates a change in potential evapotranspiration that is typically 3 times the change implied by the climate models, which explicitly track surface energy budgets. In comparison with the amplification of potential evapotranspiration, central tendencies of other contributions from hydrologic adjustment (spatial refinement, climate-bias adjustment, and process refinement) were relatively small. The authors'' findings highlight the need for caution when projecting changes in potential evapotranspiration for use in hydrologic models or drought indices to evaluate climate-change impacts on water. [ABSTRACT FROM AUTHOR]

Recent research indicates that the warming of the climate system resulting from increased greenhouse gas (GHG) emissions over the next century will persist for many centuries after the cessation of these emissions, principally because of the persistence of elevated atmospheric carbon dioxide (CO2) concentrations and their attendant radiative forcing. However, it is unknown whether the responses of other components of the climate system—including those related to Greenland and Antarctic ice cover, the Atlantic thermohaline circulation, the West African monsoon, and ecosystem and human welfare—would be reversed even if atmospheric CO2 concentrations were to recover to 1990 levels. Here, using a simple set of experiments employing a current-generation numerical climate model, the authors examine the response of the physical climate system to decreasing CO2 concentrations following an initial increase. Results indicate that many characteristics of the climate system, including global temperatures, precipitation, soil moisture, and sea ice, recover as CO2 concentrations decrease. However, other components of the Earth system may still exhibit nonlinear hysteresis. In these experiments, for instance, increases in stratospheric water vapor, which initially result from increased CO2 concentrations, remain present even as CO2 concentrations recover. These results suggest that identification of additional threshold behaviors in response to human-induced global climate change should focus on subcomponents of the full Earth system, including cryosphere, biosphere, and chemistry. [ABSTRACT FROM AUTHOR]

Earth ecosystems are not static, and they respond to environmental changes, particularly climatic and anthropogenic. Precipitation varying in its extremeness, with shifts to greater or lesser intensity of individual storms and/or to change in the length and frequency of wet and dry periods, can adversely affect both urban and rural ecosystems. Here, the authors review long-term precipitation records of the central Mediterranean area and employ a Web geographical information system (GIS)-based analytical approach to compare current rainfall impact with historical data on different spatial and temporal scales. Autumn (September–November) was recognized as the most hazardous season that marks the evidence of a changing climate, with a shift toward more intense rainfalls in recent times. In the first decade of the third millennium, areas of peninsular and insular Italy have been especially affected by extreme rains. A focus was put on the island of Sicily, where extraordinary rain events occurred in September 2009, discussed in the context of upcoming trends and climate histories. An improved knowledge and understanding of the scale at which changes on extremes occur is essential for dealing with the forthcoming challenges regarding soil and water conservation practices. The characteristics of changes in natural rainfall, its role on terrestrial ecosystems, and its effect on surface water erosion dynamics are discussed. It is argued that understanding these issues are major priorities for future research to promote a better understanding of the Earth interaction with water resources and related hydrological issues. [ABSTRACT FROM AUTHOR]

While most projections of climate change and its regional impacts focus on overall changes in the state of the climate system, useful information can also be found in the evolution of the climate system from one state to another. Here the authors introduce one method for identifying regions in which significant and systematic long-term nonlinear evolutions may be present, even given quasi-linear anthropogenic forcing. Using climate change projections taken from simulations of NCAR’s Community Climate System Model, version 3 (CCSM3), the authors then employ the technique to isolate systematic nonlinear behavior of soil moisture variations over the United States. While the projections presented here only represent the results from one model system, it is argued that such nonlinear behavior is an important characteristic of future climate change that should be considered when discussing both short-term and long-term impacts of anthropogenic climate forcing. [ABSTRACT FROM AUTHOR]

