Detecting climate-related trends in streamflow data

2002 ◽  
Vol 45 (8) ◽  
pp. 89-104 ◽  
Author(s):  
Paul J. Pilon ◽  
Sheng Yue
Keyword(s):  
Local Knowledge ◽  
Serial Correlation ◽  
Selection Criteria ◽  
Spatial Scales ◽  
High Density ◽  
Global Network ◽  
Trend Detection ◽  
Testing Procedures ◽  
Stable Conditions ◽  
Streamflow Data

This paper reviews the results of a number of studies that have investigated streamflow data for the existence of trend. These studies provide evidence that trends in various, but not all, streamflow regimes are occurring at rates that are higher than one might attribute to chance alone. Results of different studies using different approaches were compared and were shown, at times, to have dramatic differences. These differences might potentially be due to pre-conditioning of data prior to trend detection in attempts to minimize the impacts of serial correlation on testing procedures. It was also evident that patterns of trend can vary over small spatial scales and that a relatively high-density network is required to effectively comprehend trend and how it might be altering across an area. A global network of streamflow sites representing pristine or stable conditions is needed to assess patterns of change. Selection criteria for sites within such a network are provided, and it is highlighted that local knowledge is required to perform this selection.

Evaluation of Surface Fluxes in ERA-Interim Using Flux Tower Data

2016 ◽  
Vol 29 (4) ◽  
pp. 1573-1582 ◽  
Author(s):  
Chunlüe Zhou ◽  
Kaicun Wang
Keyword(s):  
Spatial Scales ◽  
Surface Air Temperature ◽  
Environmental Parameters ◽  
Turbulent Fluxes ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
High Density ◽  
Net Radiation ◽  
Broadleaf Forest ◽  
Deciduous Broadleaf Forest

Abstract Surface air temperature Ta is largely determined by surface net radiation Rn and its partitioning into latent (LE) and sensible heat fluxes (H). Existing model evaluations by comparison of absolute flux values are of limited help because the evaluation results are a blending of inconsistent spatial scales, inaccurate model forcing data, and imperfect parameterizations. This study further evaluates the relationships of LE and H with Rn and environmental parameters, including Ta, relative humidity (RH), and wind speed (WS), using ERA-Interim data at a 0.125° × 0.125° grid with observations at AmeriFlux sites from 1998 to 2012. The results demonstrate ERA-Interim can roughly reproduce the absolute values of environmental parameters, radiation, and turbulent fluxes. The model performs well in simulating the correlation of LE and H with Rn, except for the notable correlation overestimation of H against Rn over high-density vegetation (e.g., deciduous broadleaf forest, grassland, and cropland). The sensitivity of LE to Rn in the model is similar to that observed, but that of H to Rn is overestimated by 24.2%. Over the high-density vegetation, the correlation coefficient between H and Ta is overestimated by over 0.2, whereas that between H and WS is underestimated by over 0.43. The sensitivity of H to Ta is overestimated by 0.72 W m−2 °C−1, whereas that of H to WS in the model is underestimated by 16.15 W m−2 (m s−1)−1 over all of the sites. The model cannot accurately capture the responses of evaporative fraction [EF; EF = LE / (LE + H)] to Rn and environmental parameters. This calls for major research efforts to improve the intrinsic parameterizations of turbulent fluxes, particularly over high-density vegetation.

scholarly journals Estimation of global and local complexities of brain networks: A random walks approach

2020 ◽  
Vol 4 (3) ◽  
pp. 575-594
Author(s):  
Roberto C. Sotero ◽  
Lazaro M. Sanchez-Rodriguez ◽  
Narges Moradi ◽  
Mehdy Dousty
Keyword(s):  
Time Series ◽  
Functional Connectivity ◽  
Random Network ◽  
Brain Activity ◽  
Spatial Scales ◽  
Mental States ◽  
Sample Entropy ◽  
Global Network ◽  
Random Walker ◽  
Functional Connections

