scholarly journals Par@Graph – a parallel toolbox for the construction and analysis of large complex climate networks

2015 ◽  
Vol 8 (1) ◽  
pp. 319-349 ◽  
Author(s):  
H. Ihshaish ◽  
A. Tantet ◽  
J. C. M. Dijkzeul ◽  
H. A. Dijkstra
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Network Analysis ◽  
Large Scale ◽  
Ocean Model ◽  
Clustering Coefficient ◽  
Connected Components ◽  
Eigenvector Centrality ◽  
Key Innovation ◽  
Climate Networks

Abstract. In this paper, we present Par@Graph, a software toolbox to reconstruct and analyze complex climate networks having a large number of nodes (up to at least O (106)) and of edges (up to at least O (1012)). The key innovation is an efficient set of parallel software tools designed to leverage the inherited hybrid parallelism in distributed-memory clusters of multi-core machines. The performance of the toolbox is illustrated through networks derived from sea surface height (SSH) data of a global high-resolution ocean model. Less than 8 min are needed on 90 Intel Xeon E5-4650 processors to construct a climate network including the preprocessing and the correlation of 3 × 105 SSH time series, resulting in a weighted graph with the same number of vertices and about 3 × 106 edges. In less than 5 min on 30 processors, the resulted graph's degree centrality, strength, connected components, eigenvector centrality, entropy and clustering coefficient metrics were obtained. These results indicate that a complete cycle to construct and analyze a large-scale climate network is available under 13 min. Par@Graph therefore facilitates the application of climate network analysis on high-resolution observations and model results, by enabling fast network construction from the calculation of statistical similarities between climate time series. It also enables network analysis at unprecedented scales on a variety of different sizes of input data sets.

scholarly journals Par@Graph – a parallel toolbox for the construction and analysis of large complex climate networks

2015 ◽  
Vol 8 (10) ◽  
pp. 3321-3331 ◽  
Author(s):  
H. Ihshaish ◽  
A. Tantet ◽  
J. C. M. Dijkzeul ◽  
H. A. Dijkstra
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Network Analysis ◽  
Large Scale ◽  
Ocean Model ◽  
Clustering Coefficient ◽  
Connected Components ◽  
Eigenvector Centrality ◽  
Key Innovation ◽  
Climate Networks

Abstract. In this paper, we present Par@Graph, a software toolbox to reconstruct and analyze complex climate networks having a large number of nodes (up to at least 106) and edges (up to at least 1012). The key innovation is an efficient set of parallel software tools designed to leverage the inherited hybrid parallelism in distributed-memory clusters of multi-core machines. The performance of the toolbox is illustrated through networks derived from sea surface height (SSH) data of a global high-resolution ocean model. Less than 8 min are needed on 90 Intel Xeon E5-4650 processors to reconstruct a climate network including the preprocessing and the correlation of 3 × 105 SSH time series, resulting in a weighted graph with the same number of vertices and about 3.2 × 108 edges. In less than 14 min on 30 processors, the resulted graph's degree centrality, strength, connected components, eigenvector centrality, entropy and clustering coefficient metrics were obtained. These results indicate that a complete cycle to construct and analyze a large-scale climate network is available under 22 min Par@Graph therefore facilitates the application of climate network analysis on high-resolution observations and model results, by enabling fast network reconstruct from the calculation of statistical similarities between climate time series. It also enables network analysis at unprecedented scales on a variety of different sizes of input data sets.

scholarly journals Estimating mass-wasting processes in active earth slides – earth flows with time-series of High-Resolution DEMs from photogrammetry and airborne LiDAR

2009 ◽  
Vol 9 (2) ◽  
pp. 433-439 ◽  
Author(s):  
A. Corsini ◽  
L. Borgatti ◽  
F. Cervi ◽  
A. Dahne ◽  
F. Ronchetti ◽  
...  
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Large Scale ◽  
Airborne Lidar ◽  
Mitigation Measures ◽  
Mass Wasting ◽  
Aerial Photos ◽  
Use Of Time ◽  
Elevation Changes ◽  
Earth Flows

Abstract. This paper deals with the use of time-series of High-Resolution Digital Elevation Models (HR DEMs) obtained from photogrammetry and airborne LiDAR coupled with aerial photos, to analyse the magnitude of recently reactivated large scale earth slides – earth flows located in the northern Apennines of Italy. The landslides underwent complete reactivation between 2001 and 2006, causing civil protection emergencies. With the final aim to support hazard assessment and the planning of mitigation measures, high-resolution DEMs are used to identify, quantify and visualize depletion and accumulation in the slope resulting from the reactivation of the mass movements. This information allows to quantify mass wasting, i.e. the amount of landslide material that is wasted during reactivation events due to stream erosion along the slope and at its bottom, resulting in sediment discharge into the local fluvial system, and to assess the total volumetric magnitude of the events. By quantifying and visualising elevation changes at the slope scale, results are also a valuable support for the comprehension of geomorphological processes acting behind the evolution of the analysed landslides.

