High-resolution climate simulation of the last glacial maximum

The climate of the last glacial maximum (LGM) is simulated with a high-resolution atmospheric general circulation model, the NCAR CCM3 at spectral truncation of T170, corresponding to a grid cell size of roughly 75 km. The purpose of the study is to assess whether there are significant benefits from the higher resolution simulation compared to the lower resolution simulation associated with the role of topography. The LGM simulations were forced with modified CLIMAP sea ice distribution and sea surface temperatures (SST) reduced by 1°C, ice sheet topography, reduced CO₂, and 21,000 BP orbital parameters. The high-resolution model captures modern climate reasonably well, in particular the distribution of heavy precipitation in the tropical Pacific. For the ice age case, surface temperature simulated by the high-resolution model agrees better with those of proxy estimates than does the low-resolution model. Despite the fact that tropical SSTs were only 2.1°C less than the control run, there are many lowland tropical land areas 4–6°C colder than present. Comparison of T170 model results with the best constrained proxy temperature estimates (noble gas concentrations in groundwater) now yield no significant differences between model and observations. There are also significant upland temperature changes in the best resolved tropical mountain belt (the Andes). We provisionally attribute this result in part as resulting from decreased lateral mixing between ocean and land in a model with more model grid cells. A longstanding model-data discrepancy therefore appears to be resolved without invoking any unusual model physics. The response of the Asian summer monsoon can also be more clearly linked to local geography in the high-resolution model than in the low-resolution model; this distinction should enable more confident validation of climate proxy data with the high-resolution model. Elsewhere, an inferred salinity increase in the subtropical North Atlantic may have significant implications for ocean circulation changes during the LGM. A large part of the Amazon and Congo Basins are simulated to be substantially drier in the ice age—consistent with many (but not all) paleo data. These results suggest that there are considerable benefits derived from high-resolution model regarding regional climate responses, and that observationalists can now compare their results with models that resolve geography at a resolution comparable to that which the proxy data represent.     

Compression Behaviour of Chlef Sand and Transition of Fines Content Using Pressure-Dependent Maximum Void Ratios of Sand

Geotechnical and Geological Engineering - This paper presents a study on Chlef sand to examine the effect of fines content (Fc), relative density (RD) and initial conditions on the compressibility...     

Variogram Model Selection via Nonparametric Derivative Estimation

Before optimal linear prediction can be performed on spatial data sets, the variogram is usually estimated at various lags and a parametric model is fitted to those estimates. Apart from possible a priori knowledge about the process and the user's subjectivity, there is no standard methodology for choosing among valid variogram models like the spherical or the exponential ones. This paper discusses the nonparametric estimation of the variogram and its derivative, based on the spectral representation of positive definite functions. The use of the estimated derivative to help choose among valid parametric variogram models is presented. Once a model is selected, its parameters can be estimated—for example, by generalized least squares. A small simulation study is performed that demonstrates the usefulness of estimating the derivative to help model selection and illustrates the issue of aliasing. MATLAB software for nonparametric variogram derivative estimation is available at http://www-math.mit.edu/~gorsich/derivative.html. An application to the Walker Lake data set is also presented.     

Thermal contraction crack polygons on Mars: A synthesis from HiRISE, Phoenix, and terrestrial analog studies

Thermal contraction crack polygons are complex landforms that have begun to be deciphered on Earth and Mars by the combined investigative efforts of geomorphology, environmental monitoring, physical models, paleoclimate reconstruction, and geochemistry. Thermal contraction crack polygons are excellent indicators of the current or past presence of ground ice, ranging in ice content from weakly cemented soils to debris-covered massive ice. Relative to larger topographic features, polygons may form rapidly, and reflect climate conditions at the time of formation—preserving climate information as relict landforms in the geological record. Polygon morphology and internal textural characteristics can be used to distinguish surfaces modified by the seasonal presence of a wet active layer or dry active layer, and to delimit subsurface ice conditions. Analysis of martian polygon morphology and distribution indicates that geologically-recent thermal contraction crack polygons on Mars form predominantly in an ice-rich latitude-dependent mantle, more likely composed of massive ice deposited by precipitation than by cyclical vapor diffusion into regolith. Regional and local heterogeneities in polygon morphology can be used to distinguish variations in ice content, deposition and modification history, and to assess microclimate variation on timescales of ka to Ma. Analyses of martian polygon morphology, guided by investigations of terrestrial analog thermal contraction crack polygons, strongly suggest the importance of excess ice in the formation and development of many martian thermal contraction crack polygons—implying the presence of an ice-rich substrate that was fractured during and subsequent to obliquity-driven depositional periods and continually modified by ongoing vapor equilibration processes.     