The complexity of brain activity has been observed at many spatial scales and has been proposed to differentiate between mental states and disorders. Here we introduced a new measure of (global) network complexity, constructed as the sum of the complexities of its nodes (i.e., local complexity). The complexity of each node is obtained by comparing the sample entropy of the time series generated by the movement of a random walker on the network resulting from removing the node and its connections, with the sample entropy of the time series obtained from a regular lattice (ordered state) and a random network (disordered state). We studied the complexity of fMRI-based resting-state networks. We found that positively correlated (pos) networks comprising only the positive functional connections have higher complexity than anticorrelation (neg) networks (comprising the negative connections) and the network consisting of the absolute value of all connections (abs). We also observed a significant correlation between complexity and the strength of functional connectivity in the pos network. Our results suggest that the pos network is related to the information processing in the brain and that functional connectivity studies should analyze pos and neg networks separately instead of the abs network, as is commonly done.

scholarly journals Use of Silicone Sizers in Implantation of Porous Polyethylene Nasal Dorsal Implants in Asians

2011 ◽  
Vol 2011 ◽  
pp. 1-3
Author(s):  
Randal Pham
Keyword(s):  
Selection Criteria ◽  
High Density ◽  
Nasal Surgery ◽  
Porous Polyethylene ◽  
Asian Patients ◽  
Thin Skin ◽  
History Of ◽  
A New Technique ◽  
Patient Selection Criteria ◽  
Porous Polyethylene Implants

Introduction. A new technique of implantation of high-density porous polyethylene nasal dorsal implants in Asians is described in this paper. Silicone sizers, which have smooth surfaces, were used to facilitate implantation of porous polyethylene implants in Asian patients. Materials and Methods. Twenty-three patients of Asian descent underwent dorsal augmentation rhinoplasty with open technique using high-density porous polyethylene implants. In all cases, silicone sizers were used to facilitate implantations of high-density porous polyethylene nasal dorsal implants. Patient selection criteria exclude patients with history of cocaine use, history of nasal or sinus disorders, previous nasal surgery, deviated septum, poor cartilage support, and thin skin. Results. No bleeding, infection, rejection, displacement, or extrusion was noted. One implant was removed because of a patient's dissatisfaction with the resulting tip height. Conclusion. The use of silicone sizers to facilitate implantations of high-density porous polyethylene nasal dorsal implants was safe and efficacious.

scholarly journals Reconstructing North Sea palaeolandscapes from 3D and high-density 2D seismic data: An overview

2014 ◽  
Vol 93 (1-2) ◽  
pp. 31-42 ◽  
Author(s):  
S. van Heteren ◽  
J.A.C. Meekes ◽  
M.A.J. Bakker ◽  
V. Gaffney ◽  
S. Fitch ◽  
...  
Keyword(s):  
North Sea ◽  
Spatial Scales ◽  
Building Blocks ◽  
High Density ◽  
Glacial Cycles ◽  
The North ◽  
3D Data ◽  
Hunting And Gathering ◽  
Environmental Setting ◽  
The North Sea

AbstractThe North Sea subsurface shows the marks of long-term tectonic subsidence. Much of it contains a thick record of glacial and interglacial deposits and landscapes, formed during multiple glacial cycles and the associated regressions and transgressions during the past two million years. At times of lower sea level than today, areas that are presently submerged were fertile lowlands more favourable for hunting and gathering than the surrounding upland. These drowned lowlands are not captured by traditional 1:250,000 geological maps of the North Sea subsurface because the underlying seismic and core data are commonly too widely spaced to achieve this. Palaeolandscape mapping requires identification of building blocks with spatial scales in the order of 1 km or less. As high-density 2D and high-quality 3D seismics are becoming available for an increasing part of the North Sea, glacial and interglacial palaeolandscapes can be reconstructed for more and more areas. An overview of published palaeolandscape reconstructions shows that shallow time slices through 3D data provide map views that are very suitable for the identification of landscape elements. For optimal results, each time slice needs to be validated and ground-truthed with 2D seismics and with descriptions and analyses of cores and borehole samples. Interpretations should be made by teams of geoscientists with a sufficiently broad range of expertise to recognise and classify even subtle or unfamiliar patterns and features. The resulting reconstructions will provide a context and an environmental setting for Palaeolithic, Mesolithic, and Neolithic societies and finds.

