Correlations et interpretations genetiques dans les formations recifales oxfordiennes de la haute vallee de l'Yonne (sud-est du bassin de Paris, France)

2001 ◽  
Vol 172 (1) ◽  
pp. 69-84 ◽  
Author(s):  
Francis Chevalier ◽  
Jean-Pierre Garcia ◽  
Didier Quesne ◽  
Michel Guiraud ◽  
Jean-Claude Menot
Keyword(s):  
High Resolution ◽  
Environmental Conditions ◽  
Local Scale ◽  
Depositional Environments ◽  
Genetic Sequence ◽  
Tectonic Control ◽  
Genetic Stratigraphy

Abstract Novel palaeoenvironmental interpretations and high-resolution correlations in Oxfordian reefal formations (fig. 1, 2) are provided by genetic stratigraphy. The main objectives of this study are: (1) to determine environmental conditions and the zonation of depositional environments; (2) to propose a genetic sequence framework and correlations of the outcrop sections; (3) to evaluate a possible tectonic control on coral buildup settlement and growth both at local scale.

COMBINED HRLEED AND STM INVESTIGATIONS ON THE INITIAL STAGES OF Cu HETEROEPITAXY Ru(0001)

1997 ◽  
Vol 04 (06) ◽  
pp. 1167-1171 ◽  
Author(s):  
CH. AMMER ◽  
K. MEINEL ◽  
H. WOLTER ◽  
A. BECKMANN ◽  
H. NEDDERMEYER
Keyword(s):  
High Resolution ◽  
Electron Diffraction ◽  
Strain Relaxation ◽  
Local Scale ◽  
Low Energy ◽  
Scanning Tunneling ◽  
Tunneling Microscopy ◽  
Low Energy Electron Diffraction ◽  
Layer Structures ◽  
Low Energy Electron

Recent scanning tunneling microscopy (STM) observations revealed different layer structures in the heteroepitaxial Cu/Ru(0001) system with increasing film thickness attributed to various stages of strain relaxation. High-resolution low-energy electron diffraction (HRLEED) analysis permits one to derive more exactly both lattice periodicities and lattice rotations. Furthermore, the representative character of local STM results can be proved. However, STM measurements are needed to identify and to assign the satellite spots to coexistent different superstructures which are superposed incoherently in the diffraction pattern. Generally, the integral LEED results confirm the crystallographic data obtained by STM in a local scale.

scholarly journals A high resolution multimedia environmental monitoring project at regional and local scale: the Campania region (southern Italy) case study

2021 ◽  
Author(s):  
Benedetto De Vivo ◽  
Stefano Albanese ◽  
Annamaria Lima ◽  
Domenico Cicchella ◽  
David Hope ◽  
...  
Keyword(s):  
High Resolution ◽  
Environmental Monitoring ◽  
Southern Italy ◽  
Local Scale ◽  
Campania Region

scholarly journals Large-scale atmospheric forcing and topographic modification of precipitation rates over High Asia – a neural-network-based approach

2015 ◽  
Vol 6 (1) ◽  
pp. 61-81 ◽  
Author(s):  
L. Gerlitz ◽  
O. Conrad ◽  
J. Böhner
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Spatial Resolution ◽  
Large Scale ◽  
Local Scale ◽  
Predictor Variables ◽  
High Mountain ◽  
Target Area ◽  
Monthly Precipitation ◽  
Highly Nonlinear