scholarly journals Identification of Droughts and Heat Waves in Germany with Regional Climate Networks

2020 ◽  
Author(s):  
Gerd Schädler ◽  
Marcus Breil
Keyword(s):  
Time Series ◽  
Extreme Events ◽  
Heat Waves ◽  
Regional Climate ◽  
Clustering Coefficient ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Published Data ◽  
Data Set ◽  
Climate Networks

Abstract. Regional Climate Networks (RCNs) are used to identify heat waves and droughts in Germany and two subregions for the summer half years resp. summer seasons of the period 1951 to 2019. RCNs provide information for whole areas (in contrast to the point-wise information from standard indices), the underlying nodes can be distributed arbitrarily, they are easy to 5 construct and provide details otherwise difficult to avail of like extent, intensity and collective behaviour of extreme events. The RCNs were constructed on the regular 0.25 degree grid of the E-Obs data set. The season-wise correlation of time series of daily maximum temperature Tmax and precipitation were used to construct the adjacency matrix of the networks. Metrics to identify extremes were the edge density, the 90th percentile of the correlations and the average clustering coefficient, which turned out to be highly correlated; they increased considerably during extreme events. The standard indices for comparison 10 were the effective drought and heat index (EDI and EHI) respectively, based on the same time series, and complemented by other published data. Our results show that the RCNs are able to identify severe extremes in all cases and moderate extremes in most cases. An interesting finding is that during average years, the distribution of the node degrees is close to the Poisson distribution, characteristic of random networks, while for extreme years the distribution is more uniform and heavy tailed.

scholarly journals Automated High-Resolution Time Series Mapping of Mangrove Forests Damaged by Hurricane Irma in Southwest Florida

2020 ◽  
Vol 12 (11) ◽  
pp. 1740
Author(s):  
Matthew J. McCarthy ◽  
Brita Jessen ◽  
Michael J. Barry ◽  
Marissa Figueroa ◽  
Jessica McIntosh ◽  
...  
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Land Cover ◽  
Satellite Imagery ◽  
Large Scale ◽  
Detection Methods ◽  
Mangrove Forests ◽  
Wetland Ecosystems ◽  
Southwest Florida ◽  
Hurricane Irma

In September of 2017, Hurricane Irma made landfall within the Rookery Bay National Estuarine Research Reserve of southwest Florida (USA) as a category 3 storm with winds in excess of 200 km h−1. We mapped the extent of the hurricane’s impact on coastal land cover with a seasonal time series of satellite imagery. Very high-resolution (i.e., <5 m pixel) satellite imagery has proven effective to map wetland ecosystems, but challenges in data acquisition and storage, algorithm training, and image processing have prevented large-scale and time-series mapping of these data. We describe our approach to address these issues to evaluate Rookery Bay ecosystem damage and recovery using 91 WorldView-2 satellite images collected between 2010 and 2018 mapped using automated techniques and validated with a field campaign. Land cover was classified seasonally at 2 m resolution (i.e., healthy mangrove, degraded mangrove, upland, soil, and water) with an overall accuracy of 82%. Digital change detection methods show that hurricane-related degradation was 17% of mangrove forest (~5 km2). Approximately 35% (1.7 km2) of this loss recovered one year after Hurricane Irma. The approach completed the mapping approximately 200 times faster than existing methods, illustrating the ease with which regional high-resolution mapping may be accomplished efficiently.

scholarly journals A New Statistical–Dynamical Downscaling Procedure Based on EOF Analysis for Regional Time Series Generation

2013 ◽  
Vol 52 (4) ◽  
pp. 935-952 ◽  
Author(s):  
Yosvany Martinez ◽  
Wei Yu ◽  
Hai Lin
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Large Scale ◽  
Dynamical Downscaling ◽  
Resource Assessment ◽  
Computational Effort ◽  
Limited Area ◽  
Eof Analysis ◽  
Large Scale Data ◽  
Wind Resource

AbstractA new statistical–dynamical downscaling procedure is developed and then applied to high-resolution (regional) time series generation and wind resource assessment. The statistical module of the new procedure uses empirical orthogonal function (EOF) analysis for the generation of large-scale atmospheric component patterns. The dominant atmospheric patterns (associated with the EOF modes explaining most of the statistical variance) are then dynamically downscaled or adjusted to high-resolution terrain and surface roughness by using the Global Environmental Multiscale–Limited Area Model (GEM-LAM). Regional time series are constructed using the model outputs. The new method is applied to the Gaspé region of Québec in Canada. The dataset used is the NCEP–NCAR reanalysis of wind, temperature, humidity, and geopotential height during the period 1958–2004. Regional time series of wind speed and temperature are constructed, and a numerical wind atlas of the Gaspé region is generated. The generated time series and the numerical wind atlas are compared with observations at different masts located in the Gaspé Peninsula and are also compared with a numerical wind atlas for the same region generated in Yu et al. The results suggest that the newly developed procedure can be useful to generate regional time series and reasonably accurate numerical wind atlases using large-scale data with much less computational effort than previous techniques.