内蒙古鄂尔多斯高原古冰缘遗迹科学考察研究进展

冰缘遗迹(特别是冷生楔形构造及融冻褶皱)是重建古气候及第四纪晚期多年冻土环境的重要证据.内蒙古鄂尔多斯高原是我国北方地区冰缘现象最为发育的地区之一.为准确了解鄂尔多斯高原冰缘遗迹类型及其分布特征、区域冻土演化历史等,中国科学院西北生态环境资源研究院和荷兰自由大学共同组成科研小组,于2018年5—6月组织了"鄂尔多斯高原...     

Defining the Potential of Nanoscale Re‐Os Isotope Systematics Using Atom Probe Microscopy

Atom probe microscopy (APM) is a relatively new in situ tool for measuring isotope fractions from nanoscale volumes (< 0.01 μm³). We calculate the theoretical detectable difference of an isotope ratio measurement result from APM using counting statistics of a hypothetical data set to be ± 4δ or 0.4% (2s). However, challenges associated with APM measurements (e.g., peak ranging, hydride formation and isobaric interferences), result in larger uncertainties if not properly accounted for. We evaluate these factors for Re‐Os isotope ratio measurements by comparing APM and negative thermal ionisation mass spectrometry (N‐TIMS) measurement results of pure Os, pure Re, and two synthetic Re‐Os‐bearing alloys from Schwander et al. (2015, Meteoritics and Planetary Science, 50, 893) [the original metal alloy (HSE) and alloys produced by heating HSE within silicate liquid (SYN)]. From this, we propose a current best practice for APM Re‐Os isotope ratio measurements. Using this refined approach, mean APM and N‐TIMS ¹⁸⁷Os/¹⁸⁹Os measurement results agree within 0.05% and 2s (pure Os), 0.6–2% and 2s (SYN) and 5–10% (HSE). The good agreement of N‐TIMS and APM ¹⁸⁷Os/¹⁸⁹Os measurements confirms that APM can extract robust isotope ratios. Therefore, this approach permits nanoscale isotope measurements of Os‐bearing alloys using the Re‐Os geochronometer that could not be measured by conventional measurement principles.     

Nonhydrostatic effects and the determination of icy satellites’ moment of inertia

We compare the moment of inertia (MOI) of a simple hydrostatic, two layer body as determined by the Radau–Darwin Approximation (RDA) to its exact hydrostatic MOI calculated to first order in the parameter q = Ω²R³/GM, where Ω, R, and M are the spin angular velocity, radius, and mass of the body, and G is the gravitational constant. We show that the RDA is in error by less than 1% for many configurations of core sizes and layer densities congruent with those of solid bodies in the Solar System. We then determine the error in the MOI of icy satellites calculated with the RDA due to nonhydrostatic effects by using a simple model in which the core and outer shell have slight degree 2 distortions away from their expected hydrostatic shapes. Since the hydrostatic shape has an associated stress of order ρΩ²R² (where ρ is density) it follows that the importance of nonhydrostatic effects scales with the dimensionless number σ/ρΩ²R², where σ is the nonhydrostatic stress. This highlights the likely importance of this error for slowly rotating bodies (e.g., Titan and Callisto) and small bodies (e.g., Saturn moons other than Titan). We apply this model to Titan, Callisto, and Enceladus and find that the RDA-derived MOI can be 10% greater than the actual MOI for nonhydrostatic stresses as small as ∼0.1 bars at the surface or ∼1 bar at the core–mantle boundary, but the actual nonhydrostatic stresses for a given shape change depends on the specifics of the interior model. When we apply this model to Ganymede we find that the stresses necessary to produce the same MOI errors as on Titan, Callisto, and Enceladus are an order of magnitude greater due to its faster rotation, so Ganymede may be the only instance where RDA is reliable. We argue that if satellites can reorient to the lowest energy state then RDA will always give an overestimate of the true MOI. Observations have shown that small nonhydrostatic gravity anomalies exist on Ganymede and Titan, at least at degree 3 and presumably higher. If these anomalies are indicative of the nonhydrostatic anomalies at degree 2 then these imply only a small correction to the MOI, even for Titan, but it is possible that the physical origin of nonhydrostatic degree 2 effects is different from the higher order terms. We conclude that nonhydrostatic effects could be present to an extent that allows Callisto and Titan to be fully differentiated.     

