Radiocarbon and the Archaeological Record: An Integrative Approach for Building an Absolute Chronology for the Late Bronze and Iron Ages of Israel

Radiocarbon ◽  
2015 ◽  
Vol 57 (2) ◽  
pp. 207-216 ◽  
Author(s):  
Elisabetta Boaretto
Keyword(s):  
High Resolution ◽  
Material Culture ◽  
Regional Scale ◽  
Integrative Approach ◽  
Data Sets ◽  
Archaeological Record ◽  
Organic Residues ◽  
Southern Levant ◽  
Historical Processes ◽  
The Impact

The establishment of an absolute chronology for the Late Bronze and Iron Ages in the southern Levant would make it possible to use changes in material culture in order to study the impact of trade, dissemination of knowledge, and the impact of climate on historical processes. To achieve this, a detailed absolute chronology is needed for individual sites and on a regional scale with a resolution that can differentiate events within a century. To realize this challenging goal, only samples from well-established primary contexts ought to be studied. Such primary contexts (with “dating assemblages”) can be identified by combining macroscopic with microscopic observations. Chronological studies at the sites of Qubur el-Walaydah, Tel es-Safi, and in particular, Megiddo, demonstrate that high-resolution dating can be achieved, with very few outliers in the data sets. The major limitation on applying this approach is the fact that we are currently constrained to dating short-lived samples (charred seeds and olive pits) and collagen from bones. Thus, an immediate goal of radiocarbon research is to develop the ability to date other short-lived materials, such as organic material occluded in siliceous plant phytoliths, wood ash, and possibly organic residues preserved in pottery vessels.

scholarly journals Deep-Down Time: Political Tradition in Central Africa

1989 ◽  
Vol 16 ◽  
pp. 341-362 ◽  
Author(s):  
Jan Vansina
Keyword(s):  
Political Ideology ◽  
Regional Scale ◽  
Central Africa ◽  
Common View ◽  
Historical Processes ◽  
The Social ◽  
The Common ◽  
Political Communities ◽  
The Mind ◽  
The Impact

Around 1850 the peoples of central Africa from Duala to the Kunene River and from the Atlantic to the Great Lakes shared a common view of the universe and a common political ideology. This included assumptions about roles, statuses, symbols, values, and indeed the very notion of legitimate authority. Among the plethora of symbols connected with these views were the leopard or the lion, the sun, the anvil, and the drum, symbolizing respectively the leader as predator, protector, forger of society, and the voice of all. Obviously, in each case the common political ideology was expressed in slightly different views, reflecting the impact of differential historical processes on different peoples. But the common core persisted. The gigantic extent of this phenomenon, encompassing an area equal to two-thirds of the continental United States, baffles the mind. How did it come about? Such a common tradition certainly did not arise independently in each of the hundreds of political communities that existed then. However absorbent and stable this mental political constellation was, it must have taken shape over a profound time depth. How and as a result of what did this happen? Is it even possible to answer such queries in a part of the world that did not generate written records until a few centuries ago or less?This paper addresses this question: how can one trace the social construction of such a common constellation over great time depths and over great regional scale? All the peoples involved are agriculturalists and the political repertory with which we are concerned could not easily exist in its known form outside sedentary societies.

scholarly journals Paired refinement under the control of PAIREF

IUCrJ ◽  
2020 ◽  
Vol 7 (4) ◽  
pp. 681-692
Author(s):  
Martin Malý ◽  
Kay Diederichs ◽  
Jan Dohnálek ◽  
Petr Kolenko
Keyword(s):  
High Resolution ◽  
Diffraction Data ◽  
Structure Refinement ◽  
Data Sets ◽  
High Resolution Data ◽  
Density Maps ◽  
New Feature ◽  
And Control ◽  
The Impact ◽  
Resolution Data

Crystallographic resolution is a key characteristic of diffraction data and represents one of the first decisions an experimenter has to make in data evaluation. Conservative approaches to the high-resolution cutoff determination are based on a number of criteria applied to the processed X-ray diffraction data only. However, high-resolution data that are weaker than arbitrary cutoffs can still result in the improvement of electron-density maps and refined structure models. Therefore, the impact of reflections from resolution shells higher than those previously used in conservative structure refinement should be analysed by the paired refinement protocol. For this purpose, a tool called PAIREF was developed to provide automation of this protocol. As a new feature, a complete cross-validation procedure has also been implemented. Here, the design, usage and control of the program are described, and its application is demonstrated on six data sets. The results prove that the inclusion of high-resolution data beyond the conventional criteria can lead to more accurate structure models.

