Extra-tropical atmospheric response to ENSO in the CMIP5 models

The seasonal mean extra-tropical atmospheric response to El Niño/Southern Oscillation (ENSO) is assessed in the historical and pre-industrial control CMIP5 simulations. This analysis considers two types of El Niño events, characterized by positive sea surface temperature (SST) anomalies in either the central equatorial Pacific (CP) or eastern equatorial Pacific (EP), as well as EP and CP La Niña events, characterized by negative SST anomalies in the same two regions. Seasonal mean geopotential height anomalies in key regions typify the magnitude and structure of the disruption of the Walker circulation cell in the tropical Pacific, upper tropospheric ENSO teleconnections and the polar stratospheric response. In the CMIP5 ensembles, the magnitude of the Walker cell disruption is correlated with the strength of the mid-latitude responses in the upper troposphere i.e., the North Pacific and South Pacific lows strengthen during El Niño events. The simulated responses to El Niño and La Niña have opposite sign. The seasonal mean extra-tropical, upper tropospheric responses to EP and CP events are indistinguishable. The ENSO responses in the MERRA reanalysis lie within the model scatter of the historical simulations. Similar responses are simulated in the pre-industrial and historical CMIP5 simulations. Overall, there is a weak correlation between the strength of the tropical response to ENSO and the strength of the polar stratospheric response. ENSO-related polar stratospheric variability is best simulated in the “high-top” subset of models with a well-resolved stratosphere.     

Past and future polar amplification of climate change: climate model intercomparisons and ice-core constraints

Climate model simulations available from the PMIP1, PMIP2 and CMIP (IPCC-AR4) intercomparison projects for past and future climate change simulations are examined in terms of polar temperature changes in comparison to global temperature changes and with respect to pre-industrial reference simulations. For the mid-Holocene (MH, 6,000 years ago), the models are forced by changes in the Earth’s orbital parameters. The MH PMIP1 atmosphere-only simulations conducted with sea surface temperatures fixed to modern conditions show no MH consistent response for the poles, whereas the new PMIP2 coupled atmosphere–ocean climate models systematically simulate a significant MH warming both for Greenland (but smaller than ice-core based estimates) and Antarctica (consistent with the range of ice-core based range). In both PMIP1 and PMIP2, the MH annual mean changes in global temperature are negligible, consistent with the MH orbital forcing. The simulated last glacial maximum (LGM, 21,000 years ago) to pre-industrial change in global mean temperature ranges between 3 and 7°C in PMIP1 and PMIP2 model runs, similar to the range of temperature change expected from a quadrupling of atmospheric CO₂ concentrations in the CMIP simulations. Both LGM and future climate simulations are associated with a polar amplification of climate change. The range of glacial polar amplification in Greenland is strongly dependent on the ice sheet elevation changes prescribed to the climate models. All PMIP2 simulations systematically underestimate the reconstructed glacial–interglacial Greenland temperature change, while some of the simulations do capture the reconstructed glacial–interglacial Antarctic temperature change. Uncertainties in the prescribed central ice cap elevation cannot account for the temperature change underestimation by climate models. The variety of climate model sensitivities enables the exploration of the relative changes in polar temperature with respect to changes in global temperatures. Simulated changes of polar temperatures are strongly related to changes in simulated global temperatures for both future and LGM climates, confirming that ice-core-based reconstructions provide quantitative insights on global climate changes. An erratum to this article can be found at     

Preparing for Climatic Change: The Water, Salmon, and Forests of the Pacific Northwest

The impacts of year-to-year and decade-to-decade climatic variations on some of the Pacific Northwest's key natural resources can be quantified to estimate sensitivity to regional climatic changes expected as part of anthropogenic global climatic change. Warmer, drier years, often associated with El Niño events and/or the warm phase of the Pacific Decadal Oscillation, tend to be associated with below-average snowpack, streamflow, and flood risk, below-average salmon survival, below-average forest growth, and above-average risk of forest fire. During the 20th century, the region experienced a warming of 0.8 °C. Using output from eight climate models, we project a further warming of 0.5–2.5 °C (central estimate 1.5 °C) by the 2020s, 1.5–3.2°C (2.3 °C) by the 2040s, and an increase in precipitation except in summer. The foremost impact of a warming climate will be the reduction of regional snowpack, which presently supplies water for ecosystems and human uses during the dry summers. Our understanding of past climate also illustrates the responses of human management systems to climatic stresses, and suggests that a warming of the rate projected would pose significant challenges to the management of natural resources. Resource managers and planners currently have few plans for adapting to or mitigating the ecological and economic effects of climatic change.     

The Ensemble Kalman Filter for Groundwater Plume Characterization: A Case Study

The Kalman filter is an efficient data assimilation tool to refine an estimate of a state variable using measured data and the variable's correlations in space and/or time. The ensemble Kalman filter (EnKF) (Evensen 2004, 2009) is a Kalman filter variant that employs Monte Carlo analysis to define the correlations that help to refine the updated state. While use of EnKF in hydrology is somewhat limited, it has been successfully applied in other fields of engineering (e.g., oil reservoir modeling, weather forecasting). Here, EnKF is used to refine a simulated groundwater tetrachloroethylene (TCE) plume that underlies the Tooele Army Depot‐North (TEAD‐N) in Utah, based on observations of TCE in the aquifer. The resulting EnKF‐based assimilated plume is simulated forward in time to predict future plume migration. The correlations that underpin EnKF updating implicitly contain information about how the plume developed over time under the influence of complex site hydrology and variable source history, as they are predicated on multiple realizations of a well‐calibrated numerical groundwater flow and transport model. The EnKF methodology is compared to an ordinary kriging‐based assimilation method with respect to the accurate representation of plume concentrations in order to determine the relative efficacy of EnKF for water quality data assimilation.     

A comparison of geochemical information obtained from two fluvial bed sediment fractions

 A total of 121 bed sediment samples were collected from a 5.8-km stretch of Manoa Stream, Hawaii. Samples were physically partitioned into two grain-size fractions, <63 μm and 63–125 μm, acid digested and analyzed by ICP-AES and FAAS. Non-parametric matched-pair statistical testing and correlation analysis were used to assess differences and strengths of association between the two fractions for Al, Ba, Cu, Fe, Mn, Ni, Pb, Ti and Zn. Results indicated statistically significant differences between fractions for all elements except Mn. Concentrations were significantly greater in the <63 μm fraction for Al, Cu, Pb, Ti and Zn, while Ba, Fe and Ni were higher in the 63–125 μm fraction. Though some elements had statistically significant differences between fractions (Al, Ba, Fe and Zn) percentage differences were in the range of analytical precision of the instrument and thus differences were not practically significant. Correlation analysis indicated strong positive associations for all elements between the two fractions (p<0.0001). Three contamination indices indicated similar degrees of pollution for each size fraction for four elements having an anthropogenic signal (Ba, Cu, Pb and Zn). The environmental information obtained from the 63–125 μm fraction was essentially equivalent to that from the <63 μm fraction. In this system it is clear that both bed sediment fractions indicate anthropogenic enrichment of trace metals, especially Pb, and further supports previous research that has found that aquatic sediments are critical median for tracing sources of pollution. Received: 17 August 1998 · Accepted: 30 October 1998