scholarly journals CHARACTERISTICS OF TEXTURE INDEX OF DAMAGED BUILDINGS USING TIME-SERIES HIGH-RESOLUTION OPTICAL SATELLITE IMAGES

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1709-1714
Author(s):  
M. Sonobe
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Texture Analysis ◽  
Large Scale ◽  
Satellite Images ◽  
Image Interpretation ◽  
High Resolution Satellite Images ◽  
Survey Results ◽  
Occurrence Matrix ◽  
Optical Satellite Images

Abstract. A large-scale disaster has occurred due to the earthquake. In particular, 20% of the world's earthquakes with a magnitude of 6 or more occur near Japan. Damage analysis of buildings by image analysis have been effectively carried out using optical high-resolution satellite images and aerial photograph with spatial resolution of about 2 m or less. In this study, the damaged buildings caused by large-scale and continuous earthquakes in Kumamoto, Japan that occurred in April 2016 was selected as a typical example of damaged buildings. For these earthquake event, the applicability of damage distribution of buildings and recovery/restoration status by texture analysis was examined. The applicability of the representative in the dissimilarity texture analysis methods Gray- Level Co-occurrence Matrix (GLCM) method by image interpretation in the case of a large number of collapsed and wrecked buildings in a wide area was assessed. These results suggest that dissimilarity was applicable to the extraction of damaged and removed buildings in the event of such an earthquake. In addition, the analysis results were appropriately evaluated by comparing the field survey results with the image interpretation results of the pan-sharpened image. From these results, we confirmed the effectiveness of texture analysis using time-series high-resolution satellite images in grasping the damaged buildings before and immediately after the disaster and in the restoration situation 1 year after the disaster.

scholarly journals Relating Agulhas leakage to the Agulhas Current retroflection location

Ocean Science ◽  
2009 ◽  
Vol 5 (4) ◽  
pp. 511-521 ◽  
Author(s):  
E. van Sebille ◽  
C. N. Barron ◽  
A. Biastoch ◽  
P. J. van Leeuwen ◽  
F. C. Vossepoel ◽  
...  
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Atlantic Ocean ◽  
Ocean Model ◽  
Altimetry Data ◽  
Agulhas Current ◽  
Numerical Ocean Model ◽  
The Indian Ocean ◽  
The Mean ◽  
Annual Time

Abstract. The relation between the Agulhas Current retroflection location and the magnitude of Agulhas leakage, the transport of water from the Indian to the Atlantic Ocean, is investigated in a high-resolution numerical ocean model. Sudden eastward retreats of the Agulhas Current retroflection loop are linearly related to the shedding of Agulhas rings, where larger retreats generate larger rings. Using numerical Lagrangian floats a 37 year time series of the magnitude of Agulhas leakage in the model is constructed. The time series exhibits large amounts of variability, both on weekly and annual time scales. A linear relation is found between the magnitude of Agulhas leakage and the location of the Agulhas Current retroflection, both binned to three month averages. In the relation, a more westward location of the Agulhas Current retroflection corresponds to an increased transport from the Indian Ocean to the Atlantic Ocean. When this relation is used in a linear regression and applied to almost 20 years of altimetry data, it yields a best estimate of the mean magnitude of Agulhas leakage of 13.2 Sv. The early retroflection of 2000, when Agulhas leakage was probably halved, can be identified using the regression.

scholarly journals Relating Agulhas leakage to the Agulhas Current retroflection location

2009 ◽  
Vol 6 (2) ◽  
pp. 1193-1221 ◽  
Author(s):  
E. van Sebille ◽  
C. N. Barron ◽  
A. Biastoch ◽  
P. J. van Leeuwen ◽  
F. C. Vossepoel ◽  
...  
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Atlantic Ocean ◽  
Ocean Model ◽  
Altimetry Data ◽  
Agulhas Current ◽  
Numerical Ocean Model ◽  
The Indian Ocean ◽  
The Mean ◽  
Annual Time