scholarly journals The assessment of temperature and salinity sampling strategies in the Mediterranean Sea: idealized and real cases

Ocean Science ◽  
2006 ◽  
Vol 2 (2) ◽  
pp. 97-112 ◽  
Author(s):  
F. Raicich
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Regional Scale ◽  
Optimal Interpolation ◽  
Data Sets ◽  
Sampling Strategies ◽  
Argo Data ◽  
Basin Scale ◽  
The Mediterranean ◽  
The Impact

Abstract. Temperature and salinity sampling strategies are studied and compared by means of the Observing System Simulation Experiment technique in order to assess their usefulness for data assimilation in the framework of the Mediterranean Forecasting System. Their impact in a Mediterranean General Circulation Model is quantified in numerical twin experiments via bivariate data assimilation of temperature and salinity profiles in summer and winter conditions, using the optimal interpolation algorithm implemented in the System for Ocean Forecasting and Analysis. The data impact is quantified by the error reduction in the assimilation run relative to the free run. The sampling strategies studied here include various combinations of temperature and salinity profiles collected along Volunteer Observing Ship (VOS) tracks, by Mediterranean Multi-sensor Moored Arrays (M3A), a Glider and ARGO floating profilers. Idealized sampling strategies involving VOS data allow to recognize the impact of individual tracks. As a result, the most effective tracks are those crossing regions characterized by high mesoscale variability and the presence of frontal structures between water masses. Sampling strategies adopted in summer–autumn 2004 and winter 2005 are studied to assess the impact of VOS and ARGO data in real conditions. The combination of all available data allows to achieve up to 30% error reductions. ARGO data produce a small impact when alone, but represent the only continuous coverage of the basin and are useful as a complement to VOS data sets. Localized data sets, as those obtained by M3As and the Glider, seem to have an almost negligible impact in the basin-scale assessment, and are expected to be more effective at regional scale.

scholarly journals Radiocarbon Dating Shows an Early Appearance of Philistine Material Culture in Tell es-Safi/Gath, Philistia

Radiocarbon ◽  
2015 ◽  
Vol 57 (5) ◽  
pp. 825-850 ◽  
Author(s):  
Yotam Asscher ◽  
Dan Cabanes ◽  
Louise A Hitchcock ◽  
Aren M Maeir ◽  
Steve Weiner ◽  
...  
Keyword(s):  
Material Culture ◽  
Bronze Age ◽  
Iron Age ◽  
Cultural Change ◽  
Radiocarbon Dating ◽  
Integrative Approach ◽  
Southern Levant ◽  
13Th Century ◽  
12Th Century ◽  
Archaeological Artifacts

The Late Bronze Age to Iron Age transition in the coastal southern Levant involves a major cultural change, which is characterized, among other things, by the appearance of Philistine pottery locally produced in styles derived from outside the Levant. This transition in the coastal southern Levant is conventionally dated to the 12th century BC, based on historical and archaeological artifacts associated with the Philistine pottery. Radiocarbon dating can provide a more precise independent absolute chronology for this transition, but dating for the period under discussion is complicated by the wiggles and relatively flat slope in the calibration curve, which significantly reduce precision. An additional complication is that the stratigraphic record below and above the transition at this site, as well as at most other sites in the region, is far from complete. We thus used a variety of microarchaeological techniques to improve our understanding of the stratigraphy, and to ensure that the locations with datable short-lived materials were only derived from primary contexts, which could be related directly to the associated material culture. The 14C dates were modeled using Bayesian statistics that incorporate the stratigraphic information. Using this integrative approach, we date the appearance of the Philistine pottery in Tell es-Safi/Gath in the 13th century BC.

