ORCID Profile
0000-0003-3049-6505
Current Organisation
University of Adelaide
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Publisher: The Royal Society
Date: 03-2019
DOI: 10.1098/RSOS.181089
Abstract: The eye may perceive a significant trend in plotted time-series data, but if the model errors of nearby data points are correlated, the trend may be an illusion. We examine generalized least-squares (GLS) estimation, finding that error correlation may be underestimated in highly correlated small datasets by conventional techniques. This risks indicating a significant trend when there is none. A new correlation estimate based on the Durbin–Watson statistic is developed, leading to an improved estimate of autoregression with highly correlated data, thus reducing this risk. These techniques are generalized to randomly located data points in space, through the new concept of the nearest new neighbour path. We describe tests on the validity of the GLS schemes, allowing verification of the models employed. Ex les illustrating our method include a 40-year record of atmospheric carbon dioxide, and Antarctic ice core data. While more conservative than existing techniques, our new GLS estimate finds a statistically significant increase in background carbon dioxide concentration, with an accelerating trend. We conclude with an ex le of a worldwide empirical climate model for radio propagation studies, to illustrate dealing with spatial correlation in unevenly distributed data points over the surface of the Earth. The method is generally applicable, not only to climate-related data, but to many other kinds of problems (e.g. biological, medical and geological data), where there are unequally (or randomly) spaced observations in temporally or spatially distributed datasets.
Publisher: SPIE
Date: 21-08-2001
DOI: 10.1117/12.438143
Publisher: SPIE
Date: 28-12-2006
DOI: 10.1117/12.638889
Publisher: IEEE
Date: 08-2018
Publisher: SPIE
Date: 11-2002
DOI: 10.1117/12.476109
Publisher: SPIE
Date: 11-2002
DOI: 10.1117/12.476427
Publisher: SPIE
Date: 19-11-2001
DOI: 10.1117/12.448842
Publisher: SPIE
Date: 08-10-1999
DOI: 10.1117/12.368458
Publisher: IEEE
Date: 07-2015
Publisher: IEEE
Date: 09-2008
Publisher: IEEE
Date: 08-2014
Publisher: IEEE
Date: 04-2014
Publisher: Institution of Engineering and Technology (IET)
Date: 07-2015
DOI: 10.1049/EL.2015.0195
Publisher: American Meteorological Society
Date: 03-2017
DOI: 10.1175/BAMS-D-14-00284.1
Abstract: The purpose of the Tropical Air–Sea Propagation Study (TAPS), which was conducted during November–December 2013, was to gather coordinated atmospheric and radio frequency (RF) data, offshore of northeastern Australia, in order to address the question of how well radio wave propagation can be predicted in a clear-air, tropical, littoral maritime environment. Spatiotemporal variations in vertical gradients of the conserved thermodynamic variables found in surface layers, mixing layers, and entrainment layers have the potential to bend or refract RF energy in directions that can either enhance or limit the intended function of an RF system. TAPS facilitated the collaboration of scientists and technologists from the United Kingdom, the United States, France, New Zealand, and Australia, bringing together expertise in boundary layer meteorology, mesoscale numerical weather prediction (NWP), and RF propagation. The focus of the study was on investigating for the first time in a tropical, littoral environment the i) refractivity structure in the marine and coastal inland boundary layers ii) the spatial and temporal behavior of momentum, heat, and moisture fluxes and iii) the ability of propagation models seeded with refractive index functions derived from blended NWP and surface-layer models to predict the propagation of radio wave signals of ultrahigh frequency (UHF 300 MHz–3 GHz), super-high frequency (SHF 3–30 GHz), and extremely high frequency (EHF 30–300 GHz). Coordinated atmospheric and RF measurements were made using a small research aircraft, slow-ascent radiosondes, lidar, flux towers, a kitesonde, and land-based transmitters. The use of a ship as an RF-receiving platform facilitated variable-range RF links extending to distances of 80 km from the mainland. Four high-resolution NWP forecasting systems were employed to characterize environmental variability. This paper provides an overview of the TAPS experimental design and field c aign, including a description of the unique data that were collected, preliminary findings, and the envisaged interpretation of the results.
Publisher: Elsevier BV
Date: 2002
Publisher: IOP Publishing
Date: 17-01-2008
Publisher: SPIE
Date: 30-03-2004
DOI: 10.1117/12.527948
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2007
Publisher: IEEE
Date: 09-2008
Publisher: IEEE
Date: 07-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: SPIE
Date: 21-12-2008
DOI: 10.1117/12.769202
No related grants have been discovered for Hedley Hansen.