Statistical properties of polarized radio continuum emission and effects of data processing

Polarized intensity and polarization angles are calculated from Stokes parameters Q and U in a nonlinear way. The statistical properties of polarized emission hold information about the structure of magnetic fields in a large range of scales, but the contributions of different stages of data processing to the statistical properties should first be understood. We use 1.4 GHz polarization data from the Effelsberg 100‐m telescope of emission in the Galactic plane, near the plane and far out of the plane. We analyze the probability distribution function and the wavelet spectrum of the original maps in Stokes parameters Q, U and corresponding PI. Then we apply absolute calibration (i.e. adding the large‐scale emission to the maps in Q and U), subtraction of polarized sources and subtraction of the positive bias in PI due to noise (“denoising”). We show how each procedure affects the statistical properties of the data. We find a complex behavior of the statistical properties for the different regions analyzed which depends largely on the intensity level of polarized emission. Absolute calibration changes the morphology of the polarized structures. The statistical properties change in a complex way: Compact sources in the field flatten the wavelet spectrum over a substantial range. Adding large‐scale emission does not change the spectral slopes in Q and U at small scales, but changes the PI spectrum in a complex way. “Denoising” significantly changes the p.d.f. of PI and raises the entire spectrum. The final spectra are flat in the Galactic plane due to magnetic structures in the ISM, but steeper at high Galactic latitude and in the anticenter. For a reliable study of the statistical properties of magnetic fields and turbulence in the ISM based on radio polarization observations, absolute calibration and source subtraction are required. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Collapse assessment of moment frame buildings,considering vertical ground shaking

While many cases of structural damage in past earthquakes have been attributed to strong vertical ground shaking, our understanding of vertical seismic load effects and their influence on collapse mechanisms of buildings is limited. This study quantifies ground motion parameters that are capable of predicting trends in building collapse because of vertical shaking, identifies the types of buildings that are most likely affected by strong vertical ground motions, and investigates the relationship between element level responses and structural collapse under multi‐directional shaking. To do so, two sets of incremental dynamic analyses (IDA) are run on five nonlinear building models of varying height, geometry, and design era. The first IDA is run using the horizontal component alone; the second IDA applies the vertical and horizontal motions simultaneously. When ground motion parameters are considered independently, acceleration‐based measures of the vertical shaking best predict trends in building collapse associated with vertical shaking. When multiple parameters are considered, Housner intensity (SI), computed as a ratio between vertical and horizontal components of a record (SI_V/SI_H), predicts the significance of vertical shaking for collapse. The building with extensive structural cantilevered members is the most influenced by vertical ground shaking, but all frame structures (with either flexural and shear critical columns) are impacted. In addition, the load effect from vertical ground motions is found to be significantly larger than the nominal value used in US building design. Copyright © 2016 John Wiley & Sons, Ltd.     

Regional and global projections of twenty-first century glacier mass changes in response to climate scenarios from global climate models

A large component of present-day sea-level rise is due to the melt of glaciers other than the ice sheets. Recent projections of their contribution to global sea-level rise for the twenty-first century range between 70 and 180 mm, but bear significant uncertainty due to poor glacier inventory and lack of hypsometric data. Here, we aim to update the projections and improve quantification of their uncertainties by using a recently released global inventory containing outlines of almost every glacier in the world. We model volume change for each glacier in response to transient spatially-differentiated temperature and precipitation projections from 14 global climate models with two emission scenarios (RCP4.5 and RCP8.5) prepared for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The multi-model mean suggests sea-level rise of 155 ± 41 mm (RCP4.5) and 216 ± 44 mm (RCP8.5) over the period 2006–2100, reducing the current global glacier volume by 29 or 41 %. The largest contributors to projected global volume loss are the glaciers in the Canadian and Russian Arctic, Alaska, and glaciers peripheral to the Antarctic and Greenland ice sheets. Although small contributors to global volume loss, glaciers in Central Europe, low-latitude South America, Caucasus, North Asia, and Western Canada and US are projected to lose more than 80 % of their volume by 2100. However, large uncertainties in the projections remain due to the choice of global climate model and emission scenario. With a series of sensitivity tests we quantify additional uncertainties due to the calibration of our model with sparsely observed glacier mass changes. This gives an upper bound for the uncertainty range of ±84 mm sea-level rise by 2100 for each projection.     

Comparison of event‐specific rainfall–runoff responses and their controls in contrasting geographic areas

Numerous studies have examined the event‐specific hydrologic response of hillslopes and catchments to rainfall. Knowledge gaps, however, remain regarding the relative influence of different meteorological factors on hydrologic response, the predictability of hydrologic response from site characteristics, or even the best metrics to use to effectively capture the temporal variability of hydrologic response. This study aimed to address those knowledge gaps by focusing on 21 sites with contrasting climate, topography, geology, soil properties, and land cover. High‐frequency rainfall and discharge records were analysed, resulting in the delineation of over 1,600 rainfall–runoff events, which were described using a suite of hydrologic response metrics and meteorological factors. Univariate and multivariate statistical techniques were then applied to synthesize the information conveyed by the computed metrics and factors, notably measures of central tendency and variability, variation partitioning, partial correlations, and principal component analysis. Results showed that some response magnitude metrics generally reported in the literature (e.g., runoff ratio and area‐normalized peak discharge) did not vary significantly among sites. The temporal variability in site‐specific hydrologic response was often attributable to the joint influence of storage‐driven (e.g., total event rainfall and antecedent precipitation) and intensity‐driven (e.g., rainfall intensity and antecedent potential evapotranspiration) meteorological factors. Mean annual temperature and potential evapotranspiration at a given site appeared to be good predictors of hydrologic response timing (e.g., response lag and lag to peak). Response timing metrics, particularly those associated with response initiation, were also identified as the metrics most critical for capturing intrasite response variability. This study therefore contributes to the growing knowledge on event‐specific hydrologic response by highlighting the importance of response timing metrics and intensity‐driven meteorological factors, which are infrequently discussed in the literature. As few correlations were found between physiographic variables and response metrics, more data‐driven studies are recommended to further our understanding of landscape–hydrology interactions.     