Quantification of Yield, Water, and Carbon budget at intra-field scale using the AgriCarbon-EO tool

2021 ◽  
Author(s):  
Ahmad Al Bitar ◽  
Taeken Wijmer ◽  
Ludovic Arnaud ◽  
Remy Fieuzal ◽  
Gaetan Pique ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Water Budget ◽  
Carbon Budget ◽  
Regional Scale ◽  
Remote Sensing Data ◽  
Crop Model ◽  
Transfer Model ◽  
Sensing Data ◽  
The Impact

<p>Achieving the United Nations Sustainable Development Goal 2 that addresses food security and sustainable agriculture requires the promotion of readily transferable and scalable agronomical solutions. The combination of high-resolution remote sensing data, field information, and physical models is identified as a robust way of answering this requirement.  Here, we present the AgriCarbon-EO tool, a decision support system that provides the yield, biomass, water and carbon budget components of agricultural fields at a 10m resolution and at a regional scale. The tool assimilates high resolution optical remote sensing data from Copernicus Sentinel-2 satellites into a  radiative transfer model and a crop model. First, the application of a spatial Bayesian retrieval approach to the PROSAIL radiative transfer model provides Leaf Area Index (LAI) with its associated uncertainty. Second, LAI is assimilated into the SAFYE-CO2 crop model using a temporal Bayesian retrieval that enables the calculation of the yield, biomass, carbon and water budgets components with their associated uncertainties. In addition to remote sensing data, input datasets of crop types, weather and soil data are used to constrain the system. The concise weather data is provided from local weather stations or weather forecasts and is used to force the crop model (SAFYE-CO2) dynamics. The soil data are used in two folds. First to better parametrize the soil emissions in the radiative model retrievals and second to parametrise the water infiltration in the soil module of the crop model. The AgriCarbon-EO tool has been optimized to enable the computation of the yield, carbon, and water budget at high spatial resolution (10m) and large scale (100km2). The model is applied over the South-West of France covered by 3 Sentinel-2 tiles for major crops (wheat, maize,  sunflower). The outputs are validated over experimental plots for biomass, yield, soil moisture, and CO2 fluxes located all in the South-West of France. The experimental sites include the FR-AUR and FR-LAM ICOS sites and 22 cropland fields (biomass sampling). The validation exercise is done for the 2017-2018 and 2019-2020 cultural years. We show the added value of the use of high resolution in driving the crop model to take into account the impact of complex processes that are embedded in the LAI signal like vegetation water stress, disease, and agricultural practices. We show that the system is capable of providing the yield, carbon, and water budget of major crops accurately.  At the regional scale, we give global estimates of the carbon budget, water needs, and yields per crop type. We present the impact of intra-plot heterogeneity in the estimation of yield and the annual carbon and water budget showing the added value for high-resolution intra-plot modeling.</p>

Impact of regional climate model input and soil map resolution on projected winter wheat production in SW Germany

2020 ◽  
Author(s):  
Sebastian Gayler ◽  
Rajina Bajracharya ◽  
Tobias Weber ◽  
Thilo Streck
Keyword(s):  
High Resolution ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Scale ◽  
Grid Cell ◽  
Small Scale ◽  
Climate Projections ◽  
Soil Map ◽  
Soil Information ◽  
The Impact

<p>Agricultural ecosystem models, driven by climate projections and fed with soil information and plausible management scenarios are frequently used tools to predict future developments in agricultural landscapes. On the regional scale, the required soil parameters must be derived from soil maps that are available in different spatial resolutions, ranging from grid cell sizes of 50 m up to 1 km and more. The typical spatial resolution of regional climate projections is currently around 12 km. Given the small-scale heterogeneity in soil properties, using the most accurate soil representation could be important for predictions of crop growth. However, simulations with very highly resolved soil data requires greater computing time and higher effort for data organization and storage. Moreover, the higher resolution may not necessarily lead to better simulations due to redundant information of the land surface and because the impact of climate forcing could dominate over the effect of soil variability. This leads to the question if the use of high-resolution soil data leads to significantly different predictions of future yields and grain protein trends compared to simulations in which soil data is adapted to the resolution of the climate input.</p><p>This study investigated the impact of weather and soil input on simulated crop growth in an intensively used agricultural region in Southwest Germany. For all areas classified as ‘arable land’ (CLC10), winter wheat growth was simulated over a 44-year period (2006 to 2050) using weather projections from three regional climate models and soil information at two spatial resolutions. The simulations were performed with the model system Expert-N 5.0, where the crop model Gecros was combined with the Richards equation and the CN turnover module of the model Daisy. Soil hydraulic parameters as well as initial values of soil organic matter pools were estimated from BK50 soil map information on soil texture and soil organic matter content, using pedo-transfer functions and SOM pool fractionation following Bruun and Jensen (2002). The coarser soil map is derived from BK50 soil map (50m x 50m) by selecting only the dominant soil type in a 12km × 12km grid to be representative for that grid cell. The crop model was calibrated with field data of crop phenology, leaf area, biomass, yield and crop nitrogen, which were collected at a research station within the study area between 2009 and 2018.</p><p>The predicted increase in temperatures during the growing season correlated with earlier maturity, lower yields and a higher grain protein content. The regional mean values varied by +/- 0.5 t/ha or +/-0.3 percentage points of protein content depending to the climate model used. On the regional scale, the simulated trends remained unchanged using high-resolution or coarse resolution soil data. However, there are strong differences in both the forecasted averages and the distribution of forecasts, as the coarser resolution captures neither the small-scale heterogeneity nor the average of the high-resolution results.</p>