Instrumental climate records suggest that summer precipitation and winter snowpack in Glacier National Park (Glacier NP), Montana, vary significantly over decadal to multidecadal time scales. Because instrumental records for the region are limited to the twentieth century, knowledge of the range of variability associated with these moisture anomalies and their impacts on ecosystems and physical processes are limited. The authors developed a reconstruction of summer (June–August) moisture variability spanning a.d. 1540–2000 from a multispecies network of tree-ring chronologies in Glacier NP. Decadal-scale drought and pluvial regimes were defined as any event lasting 10 yr or greater, and the significance of each potential regime was assessed using intervention analysis. Intervention analysis prevents single intervening years of average or opposing moisture conditions from ending what was otherwise a sustained moisture regime. The reconstruction shows numerous decadal-scale shifts between persistent drought and wet events prior to the instrumental period (before a.d. 1900). Notable wet events include a series of three long-duration, high-magnitude pluvial regimes spanning the end of the Little Ice Age (a.d. 1770–1840). Though the late-nineteenth century was marked by a series of >10 yr droughts, the single most severe dry event occurred in the early-twentieth century (a.d. 1917–41). These decadal-scale dry and wet events, in conjunction with periods of high and low snowpack, have served as a driver of ecosystem processes such as forest fires and glacial dynamics in the Glacier NP region. Using a suite of paleoproxy reconstructions and information from previous studies examining the relationship between climate variability and natural processes, the authors explore how such persistent moisture anomalies affect the delivery of vital goods and services provided by Glacier NP and surrounding areas. These analyses show that regional water resources and tourism are particularly vulnerable to persistent moisture anomalies in the Glacier NP area. Many of these same decadal-scale wet and dry events were also seen among a wider network of hydroclimatic reconstructions along a north–south transect of the Rocky Mountains. Such natural climate variability can, in turn, have enormous impacts on the sustainable provision of natural resources over wide areas. Overall, these results highlight the susceptibility of goods and services provided by protected areas like Glacier NP to natural climate variability, and show that this susceptibility will likely be compounded by the effects of future human-induced climate change. [ABSTRACT FROM AUTHOR]

Time series analyses of a 22-yr record of satellite observations across the northern circumpolar high latitudes were conducted, and trends in vegetation photosynthetic activity were assessed using a series of statistical tests. The results indicate that most of the northern circumpolar high latitudes (>85%) showed no significant trend in vegetation activity despite systematic climate warming during the period of analysis. Of the areas that did change, many showed the expected trends in “greening” of vegetation activity. There were, however, significant differences in the magnitude and even in the direction of trends when stratified by vegetation type and density. Tundra areas consistently and predominantly showed greening trends. Forested areas showed declines in activity (“browning”) in many areas, and these were systematically higher in areas with denser tree cover—whether deciduous or evergreen, needle- or broad-leafed. The seasonality of the trends was also distinct between vegetation types, with a divergence in trends between late spring and early summer (positive) versus late summer (negative) portions of the growing seasons in forested areas. In contrast, tundra and other predominantly herbaceous areas showed positive trends in all portions of the growing season. These results confirm recent findings across the high latitudes of North America and are supported by an increasing array of in situ measurements. They indicate that the boreal forest biome might be responding to climate change in previously unexpected ways, and point to a need for an expanded observational network, additional analysis of existing datasets (e.g., tree rings), and improvements in process models of ecosystem responses to climate change. [ABSTRACT FROM AUTHOR]