Diagenesis of plant biopolymers: Decay and macromolecular preservation of Metasequoia

Analysis of modern Metasequoia leaves revealed the presence of the structural polyester cutin, guaiacyl lignin units and polysaccharides. Analysis of environmentally decayed Metasequoia leaves revealed that guaiacyl lignin units and cellulose were degraded more than vinyl phenol (the last being the primary pyrolysis product of cutin and plant cuticles) suggesting that cutin is more stable than lignin and cellulose during degradation, contrary to some previous studies. This observation is supported by electron microscopy showing changes in the cellular structure and cuticle of modern, decayed and fossil Metasequoia leaves. Metasequoia fossils from the Eocene of Republic (Washington State) showed a significant aliphatic component, but biopolymeric lignin and polysaccharides were not detected. Fossils from the Eocene of Axel Heiberg revealed the presence of lignin and an aliphatic polymer up to C₂₉ with cellulose, and fossils from the Miocene Clarkia deposit (Idaho) revealed lignin and an aliphatic polymer up to C₂₇ without any polysaccharides. Modern Metasequoia needles heated experimentally in confined conditions generated a macromolecular composition with an aliphatic polymer up to C₃₂ and additional phenolic compounds similar to those present in the fossils. Experimental heating of cutin is known to generate an aliphatic polymer with carbon chain length units <C₂₀. Thus, the n-alkyl component with chain length units >C₂₀ in the heated Metasequoia needles is a product of incorporation of longer chain plant waxes, indicated by the odd/even predominance of the >C₂₇ n-alkanes. The resistant nature of cutin compared to lignin and polysaccharides explains the presence of an n-alkyl component (<C₂₀) in fossil leaves even when polysaccharides are absent and lignin has decayed; cutin and its diagenetically altered products contribute significantly to the presence of aliphatic components in terrestrially derived sedimentary organic matter.     

Potential extents for ENSO-driven hydrologic drought forecasts in the United States

The relationship between the El Niño-Southern Oscillation (ENSO) and hydrologic variability in the United States is investigated using Empirical Orthogonal Function (EOF)/Principal Component Analysis (PCA). The multivariate ENSO index (MEI) is utilized to identify strong coherences associated with multiple months (1-, 2-, 4-, 6-, 12-, 24-, 48-month) of the Log-Standardized Hydrologic Drought Index (LSHDI) in the conterminous states for the period 1950–2005. Based on 56 years of monthly streamflow data for 102 forecast climate divisions, this research explores the spatial and temporal variation of hydrologic responses corresponding to ENSO events. Preliminary results show that a potential predictor of the dominant streamflow modes in the northern Great Plains is identified from streamflows in western Arizona. Also, positive relationships between hydrologic drought and El Niño were found in the Pacific Northwest (Washington, Oregon, and northern California), whereas negative relationships were detected in southern California and the northern Great Plains. These findings will provide useful insights to help improve streamflow forecast potential and capabilities, and minimize the impacts of hydrologic events (e.g. floods and droughts) associated with ENSO events.     

Anharmonicity of Stellar Cycles: A Wavelet Quantification

Two quantitative measures for the anharmonicity of stellar cycles, as recorded in the Ca II H and K chromospheric activity data as well as in simple dynamo models, are presented and discussed.     

Time-spectra of chromospheric activity of old solar-type stars: detection of rotational signals from double wavelet analysis

We introduce a novel technique, called the double wavelet analysis (DWA), for the determination of stellar rotation periods from time serial data. This first paper aims narrowly at the discussion, introduction and application of the DWA technique to records of surface magnetism in solar-type (relatively old) lower main sequence stars that are obtained by the Mount Wilson Observatory (MWO) HK Project. The technique takes a series of careful steps that seek to optimize wavelet parameters and normalization schemes, ultimately allowing fine-tuned, arguably more accurate, estimates of rotation-modulated signals (with, e.g., periods of days to months) in records that contain longer periodicities such as stellar magnetic activity cycles (with, e.g., period of years). The apparent rotation periods estimated from the DWA technique are generally consistent with results from both “first-pass” (i.e., ordinary) global wavelet spectrum and earlier classical periodogram analyses. But there are surprises as well. For example, the rotation period of the ancient subdwarf Goombridge 1830 (HD 103095), previously identified as ≈31 days, suggests under the DWA technique a significantly slower period of 60 days. DWA spectra also generally reveal a shift in the cycle period toward high frequencies (hence shorter periods) compared to the first-pass wavelet spectrum. For solar-type stars analyzed here, the character of the DWA spectrum and slope of the first-pass global wavelet spectrum produce a classification scheme that allows a star's record to be placed into one of three categories.