Heavy REE are compatible in clinopyroxene on the spinel lherzolite solidus

Trace element partitioning between clinopyroxene and melt was investigated experimentally under conditions appropriate to near-solidus melting of spinel lherzolite in the upper mantle. Starting material was a high-Na, Al basalt glass previously shown to be a very low degree (1%) partial melt of spinel lherzolite at 1.5 GPa, 1269°C [Robinson et al., Earth Planet. Sci. Lett., in press]. The experiment was run with a spinel seed under sub-liquidus conditions (1255°C) to ensure clinopyroxene crystallisation. The experimental clinopyroxene composition is consistent with equilibrium close to the solidus of fertile mantle lherzolite, most notably in its high contents of Ca-Tschermak's (CaTs) molecule (22 mol %) and Na₂O (1.4 wt%). Clinopyroxene–melt partition coefficients (D) for a wide range of trace elements, determined by SIMS analysis of run products, differ markedly from those reported in other studies under conditions less appropriate to mantle melting. In particular partition coefficients for the heavy rare earth elements (Gd–Lu) are greater than unity (e.g. D_Lu=1.45), and the critical partitioning parameter, (D_Sm/D_Nd)×(D_Hf/D_Lu), is 0.68. These features, which arise due to the high CaTs content of the clinopyroxene, dramatically reduce the required involvement of garnet in the melting region beneath mid-ocean ridges.     

Evaluation of summer temperature and precipitation predictions from NCEP CFSv2 retrospective forecast over China

National Centers for Environmental Prediction recently upgraded its operational seasonal forecast system to the fully coupled climate modeling system referred to as CFSv2. CFSv2 has been used to make seasonal climate forecast retrospectively between 1982 and 2009 before it became operational. In this study, we evaluate the model’s ability to predict the summer temperature and precipitation over China using the 120 9-month reforecast runs initialized between January 1 and May 26 during each year of the reforecast period. These 120 reforecast runs are evaluated as an ensemble forecast using both deterministic and probabilistic metrics. The overall forecast skill for summer temperature is high while that for summer precipitation is much lower. The ensemble mean reforecasts have reduced spatial variability of the climatology. For temperature, the reforecast bias is lead time-dependent, i.e., reforecast JJA temperature become warmer when lead time is shorter. The lead time dependent bias suggests that the initial condition of temperature is somehow biased towards a warmer condition. CFSv2 is able to predict the summer temperature anomaly in China, although there is an obvious upward trend in both the observation and the reforecast. Forecasts of summer precipitation with dynamical models like CFSv2 at the seasonal time scale and a catchment scale still remain challenge, so it is necessary to improve the model physics and parameterizations for better prediction of Asian monsoon rainfall. The probabilistic skills of temperature and precipitation are quite limited. Only the spatially averaged quantities such as averaged summer temperature over the Northeast China of CFSv2 show higher forecast skill, of which is able to discriminate between event and non-event for three categorical forecasts. The potential forecast skill shows that the above and below normal events can be better forecasted than normal events. Although the shorter the forecast lead time is, the higher deterministic prediction skill appears, the probabilistic prediction skill does not increase with decreased lead time. The ensemble size does not play a significant role in affecting the overall probabilistic forecast skill although adding more members improves the probabilistic forecast skill slightly.     

Assessing Climate Change Implications for Water Resources Planning

Numerous recent studies have shown that existing water supply systems are sensitive to climate change. One apparent implication is that water resources planning methods should be modified accordingly. Few of these studies, however, have attempted to account for either the chain of uncertainty in projecting water resources system vulnerability to climate change, or the adaptability of system operation resulting from existing planning strategies. Major uncertainties in water resources climate change assessments lie in a) climate modeling skill; b) errors in regional downscaling of climate model predictions; and c) uncertainties in future water demands. A simulation study was designed to provide insight into some aspects of these uncertainties. Specifically, the question that is addressed is whether a different decision would be made in a reservoir reallocation decision if knowledge about future climate were incorporated (i.e., would planning based on climate change information be justified?). The case study is possible reallocation of flood storage to conservation (municipal water supply) on the Green River, WA. We conclude that, for the case study, reservoir reallocation decisions and system performance would not differ significantly if climate change information were incorporated in the planning process.     

Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs

Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the NCAR-DOE Parallel ClimateModel (PCM), and the implications of the comparison for a future(2040–2060) PCM climate scenario were also explored. The six approaches were made up of three relatively simple statistical downscaling methods – linear interpolation (LI), spatial disaggregation (SD), and bias-correction and spatial disaggregation (BCSD) – each applied to both PCM output directly(at T42 spatial resolution), and after dynamical downscaling via a Regional Climate Model (RCM – at 1/2-degree spatial resolution), for downscaling the climate model outputs to the 1/8-degree spatial resolution of the hydrological model. For the retrospective climate simulation, results were compared to an observed gridded climatology of temperature and precipitation, and gridded hydrologic variables resulting from forcing the hydrologic model with observations. The most significant findings are that the BCSD method was successful in reproducing the main features of the observed hydrometeorology from the retrospective climate simulation, when applied to both PCM and RCM outputs. Linear interpolation produced better results using RCM output than PCM output, but both methods (PCM-LI and RCM-LI) lead to unacceptably biased hydrologic simulations. Spatial disaggregation of the PCM output produced results similar to those achieved with the RCM interpolated output; nonetheless, neither PCM nor RCM output was useful for hydrologic simulation purposes without a bias-correction step. For the future climate scenario, only the BCSD-method (using PCM or RCM) was able to produce hydrologically plausible results. With the BCSD method, the RCM-derived hydrology was more sensitive to climate change than the PCM-derived hydrology.     

Raman spectroscopic study of hydrous wadsleyite (β-Mg2SiO4) to 50 GPa

 Raman spectra of hydrous β-Mg₂SiO₄ (1.65 wt% H₂O) have been measured in a diamond-anvil cell with helium as a pressure-transmitting medium at room temperature to 50 GPa. We observe three OH-stretching modes, a doublet with components at 3329 and 3373 cm⁻¹, which decrease linearly with pressure, and a single mode at 3586 cm⁻¹, which remains nearly constant up to 24 GPa before decreasing at higher pressures. Assessment of the mode frequencies and their pressure dependence, together with previous results from X-ray and IR data, are consistent with protonation of the O1 site in agreement with previous studies. Strict assignment of Raman activity awaits detailed structural models. The nature of the protonation in wadsleyite may require more specific experimental probes for full solution of the hydrogen-site problem. Received: 18 July 2000 / Accepted: 22 November 2000     

Potential climate-change impacts on the Chesapeake Bay

We review current understanding of the potential impact of climate change on the Chesapeake Bay. Scenarios for CO₂ emissions indicate that by the end of the 21^st century the Bay region will experience significant changes in climate forcings with respect to historical conditions, including increases in CO₂ concentrations, sea level, and water temperature of 50–160%, 0.7–1.6 m, and 2–6 °C, respectively. Also likely are increases in precipitation amount (very likely in the winter and spring), precipitation intensity, intensity of tropical and extratropical cyclones (though their frequency may decrease), and sea-level variability. The greatest uncertainty is associated with changes in annual streamflow, though it is likely that winter and spring flows will increase. Climate change alone will cause the Bay to function very differently in the future. Likely changes include: (1) an increase in coastal flooding and submergence of estuarine wetlands; (2) an increase in salinity variability on many time scales; (3) an increase in harmful algae; (4) an increase in hypoxia; (5) a reduction of eelgrass, the dominant submerged aquatic vegetation in the Bay; and (6) altered interactions among trophic levels, with subtropical fish and shellfish species ultimately being favored in the Bay. The magnitude of these changes is sensitive to the CO₂ emission trajectory, so that actions taken now to reduce CO₂ emissions will reduce climate impacts on the Bay. Research needs include improved precipitation and streamflow projections for the Bay watershed and whole-system monitoring, modeling, and process studies that can capture the likely non-linear responses of the Chesapeake Bay system to climate variability, climate change, and their interaction with other anthropogenic stressors.     

Stellar rotation and the thermomagnetic torque

The thermomagnetic torque, known to exist when a gas of polyatomic molecules experiences a temperature gradient in the presence of a magnetic field, has been investigated as a possible source of stellar rotational angular momentum. The effect does not appear to be significant during pre-mainsequence evolution. To influence stellar rotation a process must be capable of generating torques on the order of 10⁴⁰ dyn cm^–1, whereas the effect due to the thermomagnetic torque is only as large as 10¹⁷, dyn cm^–1.