The Impact of Site Sample Size on the Reconstruction of Culture Histories

2011 ◽  
Vol 76 (3) ◽  
pp. 547-572 ◽  
Author(s):  
Charles Perreault
Keyword(s):  
Simulated Data ◽  
Archaeological Sites ◽  
Cultural Tradition ◽  
Data Sets ◽  
Data Set ◽  
Rate Of Spread ◽  
Accuracy And Precision ◽  
Historical Processes ◽  
The Impact ◽  
Simulated Data Sets

I examine how our capacity to produce accurate culture-historical reconstructions changes as more archaeological sites are discovered, dated, and added to a data set. More precisely, I describe, using simulated data sets, how increases in the number of known sites impact the accuracy and precision of our estimations of (1) the earliest and (2) latest date of a cultural tradition, (3) the date and (4) magnitude of its peak popularity, as well as (5) its rate of spread and (6) disappearance in a population. I show that the accuracy and precision of inferences about these six historical processes are not affected in the same fashion by changes in the number of known sites. I also consider the impact of two simple taphonomic site destruction scenarios on the results. Overall, the results presented in this paper indicate that unless we are in possession of near-total samples of sites, and can be certain that there are no taphonomic biases in the universe of sites to be sampled, we will make inferences of varying precision and accuracy depending on the aspect of a cultural trait’s history in question.

Using high-resolution DEMs for debris flow detection based on topographic signatures: A case study in the Quebrada del Toro, NW Argentina

2020 ◽  
Author(s):  
Ariane Mueting ◽  
Bodo Bookhagen ◽  
Manfred R. Strecker
Keyword(s):  
High Resolution ◽  
Debris Flow ◽  
Spatial Resolution ◽  
Debris Flows ◽  
Regional Scale ◽  
High Elevation ◽  
Transport Processes ◽  
Drainage Area ◽  
Sparse Vegetation ◽  
The Impact

<p>Mountainous high-relief terrains in climatically sensitive regions are often subjected to natural extreme events such as debris flows and landsliding. With people and infrastructure at risk, it is important to identify, measure, and comprehend the driving forces and mechanisms of slope movements in these environments at regional scale. Geomorphologic analyses and hazard assessments in these regions are, however, often limited by the availability of good-quality high-resolution digital elevation models (DEMs). Publically available data often have lower spatial resolution and are distorted in high-relief areas. In contrast, airplane-based lidar (light detection and ranging) data provide highly accurate information on 3D structure, yet, acquisition is costly and limits the size of the respective study area. Finding adequate, economical alternatives for creating high-resolution DEMs is therefore essential to study Earth-surface processes at regional scale, which may enable the detection of spatial variations, clusters and trends.</p><p>In areas with sparse vegetation, stereogrammetry has proven to be a viable tool for creating high-resolution DEMs. Here, we use SPOT-7 tri-stereo satellite imagery to create DEMs at 3 m spatial resolution for the Quebrada del Toro (QdT) in the Eastern Cordillera of NW Argentine Andes, an area with extreme gradients in topography, rainfall and erosion. Over 5000 GPS points collected during fieldwork ensure the spatial coherence of our DEMs.</p><p>Field observations in this high-elevation area show that the hillslopes of the deeply incised QdT gorge are characterized by debris flow deposits of various extent. Debris flows have a specific slope-drainage area relationship that curves in log-log space. Using high-resolution topographic data, we are able to provide further evidence for this phenomenon and characterize the distinct topographic signature of debris flows. We specifically focus on the transition zone between debris-flow and fluvial processes, which is variable in the different catchments. The transition is characterized by a pronounced kink revealed in slope-drainage plots, as well as an increase of slope scatter in the drainage area logbins. We propose that the presence and location of this kink reflects the nature of the dominating transport processes in the corresponding catchments. In light of these observations we discriminate between debris-flow and fluvially dominated catchments in the QdT and identify regions that primarily exhibit slope movement. Our new results reveal a cluster of fluvial catchments to the SE of our study area – an area that receives significantly more moisture than upstream regions. In contrast, debris flows are prominent in areas of sparse vegetation, where occasional extreme rainfall events are efficient in transporting large amounts of talus downhill. These observations are key to a better understanding of the relationships between the impact of extreme rainfalls at high elevation and the formation of large volumes of sediment in the arid highlands of the Andes.</p>

scholarly journals Improved retrieval of global tropospheric formaldehyde columns from GOME-2/MetOp-A addressing noise reduction and instrumental degradation issues