Abstract. The heterogeneity of precipitation rates in high-mountain regions is not sufficiently captured by state-of-the-art climate reanalysis products due to their limited spatial resolution. Thus there exists a large gap between the available data sets and the demands of climate impact studies. The presented approach aims to generate spatially high resolution precipitation fields for a target area in central Asia, covering the Tibetan Plateau and the adjacent mountain ranges and lowlands. Based on the assumption that observed local-scale precipitation amounts are triggered by varying large-scale atmospheric situations and modified by local-scale topographic characteristics, the statistical downscaling approach estimates local-scale precipitation rates as a function of large-scale atmospheric conditions, derived from the ERA-Interim reanalysis and high-resolution terrain parameters. Since the relationships of the predictor variables with local-scale observations are rather unknown and highly nonlinear, an artificial neural network (ANN) was utilized for the development of adequate transfer functions. Different ANN architectures were evaluated with regard to their predictive performance. The final downscaling model was used for the cellwise estimation of monthly precipitation sums, the number of rainy days and the maximum daily precipitation amount with a spatial resolution of 1 km2. The model was found to sufficiently capture the temporal and spatial variations in precipitation rates in the highly structured target area and allows for a detailed analysis of the precipitation distribution. A concluding sensitivity analysis of the ANN model reveals the effect of the atmospheric and topographic predictor variables on the precipitation estimations in the climatically diverse subregions.

scholarly journals Analysis of High-Resolution QTL Markers Associated with Rice Yields Using Data for Two Consecutive Years in Different Environmental Conditions

2014 ◽  
Vol 06 (11) ◽  
pp. 818-827 ◽  
Author(s):  
Ye-Jin Son ◽  
Gyu-Ho Lee ◽  
Hyun-Suk Lee ◽  
Tri Handoyo ◽  
Byung-Wook Yun ◽  
...  
Keyword(s):  
High Resolution ◽  
Environmental Conditions ◽  
Rice Yields ◽  
Using Data

Generating long-term high-resolution land-use change datasets for regional climate modeling in CORDEX domains

2021 ◽  
Author(s):  
Peter Hoffmann ◽  
Diana Rechid ◽  
Vanessa Reinhart ◽  
Christina Asmus ◽  
Edouard L. Davin ◽  
...  
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Land Use Change ◽  
Land Cover ◽  
Climate Modeling ◽  
Regional Climate ◽  
Regional Climate Modeling ◽  
Local Scale ◽  
Modeling Studies

<p>Land-use and land cover (LULC) are continuously changing due to environmental changes and anthropogenic activities. Many observational and modeling studies show that LULC changes are important drivers altering land surface feedbacks and land-atmosphere exchange processes that have substantial impact on climate on the regional and local scale. Yet, most long-term regional climate modeling studies do not account for these changes. Therefore, within the WCRP CORDEX Flagship Pilot Study LUCAS (Land Use Change Across Scales) a new workflow was developed to generate high-resolution annual land cover change time series based on past reconstructions and future projections. First, the high-resolution global land cover dataset ESA-CCI LC (~300 m resolution) is aggregated and converted to a 0.1° resolution, fractional plant functional type (PFT) dataset. Second, the land use change information from the land-use harmonized dataset (LUH2), provided at 0.25° resolution as input for CMIP6 experiments, is translated into PFT changes employing a newly developed land use translator (LUT). The new LUT was first applied to the EURO-CORDEX domain. The resulting LULC maps for past and future - the LUCAS LUC dataset - can be applied as land use forcing to the next generation RCM simulations for downscaling CMIP6 by the EURO-CORDEX community and in the framework of FPS LUCAS. The dataset includes land cover and land management practices changes important for the regional and local scale such as urbanization and irrigation. The LUCAS LUC workflow is applied to further CORDEX domains, such as Australasia and North America. The resulting past and future land cover changes will be presented, and challenges regarding the application of the new workflow to different regions will be addressed. In addition, issues related to the implementation of the dataset into different RCMs will be discussed.</p>

scholarly journals Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France

2016 ◽  
Vol 12 (3) ◽  
pp. 635-662 ◽  
Author(s):  
Laurie Caillouet ◽  
Jean-Philippe Vidal ◽  
Eric Sauquet ◽  
Benjamin Graff
Keyword(s):  
Climate Change ◽  
Twentieth Century ◽  
High Resolution ◽  
Large Scale ◽  
Local Scale ◽  
Precipitation Forecast ◽  
Seasonal Temperature ◽  
Downscaling Method ◽  
Quantitative Precipitation Forecast ◽  
Precipitation And Temperature