Temporal variations in bedload transport rates associated with the migration of bedforms

Temporal variations in bedload transport rates that occur at a variety of timescales, even under steady flow conditions, are accepted as an inherent component of the bedload transport process. Rarely, however, has the cause of such variations been explained clearly. We consider three data sets, obtained from laboratory experiments, that refer to measurements of bedload transport made with continuously recording bedload traps. Each data set is characterized by a predominant low-frequency oscillation, on which additional higher-frequency oscillations generally are superimposed. The period of these oscillations, as isolated through the use of spectral analysts, ranged between 0·47 and 168 minutes, and was associated unequivocally with the migration of bedforms such as ripples, dunes, and bars. The extent to which such oscillatory behaviour may be recognized in a data set depends on the duration of sampling and the length of the sampling time, with respect to the period of a given bedform. Several theoretical probability distribution functions have been developed to describe the frequency distributions of (relative) bedload transport rates that are associated with the migration of bedforms (Einstein, 1937b; Hamamori, 1962; Carey and Hubbell, 1986). These distribution functions were derived without reference to a sampling interval. We present a modification of Hamamori's (1962) probability distribution function, generated by Monte Carlo simulation, which permits one to specify the sampling interval, in relation to the length of a bedform. Comparisons between the simulated and observed frequency distributions, that were undertaken on the basis of the data described herein, are good (significant at the 90 per cent confidence level). Finally, the implications that temporal variability, which is associated with the migration of bedforms, have for the accurate determination of bedload transport rates are considered.     

Developing coastal adaptation to climate change in the New York City infrastructure-shed: process, approach, tools, and strategies

While current rates of sea level rise and associated coastal flooding in the New York City region appear to be manageable by stakeholders responsible for communications, energy, transportation, and water infrastructure, projections for sea level rise and associated flooding in the future, especially those associated with rapid icemelt of the Greenland and West Antarctic Icesheets, may be outside the range of current capacity because extreme events might cause flooding beyond today??s planning and preparedness regimes. This paper describes the comprehensive process, approach, and tools for adaptation developed by the New York City Panel on Climate Change (NPCC) in conjunction with the region??s stakeholders who manage its critical infrastructure, much of which lies near the coast. It presents the adaptation framework and the sea-level rise and storm projections related to coastal risks developed through the stakeholder process. Climate change adaptation planning in New York City is characterized by a multi-jurisdictional stakeholder?Cscientist process, state-of-the-art scientific projections and mapping, and development of adaptation strategies based on a risk-management approach.     

Modelling the effect of changing precipitation inputs on deep soil water utilization

Forests in the Southeastern United States are predicted to experience future changes in seasonal patterns of precipitation inputs as well as more variable precipitation events. These climate change‐induced alterations could increase drought and lower soil water availability. Drought could alter rooting patterns and increase the importance of deep roots that access subsurface water resources. To address plant response to drought in both deep rooting and soil water utilization as well as soil drainage, we utilize a throughfall reduction experiment in a loblolly pine plantation of the Southeastern United States to calibrate and validate a hydrological model. The model was accurately calibrated against field measured soil moisture data under ambient rainfall and validated using 30% throughfall reduction data. Using this model, we then tested these scenarios: (a) evenly reduced precipitation; (b) less precipitation in summer, more in winter; (c) same total amount of precipitation with less frequent but heavier storms; and (d) shallower rooting depth under the above 3 scenarios. When less precipitation was received, drainage decreased proportionally much faster than evapotranspiration implying plants will acquire water first to the detriment of drainage. When precipitation was reduced by more than 30%, plants relied on stored soil water to satisfy evapotranspiration suggesting 30% may be a threshold that if sustained over the long term would deplete plant available soil water. Under the third scenario, evapotranspiration and drainage decreased, whereas surface run‐off increased. Changes in root biomass measured before and 4 years after the throughfall reduction experiment were not detected among treatments. Model simulations, however, indicated gains in evapotranspiration with deeper roots under evenly reduced precipitation and seasonal precipitation redistribution scenarios but not when precipitation frequency was adjusted. Deep soil and deep rooting can provide an important buffer capacity when precipitation alone cannot satisfy the evapotranspirational demand of forests. How this buffering capacity will persist in the face of changing precipitation inputs, however, will depend less on seasonal redistribution than on the magnitude of reductions and changes in rainfall frequency.