New snow metrics for a warming world

Snow is Earth's most climatically sensitive land cover type. Traditional snow metrics may not be able to adequately capture the changing nature of snow cover. For example, April 1 snow water equivalent (SWE) has been an effective index for streamflow forecasting, but it cannot express the effects of midwinter melt events, now expected in warming snow climates, nor can we assume that station-based measurements will be representative of snow conditions in future decades. Remote sensing and climate model data provide capacity for a suite of multi-use snow metrics from local to global scales. Such indicators need to be simple enough to “tell the story” of snowpack changes over space and time, but not overly simplistic or overly complicated in their interpretation. We describe a suite of spatially explicit, multi-temporal snow metrics based on global satellite data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and downscaled climate model output for the U.S. We describe and provide examples for Snow Cover Frequency (SCF), Snow Disappearance Date (SDD), At-Risk Snow (ARS), and Frequency of a Warm Winter (FWW). Using these retrospective and prospective snow metrics, we assess the current and future snow-related conditions in three hydroclimatically different U.S. watersheds: the Truckee, Colorado Headwaters, and Upper Connecticut. In the two western U.S. watersheds, SCF and SDD show greater sensitivity to annual differences in snow cover compared with data from the ground-based Snow Telemetry (SNOTEL) network. The eastern U.S. watershed does not have a ground-based network of data, so these MODIS-derived metrics provide uniquely valuable snow information. The ARS and FWW metrics show that the Truckee Watershed is highly vulnerable to conversion from snowfall to rainfall (ARS) and midwinter melt events (FWW) throughout the seasonal snow zone. In comparison, the Colorado Headwaters and Upper Connecticut Watersheds are colder and much less vulnerable through mid- and late-century.     

Probing the Formation and Evolution of early-type galaxies: the SAURON project

We are conducting a systematic study of a carefully selected sampleof nearby E/S0 galaxies and Sa bulges using the unique panoramic integral-fieldspectrograph SAURON, mounted at the WHT. The goal of the SAURON projectis to fully map the gaseous/stellar kinematics and the stellar populations of a representative sample of 80 early-type galaxies up to 1 Re,probing different environments (clusters, field). These data, used in combination with existing ground-based and HST observations, and fed to the theoretical machinery we have developed, will allow to determine theintrinsic dynamical structure of the galaxies. We will also measure the masses of central black holes, relate the internal dynamics to the ageand metallicity of the stellar populations, and establish the historyof metal enrichment as a function of Hubble type and environment. Some brief results on two targets observed during the SAURON campaign will serve as an illustration of the unique and high quality data we are currently gathering. This revised version was published online in September 2006 with corrections to the Cover Date.     

Surficial and Deep Earth Material Prediction from Geochemical Compositions

Prediction of true classes of surficial and deep earth materials using multivariate spatial data is a common challenge for geoscience modelers. Most geological processes leave a footprint that can be explored by geochemical data analysis. These footprints are normally complex statistical and spatial patterns buried deep in the high-dimensional compositional space. This paper proposes a spatial predictive model for classification of surficial and deep earth materials derived from the geochemical composition of surface regolith. The model is based on a combination of geostatistical simulation and machine learning approaches. A random forest predictive model is trained, and features are ranked based on their contribution to the predictive model. To generate potential and uncertainty maps, compositional data are simulated at unsampled locations via a chain of transformations (isometric log-ratio transformation followed by the flow anamorphosis) and geostatistical simulation. The simulated results are subsequently back-transformed to the original compositional space. The trained predictive model is used to estimate the probability of classes for simulated compositions. The proposed approach is illustrated through two case studies. In the first case study, the major crustal blocks of the Australian continent are predicted from the surface regolith geochemistry of the National Geochemical Survey of Australia project. The aim of the second case study is to discover the superficial deposits (peat) from the regional-scale soil geochemical data of the Tellus Project. The accuracy of the results in these two case studies confirms the usefulness of the proposed method for geological class prediction and geological process discovery.

     

Microbial mass-dependent fractionation of chromium isotopes

Mass-dependent fractionation of Cr isotopes occurs during dissimilatory Cr(VI) reduction by Shewanella oneidensis strain MR-1. Cells suspended in a simple buffer solution, with various concentrations of lactate or formate added as electron donor, reduced 5 or 10 μM Cr(VI) to Cr(III) over days to weeks. In all nine batch experiments, ⁵³Cr/⁵²Cr ratios of the unreacted Cr(VI) increased as reduction proceeded. In eight experiments covering a range of added donor concentrations up to 100 μM, isotopic fractionation factors were nearly invariant, ranging from 1.0040 to 1.0045, with a mean value somewhat larger than that previously reported for abiotic Cr(VI) reduction (1.0034). One experiment containing much greater donor concentration (10 mM lactate) reduced Cr(VI) much faster and exhibited a lesser fractionation factor (1.0018). These results indicate that ⁵³Cr/⁵²Cr measurements should be effective as indicators of Cr(VI) reduction, either bacterial or abiotic. However, variability in the fractionation factor is poorly constrained and should be studied for a variety of microbial and abiotic reduction pathways.     

