Recent contrasting winter temperature changes over North America linked to enhanced positive Pacific‐North American pattern

Recently enhanced contrasts in winter (December‐January‐February) mean temperatures and extremes (cold southeast and warm northwest) across North America have triggered intensive discussion both within and outside of the scientific community, but the mechanisms responsible for these contrasts remain unresolved. Here we use a combination of observations and reanalysis data sets to show that the strengthened contrasts in winter mean temperatures and extremes across North America are closely related to an enhancement of the positive Pacific‐North American (PNA) pattern during the second half of the 20th century. Recent intensification of positive PNA events is associated with amplified planetary waves over North America, driving cold‐air outbreaks into the southeast and warm tropical/subtropical air into the northwest. This not only results in a strengthened winter mean temperature contrast but increases the occurrence of the opposite‐signed extremes in these two regions.Key PointsThe enhanced contrasts in winter mean temperatures and extremes in North America are observedRecent enhancement of positive PNA is a main cause of the contrasting winter temperature changesThe study provides a framework for detection and attribution of climate change in North AmericaPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/115952/1/grl53404_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/115952/2/grl53404.pd

The soil and plant biogeochemistry sampling design for The National Ecological Observatory Network

Human impacts on biogeochemical cycles are evident around the world, from changes to forest structure and function due to atmospheric deposition, to eutrophication of surface waters from agricultural effluent, and increasing concentrations of carbon dioxide (CO2) in the atmosphere. The National Ecological Observatory Network (NEON) will contribute to understanding human effects on biogeochemical cycles from local to continental scales. The broad NEON biogeochemistry measurement design focuses on measuring atmospheric deposition of reactive mineral compounds and CO2 fluxes, ecosystem carbon (C) and nutrient stocks, and surface water chemistry across 20 eco‐climatic domains within the United States for 30 yr. Herein, we present the rationale and plan for the ground‐based measurements of C and nutrients in soils and plants based on overarching or “high‐level” requirements agreed upon by the National Science Foundation and NEON. The resulting design incorporates early recommendations by expert review teams, as well as recent input from the larger natural sciences community that went into the formation and interpretation of the requirements, respectively. NEON\u27s efforts will focus on a suite of data streams that will enable end‐users to study and predict changes to biogeochemical cycling and transfers within and across air, land, and water systems at regional to continental scales. At each NEON site, there will be an initial, one‐time effort to survey soil properties to 1 m (including soil texture, bulk density, pH, baseline chemistry) and vegetation community structure and diversity. A sampling program will follow, focused on capturing long‐term trends in soil C, nitrogen (N), and sulfur stocks, isotopic composition (of C and N), soil N transformation rates, phosphorus pools, and plant tissue chemistry and isotopic composition (of C and N). To this end, NEON will conduct extensive measurements of soils and plants within stratified random plots distributed across each site. The resulting data will be a new resource for members of the scientific community interested in addressing questions about long‐term changes in continental‐scale biogeochemical cycles, and is predicted to inspire further process‐based research

Comparing Model Representations of Physiological Limits on Transpiration at a Semi-arid Ponderosa Pine Site

Mechanistic representations of biogeochemical processes in ecosystem models are rapidly advancing, requiring advancements in model evaluation approaches. Here we quantify multiple aspects of model functional performance to evaluate improved process representations in ecosystem models. We compare semi-empirical stomatal models with hydraulic constraints against more mechanistic representations of stomatal and hydraulic functioning at a semi-arid pine site using a suite of metrics and analytical tools. We find that models generally perform similarly under unstressed conditions, but performance diverges under atmospheric and soil drought. The more empirical models better capture synergistic information flows between soil water potential and vapor pressure deficit to transpiration, while the more mechanistic models are overly deterministic. Although models can be parameterized to yield similar functional performance, alternate parameterizations could not overcome structural model constraints that underestimate the unique information contained in soil water potential about transpiration. Additionally, both multilayer canopy and big-leaf models were unable to capture the magnitude of canopy temperature divergence from air temperature, and we demonstrate that errors in leaf temperature can propagate to considerable error in simulated transpiration. This study demonstrates the value of merging underutilized observational data streams with emerging analytical tools to characterize ecosystem function and discriminate among model process representations

Patterns of local and nonlocal water resource use across the western U.S. determined via stable isotope intercomparisons

