The Lacy Hotel Site: Gender Ideologies and Domestic Activities in a 19th Century Boardinghouse Context

The Lacy Hotel was a part of the Great Locomotive Chase , a significant historical event in Kennesaw, Georgia during the Civil War (AD 1861-1864), yet little is known of this site. The Lacy Hotel was a boardinghouse that operated for roughly six years until General William Tecumseh Sherman burned it in 1864. This research utilizes historical records along with archaeological fieldwork in order to provide a more detailed analysis of daily life within the Lacy household. Dominant ideologies influence the roles of women concerning their activities and choices of consumption within the household. Although the results show that the boardinghouse is not a typical household, the social dynamics and consumption are still constrained by the culture and ideology of the time period. In conclusion, this research offers a case study about the role of women on the eve of turmoil and contends that the boardinghouse is emblematic of broader changes within the rural South during the 19th century

An Improved and Homogeneous Altimeter Sea Level Record from the ESA Climate Change Initiative

Sea Level is a very sensitive index of climate change since it integrates the impacts of ocean warming and ice mass loss from glaciers and the ice sheets. Sea Level has been listed as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS). During the past 25 years, the sea level ECV has been measured from space by different altimetry missions that have provided global and regional observations of sea level variations. As part of the Climate Change Initiative (CCI) program of the European Space Agency (ESA) (established in 2010), the Sea Level project (SL_cci) aimed at providing an accurate and homogeneous long-term satellite-based sea level record. At the end of the first phase of the project (2010-2013), an initial version (v1.1) of the sea level ECV has been made available to users (Ablain et al., 2015). During the second phase (2014-2017), improved altimeter standards have been selected to produce new sea level products (called SL_cci v2.0) based on 9 altimeter missions for the period 1993-2015 (https://doi.org/10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612). Corresponding orbit solutions, geophysical corrections and altimeter standards used in this v2.0 dataset are described in details in Quartly et al. (2017). The present paper focuses on the description of the SL_cci v2.0 ECV and associated uncertainty and discusses how it has been validated. Various approaches have been used for the quality assessment such as internal validation, comparisons with sea level records from other groups and with in-situ measurements, sea level budget closure analyses and comparisons with model outputs. Compared to the previous version of the sea level ECV, we show that use of improved geophysical corrections, careful bias reduction between missions and inclusion of new altimeter missions lead to improved sea level products with reduced uncertainties at different spatial and temporal scales. However, there is still room for improvement since the uncertainties remain larger than the GCOS requirements. Perspectives for subsequent evolutions are also discussed

Zur Weiterentwicklung der Marktzinsmethode

Seit circa 10 Jahren ist die Marktzinsmethode als Kalkulations- und Steuerungselement des Bankbetriebes nicht nur einer starken Diskussion, sondern auch einer ständigen Weiterentwicklung unterworfen. Sie kann heute als wichtiges Instrument des Bank-Controlling bezeichnet werden. Die Entwicklung dieses Verfahrens begann im Jahre 1983, als ein amerikanisches Consulting-Unternehmen (McKinsey & Company, Inc.) ein neues Konzept zur Ermittlung der Zinsspanne für Kreditinstitute vorschlug. Dieses Konzept sah vor, Verrechnungszinsen für die Zinsspannenermittlung nicht mehr aus der Bilanz selbst zu ermitteln, wie es die traditionellen Verfahren der Teilzinsspannenrechnung vorsahen, sondern Opportunitätszinsen für die Verrechnung am Geld- und Kapitalmarkt (im folgenden als GKM abgekürzt) zu ermitteln. Es versprach, damit die Probleme der traditionellen Verfahren wie zum Beispiel Kunden- oder Filialkalkulation zu lösen

Seasonal variability of eddy kinetic energy in a global high-resolution ocean model

A global ocean model with 1/12∘ horizontal resolution is used to assess the seasonal cycle of surface Eddy Kinetic Energy (EKE). The model reproduces the salient features of the observed mean surface EKE, including amplitude and phase of its seasonal cycle in most parts of the ocean. In all subtropical gyres of the Pacific and Atlantic, EKE peaks in summer down to a depth of ∼350 m, below which the seasonal cycle is weak. Investigation of the possible driving mechanisms reveals the seasonal changes in the thermal interactions with the atmosphere to be the most likely cause of the summer maximum of EKE. The development of the seasonal thermocline in spring and summer is accompanied by stronger mesoscale variations in the horizontal temperature gradients near the surface which corresponds, by thermal wind balance, to an intensification of mesoscale velocity anomalies towards the surface

Effects of stencil width on surface ocean geostrophic velocity and vorticity estimation from gridded satellite altimeter data

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90421/1/2011JC007367.pd

Quantifying local rainfall dynamics and uncertain boundary conditions into a nested regional-local flood modeling system

[Abstract:] Inflow discharge and outflow stage estimates for hydraulic flood models are generally derived from river gauge data. Uncertainties in the measured inflow data and the neglect of rainfall-runoff contributions to the modeled domain downstream of the gauging locations can have a significant impact on these estimated “whole reach” inflows and consequently on flood predictions. In this study, a method to incorporate rating curve uncertainty and local rainfall-runoff dynamics into the predictions of a reach-scale flood model is proposed. The methodology is applied to the July 2007 floods of the River Severn in UK. Discharge uncertainty bounds are generated applying a nonparametric local weighted regression approach to stage-discharge measurements for two gauging stations. Measured rainfall downstream from these locations is used as input to a series of subcatchment regional hydrological model to quantify additional local inflows along the main channel. A regional simplified-physics hydraulic model is then applied to combine these contributions and generate an ensemble of discharge and water elevation time series at the boundaries of a local-scale high complexity hydraulic model. Finally, the effect of these rainfall dynamics and uncertain boundary conditions are evaluated on the local-scale model. Accurate prediction of the flood peak was obtained with the proposed method, which was only possible by resolving the additional complexity of the extreme rainfall contributions over the modeled area. The findings highlight the importance of estimating boundary condition uncertainty and local rainfall contributions for accurate prediction of river flows and inundation at regional scales.María Bermúdez gratefully acknowledges financial support from the Spanish Regional Government of Galicia (postdoctoral grant reference ED481B 2014/156-0). Gemma Coxon was supported by NERC MaRIUS: Managing the Risks, Impacts and Uncertainties of droughts and water Scarcity, grant NE/L010399/1. Jim Freer and Paul Bates by NERC Susceptibility of catchments to INTense RAinfall and flooding, grant NE/K00882X/1. A free version of the model LISFLOOD-FP is available for download at www.bristol.ac.uk/geography/research/hydrology/models/lisflood/. A free version of the model Iber is available for download at www.iberaula.es. The river cross-section data, the LiDAR digital elevation model and the gauging station rainfall, stage, flow and rating curve data of the presented case study are freely available from the Environment Agency ([email protected])Xunta de Galicia; ED481B 2014/156-0Inglaterra. University of Bristol; NE/L010399/1Inglaterra. University of Bristol; NE/K00882X/