Abstract. This work proposes a daily high-resolution probabilistic reconstruction of precipitation and temperature fields in France over the 1871–2012 period built on the NOAA Twentieth Century global extended atmospheric reanalysis (20CR). The objective is to fill in the spatial and temporal data gaps in surface observations in order to improve our knowledge on the local-scale climate variability from the late nineteenth century onwards. The SANDHY (Stepwise ANalogue Downscaling method for HYdrology) statistical downscaling method, initially developed for quantitative precipitation forecast, is used here to bridge the scale gap between large-scale 20CR predictors and local-scale predictands from the Safran high-resolution near-surface reanalysis, available from 1958 onwards only. SANDHY provides a daily ensemble of 125 analogue dates over the 1871–2012 period for 608 climatically homogeneous zones paving France. Large precipitation biases in intermediary seasons are shown to occur in regions with high seasonal asymmetry like the Mediterranean. Moreover, winter and summer temperatures are respectively over- and under-estimated over the whole of France. Two analogue subselection methods are therefore developed with the aim of keeping the structure of the SANDHY method unchanged while reducing those seasonal biases. The calendar selection keeps the analogues closest to the target calendar day. The stepwise selection applies two new analogy steps based on similarity of the sea surface temperature (SST) and the large-scale 2 m temperature (T). Comparisons to the Safran reanalysis over 1959–2007 and to homogenized series over the whole twentieth century show that biases in the interannual cycle of precipitation and temperature are reduced with both methods. The stepwise subselection moreover leads to a large improvement of interannual correlation and reduction of errors in seasonal temperature time series. When the calendar subselection is an easily applicable method suitable in a quantitative precipitation forecast context, the stepwise subselection method allows for potential season shifts and SST trends and is therefore better suited for climate reconstructions and climate change studies. The probabilistic downscaling of 20CR over the period 1871–2012 with the SANDHY probabilistic downscaling method combined with the stepwise subselection thus constitutes a perfect framework for assessing the recent observed meteorological events but also future events projected by climate change impact studies and putting them in a historical perspective.

scholarly journals Mesoscale and Local Scale Evaluations of Quantitative Precipitation Estimates by Weather Radar Products during a Heavy Rainfall Event

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Basile Pauthier ◽  
Benjamin Bois ◽  
Thierry Castel ◽  
D. Thévenin ◽  
Carmela Chateau Smith ◽  
...  
Keyword(s):  
High Resolution ◽  
Heavy Rainfall ◽  
Rain Gauge ◽  
Local Scale ◽  
Rainfall Event ◽  
Heavy Rainfall Event ◽  
Preliminary Evaluation ◽  
Rainfall Variation ◽  
Hourly Rainfall ◽  
Rain Gauge Network

A 24-hour heavy rainfall event occurred in northeastern France from November 3 to 4, 2014. The accuracy of the quantitative precipitation estimation (QPE) by PANTHERE and ANTILOPE radar-based gridded products during this particular event, is examined at both mesoscale and local scale, in comparison with two reference rain-gauge networks. Mesoscale accuracy was assessed for the total rainfall accumulated during the 24-hour event, using the Météo France operational rain-gauge network. Local scale accuracy was assessed for both total event rainfall and hourly rainfall accumulations, using the recently developed HydraVitis high-resolution rain gauge network Evaluation shows that (1) PANTHERE radar-based QPE underestimates rainfall fields at mesoscale and local scale; (2) both PANTHERE and ANTILOPE successfully reproduced the spatial variability of rainfall at local scale; (3) PANTHERE underestimates can be significantly improved at local scale by merging these data with rain gauge data interpolation (i.e., ANTILOPE). This study provides a preliminary evaluation of radar-based QPE at local scale, suggesting that merged products are invaluable for applications at very high resolution. The results obtained underline the importance of using high-density rain-gauge networks to obtain information at high spatial and temporal resolution, for better understanding of local rainfall variation, to calibrate remotely sensed rainfall products.

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