Changes in Arctic sea ice cover have the potential to impact midlatitude climate. A previous sensitivity study utilizing the National Center for Atmospheric Research¿s (NCAR) atmospheric general circulation model [AGCM; Community Climate Model, version 3 (CCM3)] to explore climate sensitivity to declining Arctic sea ice cover suggested that, as Arctic sea ice cover is reduced, precipitation patterns over western North America will shift toward dryer conditions in southwestern North America and wetter conditions in northwestern North America. Here, three complementary lines of research validate and explore the robustness of this possible climate change impact: 1) repetition of the previous sensitivity study (specified constant Arctic sea ice cover and atmospheric CO2) with an updated version of the NCAR AGCM [third Community Atmosphere Model (CAM3)], 2) investigation of the climate response to dynamically reduced Arctic sea ice cover (driven by a quadrupling of atmospheric CO2) in the coupled NCAR Community Climate System Model (CCSMv3), and 3) analysis of similar results from six other coupled climate system models. Results from the CAM3 sensitivity study are similar to those from the original study with declining Arctic sea ice cover driving up to 25% less mean annual precipitation (MAP) over southwestern North America and up to an 8% increase in MAP over northwestern North America. The seven coupled models also reproduce this same general pattern. At the time of CO2 quadrupling, Arctic sea ice cover is reduced (up to 90% in boreal winter) and MAP over southwestern North America decreases by up to 30% while MAP in northwestern North America increases by up to 40%. These results represent a significant shift in the precipitation pattern over western North America and support the findings of the original sensitivity study in suggesting that, as future reductions in Arctic sea ice cover take place, there will be a substantial impact on water resources in western North America. [ABSTRACT FROM AUTHOR]

Regional climate models (RCMs) have improved our understanding of the effects of global climate change on specific regions. The need for realistic forcing has led to the use of fully coupled global climate models (GCMs) to produce boundary conditions for RCMs. The advantages of using fully coupled GCM output is that the global-scale interactions of all components of the climate system (ocean, sea ice, land surface, and atmosphere) are considered. This study uses an RCM, driven by a fully coupled GCM, to examine the climate of a region centered over California for the time periods 1980–99 and 2080–99. Statistically significant increases in mean monthly temperatures by up to 7°C are found for the entire state. Large changes in precipitation occur in northern California in February (increase of up to 4 mm day-1 or 30%) and March (decrease of up to 3 mm day-1 or 25%). However, in most months, precipitation changes between the cases were not statistically significant. Statistically significant decreases in snow accumulation of over 100 mm (50%) occur in some months. Temperature increases lead to decreases in snow accumulation that impact the hydrologic budget by shifting spring and summer runoff into the winter months, reinforcing results of other studies that used different models and driving conditions. [ABSTRACT FROM AUTHOR]

Projections of human-induced climate change impacts arising from the emission of atmospheric chemical constituents such as carbon dioxide typically utilize multiple integrations (or ensembles) of numerous numerical climate change models to arrive at multimodel ensembles from which mean and median values and probabilities can be inferred about the response of various components of the observed climate system. Some responses are considered reliable in as much as the simulated responses show consistency within ensembles and across models. Other responses—particularly at regional levels and for certain parameters such as precipitation—show little intermodel consistency even in the sign of the projected climate changes. The authors’ results show that in these regions the consistency in the sign of projected precipitation variations is greater for intramodel runs (e.g., runs from the same model) than intermodel runs (e.g., runs from different models), indicating that knowledge of the internal “dynamics” of the climate system can provide additional skill in making projections of climate change. Given the consistency provided by the governing dynamics of the model, the authors test whether persistence from an individual model trajectory serves as a good predictor for its own behavior by the end of the twenty-first century. Results indicate that, in certain regions where intermodel consistency is low, the short-term trends of individual model trajectories do provide additional skill in making projections of long-term climate change. The climate forcing for which this forecast skill becomes relatively large (e.g., correct in 75% of the individual model runs) is equivalent to the anthropogenic climate forcing imposed over the past century, suggesting that observed changes in precipitation in these regions can provide guidance about the direction of future precipitation changes over the course of the next century. [ABSTRACT FROM AUTHOR]

Changes in the intra-annual cycle of atmospheric CO2 at Mauna Loa, Hawaii, are investigated by comparing monthly observations to the mean value of each year’s waxing and waning phase of the cycle. Results identify a previously unnoticed change between 1965 and 2004 during October in which October concentrations declined relative to the cycle’s mean value. Results confirm a previously noted change in spring (April), but unlike previous analyses, this result indicates that between 1965 and 2004 April concentrations rose relative to the cycle’s mean value. The timing of these changes is not caused by commonly recognized patterns of atmospheric circulation, such as ENSO events. Instead, these changes may be generated by asymmetric effects of warming. Warming in early spring may increase heterotrophic respiration relative to net primary production while warming in late summer/early fall may enhance net primary production relative to heterotrophic respiration. [ABSTRACT FROM AUTHOR]