Erodibility of low‐compaction steep‐sloped reclaimed surface mine lands in the southern Appalachian region,USA

The use of loose spoils on steep slopes for surface coal mining reclamation sites has been promoted by the US Department of Interior, Office of Surface Mining for the establishment of native forest, as prescribed by the Forest Reclamation Approach (FRA). Although low‐compaction spoils improve tree survival and growth, erodibility on steep slopes was suspected to increase. This study quantified a combined K_C factor (combining the effects of the soil erodibility K factor and cover management C) for low compaction, steep‐sloped (>20°) reclaimed mine lands in the Appalachian region, USA. The combined K_C factor was used because standard Unit Plot conditions required to separate these factors, per Revised Universal Soil Loss Equation (RUSLE) experimental protocols, were not followed explicitly. Three active coal mining sites in the Appalachian region of East Tennessee, each containing four replicate field plots, were monitored for rainfall and sediment yields during a 14‐month period beginning June 2009. Average cumulative erosivity for the study sites during the monitoring period was measured as 5248.9 MJ·mm·ha^?1·h^?1. The K_C ranged between 0.001 and 0.05 t·ha·h·ha^?1·MJ^?1·mm^?1, with the highest values occurring immediately following reclamation site construction as rills developed (June – August 2009). The K_C for two study sites with about an 18–20 mm spoil D₈₄ were above 0.01 t·ha·h·ha^?1·MJ^?1·mm^?1 during rill development, and below 0.003 t·ha·h·ha^?1·MJ^?1·mm^?1 after August 2009 for the post‐rill development period. The K_C values for one site with a 40 mm spoil D₈₄ were never above 0.008 t·ha·h·ha^?1·MJ^?1·mm^?1 and also on average were lower, being more similar to the other two sites after the rill development period. Based on an initial K_C factor (K_e) measured during the first few storm events, the average C factor (C_e) was estimated as 0.58 for the rill development period and 0.13 for the post‐rill development period. It appears that larger size fractions of spoils influence K_C and C_e factors on low‐compaction steep slopes reclamation sites. Copyright © 2013 John Wiley & Sons, Ltd.     

Heat tracing to examine seasonal groundwater flow beneath a low-gradient stream in rural central Illinois,USA

The thermal profile of a streambed is affected by a number of factors including: temperatures of stream water and groundwater, hydraulic conductivity, thermal conductivity, heat capacity of the streambed, and the geometry of hyporheic flow paths. Changes in these parameters over time cause changes in thermal profiles. In this study, temperature data were collected at depths of 30, 60, 90 and 150 cm at six streambed wells 5 m apart along the thalweg of Little Kickapoo Creek, in rural central Illinois, USA. This is a third-order low-gradient baseflow-fed stream. A positive temperature gradient with inflection at 90-cm depth was observed during the summer period. A negative temperature gradient with inflection at 30 cm was observed during the winter period, which suggests greater influence of stream-water temperatures in the substrate during the summer. Thermal models of the streambed were built using VS2DHI to simulate the thermal profiles observed in the field. Comparison of the parameters along with analysis of temperature envelopes and Peclet numbers suggested greater upwelling and stability in temperatures during the winter than during the summer. Upwelling was more pronounced in the downstream reach of the pool in the riffle and pool sequence.     

Soils and stratigraphy of the laddie creek site (48BH345), an altithermal-age occupation in the big horn mountains,wyoming

Haploborolls and Ustifluvents with A-C horizonation characterize Holocene soil development in alluvium and colluvium of the Laddie Creek valley. Cumulic soils with overthickened A horizons, including those of Altithermal age, have formed along the valley walls under the influence of spring activity from the Amsden Formation (Mississippian-Pennsylvanian). Soil texture, mineralogy, and to some extent color, are inherited largely from sediment derived from the Amsden and Tensleep (Pennsylvanian) Formations. The valley was able to support human occupation during Altithermal time (ca. 7500-4000 B.P.) because of springs emanating from the valley walls. Past spring locations are identified from soil morphology and stratigraphy. Springs are still active along the valley, although they have shifted positions many times in the past. The association of spring soils with Altithermal-age occupation at the site (ca. 6600-5700 B.P.) does not coincide with the caliche concept of the Altithermal paleosol in Holocene alluvial valleys in Wyoming basins as identified by Leopold and Miller. Nevertheless, early man of Altithermal time probably sought higher elevations within mountains of the region where springs offered water and the environs provided food and shelter—thus enabling human groups to survive the drought, and possible high temperatures, which seemingly prevailed in the basins and plains.