2012 ◽  
Vol 5 (4) ◽  
pp. 5571-5616 ◽  
Author(s):  
I. De Smedt ◽  
M. Van Roozendael ◽  
T. Stavrakou ◽  
J.-F. Müller ◽  
C. Lerot ◽  
...  
Keyword(s):  
A Priori ◽  
Regional Scale ◽  
Data Sets ◽  
Data Set ◽  
Cloud Parameters ◽  
Fitting Procedure ◽  
Retrieval Scheme ◽  
Gaussian Line Shape ◽  
Regression Slopes ◽  
The Impact

Abstract. We present a new data set of formaldehyde vertical columns retrieved from observations of GOME-2 onboard of the EUMETSAT MetOp-A platform between 2007 and 2011. The new retrieval scheme, which has been optimised for GOME-2, includes a two-step fitting procedure that strongly reduces the impact of spectral interferences between H2CO and BrO, and a modified DOAS approach that better handles ozone absorption effects at moderately low sun elevations. Owing to these new features, the noise in the H2CO slant columns is reduced by up to 40% in comparison to baseline retrieval settings used operationally. Also, the previously reported underestimation of the H2CO columns in tropical and mid-latitudes regions has been largely eliminated, improving the agreement with coincident SCIAMACHY observations. To compensate for the drift of the GOME-2 slit function and to mitigate the instrumental degradation effects on H2CO retrievals, an asymmetric Gaussian line shape is fitted during the irradiance calibration. Additionally, external parameters used in the tropospheric air mass factor computation (surface reflectances, cloud parameters and a priori profile shapes of H2CO) have been updated using most recent data bases. Similar updates were also applied to the historical data sets of GOME and SCIAMACHY leading to the generation of a consistent multi-mission H2CO data record covering the time period from 1997 until 2011. Comparing the resulting time series of monthly averaged H2CO vertical columns in 12 large regions worldwide, the correlation coefficient between SCIAMACHY and GOME-2 columns is generally higher than 0.8 in the overlap period, and linear regression slopes differ by less than 10% from unity in most of the regions. In comparison to SCIAMACHY, the largely improved spatial sampling of GOME-2 allows for a better characterisation of formaldehyde distribution at the regional scale and/or at shorter timescales, leading to a better identification of the emission sources of non-methane volatile organic compounds.

Comparison of MK-PRISM according to horizontal resolution in South Korea

2020 ◽  
Author(s):  
Maeng-Ki Kim ◽  
Jeong Sang ◽  
Ji-hyun Yun ◽  
Ji-Seon Oh
Keyword(s):  
High Resolution ◽  
Group Performance ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Data Sets ◽  
Grid Data ◽  
The Impact ◽  
Resolution Data

<p>In this study, we produced grid climate data sets of 1km×1km and 5km×5km horizontal resolutions based on MK (Modified Korean)-PRISM (Parameter-elevation Regressions on Independent Slopes Model), a statistical method that can estimate grid data of horizontal high-resolution using observational station data in Korea. To compare the MK-PRISM performance according to resolution, RMSEs of 1km resolution data and 5km resolution data were calculated and analyzed. The RMSEs of the two data sets were similar, but the results classified according to the elevation were different. The 1km high resolution estimated data was shown to better reflect the impact of the terrain for the daily mean temperature and daily maximum temperature, whereas the difference between the two data sets for daily minimum temperature was not statistically significant at each elevation. Furthermore, we also divided the temperature data into 9-classes based on the observed temperatures, and then compared the estimated performance of the two data sets according to elevation. For the low temperature group, performance of the 1 km resolution data at high elevations outperformed that of the 5 km resolution data, regardless of the season. In addition, we have verified the improved PRIDE (PRism based Dynamic downscaling Error correction) model, which can produce future high-resolution scenarios data using the results of RCM and MK-PRISM.</p>

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