Changes in vegetation are known to have an impact on climate via biogeophysical effects such as changes in albedo and heat fluxes. Here, the effects of maximum afforestation and deforestation are studied over Europe. This is done by comparing three regional climate model simulations—one with present-day vegetation, one with maximum afforestation, and one with maximum deforestation. In general, afforestation leads to more evapotranspiration (ET), which leads to decreased near-surface temperature, whereas deforestation leads to less ET, which leads to increased temperature. There are exceptions, mainly in regions with little water available for ET. In such regions, changes in albedo are relatively more important for temperature. The simulated biogeophysical effect on seasonal mean temperature varies between 0.5° and 3°C across Europe. The effect on minimum and maximum temperature is larger than that on mean temperature. Increased (decreased) mean temperature is associated with an even larger increase (decrease) in maximum summer (minimum winter) temperature. The effect on precipitation is found to be small. Two additional simulations in which vegetation is changed in only one-half of the domain were also performed. These simulations show that the climatic effects from changed vegetation in Europe are local. The results imply that vegetation changes have had, and will have, a significant impact on local climate in Europe; the climatic response is comparable to climate change under RCP2.6. Therefore, effects from vegetation change should be taken into account when simulating past, present, and future climate for this region. The results also imply that vegetation changes could be used to mitigate local climate change. [ABSTRACT FROM AUTHOR]

Land–atmosphere interactions play a critical role in the Earth system, and a better understanding of these interactions could improve weather and climate models. The interaction among drought, vegetation productivity, and land cover is of particular significance. In a semiarid environment, such as the U.S. Great Plains, droughts can have a large influence on the productivity of agriculture and grasslands, with serious environmental and economic impacts. Here, we used the vegetation drought response index (VegDRI) drought indicator to investigate the response of vegetation to weather and climate for land-cover types in the Great Plains in the United States from 1989 to 2012. We found that analysis that focused on land-cover types within ecoregion divisions provided substantially more and land-cover-based detail on the timing and intensity of drought than did summarizing across the entire Great Plains region. In the northern Great Plains, VegDRI measured more frequent drought impacts on vegetation in the western ecoregions than in the eastern ecoregions. Across the ecoregions of the Great Plains, drought impacts on vegetation were more commonly found in grassland than in cropland. For example, in the "Northwestern Great Plains" ecoregion (which encompasses areas of Montana, Wyoming, North Dakota, South Dakota, and Nebraska), grassland and nonirrigated cropland were observed in VegDRI to have historical fractional drought coverages in the growing season of 17% and 11%, respectively. [ABSTRACT FROM AUTHOR]

Climatic extremes have direct and indirect effects on an ecosystem, whereby thermal variations bring warm and cold weather, and hydrological anomalies cause droughts and floods. Changing patterns of 13 temperature and 11 precipitation extreme indices for a 36-yr period (1980- 2015) for four cities of the Balochistan province of Pakistan (Pasni, Jiwani, Khuzdar, and Dalbadin) were computed using RClimdex. A nonparametric Mann-Kendall test and Sen's slope estimates were used to determine the statistical significance and magnitude of a trend, respectively. Most of the indices calculated for temperature extremes show statistically significant changes in their historic pattern, depicting a clear picture of warming in the regions. The indices calculated for precipitation extremes show statistically significant as well as nonsignificant results, depicting asymmetrical droughts in the region. If the patterns of humid weather with hot and wet extremes in the coastal cities of Balochistan continue for a couple of future decades, there will be challenges in implementing the multibillion-dollar Balochistan coastal development projects of the Pakistani port of Gwadar-a doorway to the Middle East for Chineseplanned business endeavors through Pakistan. [ABSTRACT FROM AUTHOR]