In the western U.S., the mismatch between public water demands and natural water availability necessitates large interbasin transfers of water as well as groundwater mining of fossil aquifers. Here we identify probable situations of nonlocal water use in both space and time based on isotopic comparisons between tap waters and potential water resources within hydrologic basins. Our approach, which considers evaporative enrichment of heavy isotopes during storage and distribution, is used to determine the likelihood of local origin for 612 tap water samples collected from across the western U.S. We find that 64% of samples are isotopically distinct from precipitation falling within the local hydrologic basin, a proxy for groundwater with modern recharge, and 31% of samples are isotopically distinct from estimated surface water found within the local basin. Those samples inconsistent with local water sources, which we suggest are likely derived from water imported from other basins or extracted from fossil aquifers, are primarily clustered in southern California, the San Francisco Bay area, and central Arizona. Our isotope-based estimates of nonlocal water use are correlated with both hydrogeomorphic and socioeconomic properties of basins, suggesting that these factors exert a predictable influence on the likelihood that nonlocal waters are used to supply tap water. We use these basin properties to develop a regional model of nonlocal water resource use that predicts (r2 = 0.64) isotopically inferred patterns and allows assessment of total interbasin transfer and/or fossil aquifer extraction volumes across the western U.S.Fil: Good, Stephen P.. University of Utah; Estados UnidosFil: Kennedy, Casey D.. United States Department Of Agriculture. Agriculture Research Service; Estados UnidosFil: Stalker Jeremy C.. Jacksonville University; Estados UnidosFil: Chesson, Lesley A.. IsoForensics; Estados UnidosFil: Valenzuela, Luciano Oscar. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Sociales. Departamento de Arqueología. Laboratorio de Ecología Evolutiva Humana (Sede Quequén); Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Utah; Estados UnidosFil: Beasley, Melanie M.. University of California at San Diego; Estados UnidosFil: Ehleringer, James R. University of Utah; Estados UnidosFil: Bowen, Gabriel J.. University of Utah; Estados Unido

Joint inversion of proxy system models to reconstruct paleoenvironmental time series from heterogeneous data

Paleoclimatic and paleoenvironmental reconstructions are fundamentally uncertain because no proxy is a direct record of a single environmental variable of interest; all proxies are indirect and sensitive to multiple forcing factors. One productive approach to reducing proxy uncertainty is the integration of information from multiple proxy systems with complementary, overlapping sensitivity. Mostly, such analyses are conducted in an ad hoc fashion, either through qualitative comparison to assess the similarity of single-proxy reconstructions or through step-wise quantitative interpretations where one proxy is used to constrain a variable relevant to the interpretation of a second proxy. Here we propose the integration of multiple proxies via the joint inversion of proxy system and paleoenvironmental time series models in a Bayesian hierarchical framework. The “Joint Proxy Inversion” (JPI) method provides a statistically robust approach to producing self-consistent interpretations of multi-proxy datasets, allowing full and simultaneous assessment of all proxy and model uncertainties to obtain quantitative estimates of past environmental conditions. Other benefits of the method include the ability to use independent information on climate and environmental systems to inform the interpretation of proxy data, to fully leverage information from unevenly and differently sampled proxy records, and to obtain refined estimates of proxy model parameters that are conditioned on paleo-archive data. Application of JPI to the marine Mg∕Ca and δ18O proxy systems at two distinct timescales demonstrates many of the key properties, benefits, and sensitivities of the method, and it produces new, statistically grounded reconstructions of Neogene ocean temperature and chemistry from previously published data. We suggest that JPI is a universally applicable method that can be implemented using proxy models of wide-ranging complexity to generate more robust, quantitative understanding of past climatic and environmental change

Stream Centric Methods for Determining Groundwater Contributions in Karst Mountain Watersheds