U.S. Mussel Watch Data from 1986 to 1994:  Temporal Trend Detection at Large Spatial Scales

1997 ◽  
Vol 31 (5) ◽  
pp. 1411-1415 ◽  
Author(s):  
B. Beliaeff ◽  
Thomas P. O'Connor ◽  
D. K. Daskalakis ◽  
P. J. Smith
Keyword(s):  
Temporal Trend ◽  
Spatial Scales ◽  
Trend Detection ◽  
Mussel Watch

scholarly journals Measuring high-density built environment for public health research: Uncertainty with respect to data, indicator design and spatial scale

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Guibo Sun ◽  
Chris Webster ◽  
Michael Y. Ni ◽  
Xiaohu Zhang
Keyword(s):  
Hong Kong ◽  
Built Environment ◽  
Urban Health ◽  
Health Research ◽  
Spatial Scales ◽  
Large Population ◽  
Rank Correlation ◽  
Public Health Research ◽  
Population Based ◽  
High Density

Uncertainty with respect to built environment (BE) data collection, measure conceptualization and spatial scales is evident in urban health research, but most findings are from relatively lowdensity contexts. We selected Hong Kong, an iconic high-density city, as the study area as limited research has been conducted on uncertainty in such areas. We used geocoded home addresses (n=5732) from a large population-based cohort in Hong Kong to extract BE measures for the participants’ place of residence based on an internationally recognized BE framework. Variability of the measures was mapped and Spearman’s rank correlation calculated to assess how well the relationships among indicators are preserved across variables and spatial scales. We found extreme variations and uncertainties for the 180 measures collected using comprehensive data and advanced geographic information systems modelling techniques. We highlight the implications of methodological selection and spatial scales of the measures. The results suggest that more robust information regarding urban health research in high-density city would emerge if greater consideration were given to BE data, design methods and spatial scales of the BE measures.

scholarly journals Applying geoscience to biodiversity monitoring: Case studies from an Australian marine park

2018 ◽  
Author(s):  
Rachel Przeslawski ◽  
Kim Picard ◽  
Scott Nichol ◽  
Ben Radford ◽  
Phil Bouchet
Keyword(s):  
Sampling Design ◽  
Spatial Scales ◽  
Biological Data ◽  
Trend Detection ◽  
Design Data ◽  
Sediment Grain Size ◽  
Marine Park ◽  
Management Plans ◽  
Robust Modelling ◽  
Research And Policy

Following the establishment of the world’s largest network of marine protected areas, Australia is now tasked with implementing national plans to manage a huge range of marine environments, from tropical to sub-Antarctic climates and shallow reef to abyssal depths. Monitoring (i.e. condition assessment and trend detection) is one of the key objectives of associated management plans. As part of a national effort to acquire baseline data for future monitoring purposes from 2009 to 2012, we collected geoscientific (bathymetry, backscatter, sub-bottom profiles, sediment grain-size) and biological data (assemblages and richness of infauna, sponges and pelagic fish) using a variety of gear (grab, sled, pelagic baited video, multibeam sonar, sparker) from the Oceanic Shoals Australian Marine Park in northern Australia. In this presentation, we describe how the integration of such data (including derived geoscientific products) helped to inform sampling design, map habitats, predict the distribution of benthic and pelagic communities at varying spatial scales, and better understand ecosystem processes. We hope to encourage ecologists and marine managers to incorporate geoscientific methods into their research and policy in order to further improve sampling design, data collection, robust modelling, and informed decision-making.

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