Abstract. The relation between the Agulhas Current retroflection location and the magnitude of Agulhas leakage, the transport of water from the Indian to the Atlantic Ocean, is investigated in a high-resolution numerical ocean model. Sudden eastward retreats of the Agulhas Current retroflection loop are linearly related to the shedding of Agulhas rings, where larger retreats generate larger rings. Using numerical Lagrangian floats a 37 year time series of the magnitude of Agulhas leakage in the model is constructed. The time series exhibits large amounts of variability, both on weekly and annual time scales. A linear relation is found between the magnitude of Agulhas leakage and the location of the Agulhas Current retroflection, both binned to three month averages. In the relation, a more westward location of the Agulhas Current retroflection corresponds to an increased transport from the Indian Ocean to the Atlantic Ocean. When this relation is used in a linear regression and applied to almost 20 years of altimetry data, it yields a best estimate of the mean magnitude of Agulhas leakage of 13.2 Sv. The early retroflection of 2000, when Agulhas leakage was probably halved, can be identified using the regression.

scholarly journals An observed 20-year time series of Agulhas leakage

Ocean Science ◽  
2014 ◽  
Vol 10 (4) ◽  
pp. 601-609 ◽  
Author(s):  
D. Le Bars ◽  
J. V. Durgadoo ◽  
H. A. Dijkstra ◽  
A. Biastoch ◽  
W. P. M. De Ruijter
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Ocean Model ◽  
Dynamic Topography ◽  
Return Current ◽  
Major Barrier ◽  
Agulhas Current ◽  
The Mean ◽  
The Difference ◽  
Geostrophic Velocities

Abstract. We provide a time series of Agulhas leakage anomalies over the last 20-years from satellite altimetry. Until now, measuring the interannual variability of Indo-Atlantic exchange has been the major barrier in the investigation of the dynamics and large scale impact of Agulhas leakage. We compute the difference of transport between the Agulhas Current and Agulhas Return Current, which allows us to deduce Agulhas leakage. The main difficulty is to separate the Agulhas Return Current from the southern limb of the subtropical "supergyre" south of Africa. For this purpose, an algorithm that uses absolute dynamic topography data is developed. The algorithm is applied to a state-of-the-art ocean model. The comparison with a Lagrangian method to measure the leakage allows us to validate the new method. An important result is that it is possible to measure Agulhas leakage in this model using the velocity field along a section that crosses both the Agulhas Current and the Agulhas Return Current. In the model a good correlation is found between measuring leakage using the full depth velocities and using only the surface geostrophic velocities. This allows us to extend the method to along-track absolute dynamic topography from satellites. It is shown that the accuracy of the mean dynamic topography does not allow us to determine the mean leakage but that leakage anomalies can be accurately computed.

Numerical Investigation of the Middle Atlantic Bight Shelfbreak Frontal Circulation Using a High-Resolution Ocean Hindcast Model

2010 ◽  
Vol 40 (5) ◽  
pp. 949-964 ◽  
Author(s):  
Ke Chen ◽  
Ruoying He
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Circulation Model ◽  
Ocean Model ◽  
Salt Flux ◽  
Open Boundary ◽  
Middle Atlantic Bight ◽  
Middle Atlantic ◽  
Eddy Heat Flux ◽  
The Mean

Abstract A nested high-resolution ocean model is used to hindcast the Middle Atlantic Bight (MAB) shelfbreak circulation from December 2003 to June 2008. The model is driven by tidal harmonics, realistic atmospheric forcing, and dynamically consistent initial and open boundary conditions obtained from a large-scale circulation model. Simulated shelfbreak sea levels and tracer fields compare favorably with satellite observations and available in situ hydrographic climatology, demonstrating the utility of this nested ocean model for resolving the MAB shelfbreak circulation. The resulting time and space continuous hindcast solutions between January 2004 and December 2007 are used to describe the mean structures and temporal variations of the shelfbreak front and jet, the bottom boundary layer detachment, and the migration of the shelfbreak front. It is found that the shelfbreak jet and boundary convergence reach their maximum intensities in the spring, at which time the foot of the front also migrates to its farthest offshore position. Vorticity analyses reveal that the magnitude ratio of the mean relative vorticity between the seaward and the shoreward portions of the shelfbreak front is about 2:1. The shelfbreak ageostrophic circulation is largely controlled by the viscosity in the boundary layers and by the nonlinear advection in the flow interior. Simulated three-dimensional velocity and tracer fields are used to estimate the transport and heat and salt fluxes across the 200-m isobath. Within the model domain, the total cross-shelf water transport, the total eddy heat flux, and the total eddy salt flux are 0.035 ± 0.26 Sv (1 Sv ≡ 106 m3 s−1), 1.0 × 103 ± 4 × 104 W m−2, and 6.7 × 10−5 ± 7.0 × 10−4 kg m−2 s−1. The empirical orthogonal function (EOF) analysis on the 4-yr shelfbreak circulation hindcast solutions identifies two dominant modes. The first EOF mode accounts for 61% variance, confirming that the shelfbreak jet is a persistent year-round circulation feature. The second mode accounts for 13% variance, representing the baroclinic eddy passages across the shelf break.

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