Climate change influences on mountain hydrology are uncertain but likely to be mediated by variability in subsurface hydrologic residence times and flow paths. The heterogeneity of karst aquifers adds complexity in assessing the resiliency of these water sources to perturbation, suggesting a clear need to quantify contributions from and losses to these aquifers. Here we develop a stream centric method that combines mass and flow balances to quantify net and gross gains and losses at different spatial scales. We then extend these methods to differentiate between karst conduit and matrix contributions from the aquifer. In the Logan River watershed in Northern Utah we found significant amounts of the river water repeatedly gained and then lost through a 35‐km study reach. Further, the direction and amount of water exchanged varied over space, time, and discharge. Streamflow was dominated by discharge of karst conduit groundwater after spring runoff with increasing, yet still small, fractions of matrix water later in the summer. These findings were combined with geologic information, prior subsurface dye tracing, and chemical sampling to provide additional lines of evidence that repeated groundwater exchanges are likely occurring and river flows are highly dependent on karst aquifer recharge and discharge. Given the large population dependent on karst aquifers throughout the world, there is a continued need to develop simple methods, like those presented here, for determining the resiliency of karst groundwater resources

Enabling online geospatial isotopic model development and analysis

In recent years, there has been a rapid growth in the amount of environmental data collected over large spatial and temporal scales. It presents unprecedented opportunities for new scientific discovery, while in the same time poses significant challenges to the research community on how to effectively identify and integrate these datasets into their research models and tools. In this paper, we describe the design and implementation of IsoMAP- a gateway for Isoscapes (isotopic landscapes) modeling, analysis and prediction. IsoMAP provides an online workspace that helps researchers access and integrate a number of disparate and diverse datasets, develop Isoscapes models over selected spatio-temporal domains using geo-statistical algorithms, and predict maps for the stable isotope ratios of water, plants, and soils. The IsoMAP system leverages the computation resources available on the TeraGrid to perform geospatial data operations and geostatistical model calculations. It builds on a variety of open source technologies for GIS, geospatial data management and processing, grid computing, and gateway development. The system was successfully used to teach a tutorial in the 2011 conference on the Roles of Stable Isotopes in Water Cycle Research. A post-tutorial survey was conducted. We review the users ’ feedback and present a future development plan based on that

A Statistical Method for Generating Temporally Downscaled Geochemical Tracers in Precipitation

Sampling intervals of precipitation geochemistry measurements are often coarser than those required by fine-scale hydrometeorological models. This study presents a statistical method to temporally downscale geochemical tracer signals in precipitation so that they can be used in high-resolution, tracer-enabled applications. In this method, we separated the deterministic component of the time series and the remaining daily stochastic component, which was approximated by a conditional multivariate Gaussian distribution. Specifically, statistics of the stochastic component could be explained from coarser data using a newly identified power-law decay function, which relates data aggregation intervals to changes in tracer concentration variance and correlations with precipitation amounts. These statistics were used within a copula framework to generate synthetic tracer values from the deterministic and stochastic time series components based on daily precipitation amounts. The method was evaluated at 27 sites located worldwide using daily precipitation isotope ratios, which were aggregated in time to provide low resolution testing datasets with known daily values. At each site, the downscaling method was applied on weekly, biweekly and monthly aggregated series to yield an ensemble of daily tracer realizations. Daily tracer concentrations downscaled from a biweekly series had average (+/- standard deviation) absolute errors of 1.69‰ (1.61‰) for δ2H and 0.23‰ (0.24‰) for δ18O relative to observations. The results suggest coarsely sampled precipitation tracers can be accurately downscaled to daily values. This method may be extended to other geochemical tracers in order to generate downscaled datasets needed to drive complex, fine-scale models of hydrometeorological processes

Controls on Stable Water Isotopes in Monsoonal Precipitation Across the Bay of Bengal: Atmosphere and Surface Analysis

Stable hydrogen isotopes in monsoonal precipitation (δDp) at three sites (Port Blair, Barisal and Darjeeling) reveal the factors governing δDp variations over a south-north gradient across the Bay of Bengal. We found that the δDp at each site continuously decreases from May to September and these trends become more pronounced from south to north. The decreasing trends of downstream δDp closely follow the decreasing trends of upstream stable hydrogen isotopes in water vapor (δDv), which indicates that upstream δDv properties shape initial spatiotemporal patterns of the downstream δDp (“shaping effect”). Additionally, our results demonstrate that, during moisture transport, upstream vertical air motions (convection and downward motion) and topographic relief magnify the amplitude of the decreasing trends of downstream δD (“magnifying effect”). Our findings imply that upstream δD properties and relevant atmospheric and pv topographical conditions along the moisture transport pathway need to be considered collectively to better interpret paleoclimate records