Using spatial interpolation to construct a comprehensive archive of Australian climate data

By Stephen J. Jeffrey, John O. Carter, Keith B. Moodie, Alan R. Beswick. Environmental Modelling & Software, 2001

1,978 citations recorded by the source corpus.

Subfields: Environmental Engineering, Global and Planetary Change, Oceanography

View Paper: https://www.semanticscholar.org/paper/01892654ccb46b6b240172c5ad8bde4a2768b515

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Citations in the corpus

Water and temperature stress define the optimal flowering period for wheat in south-eastern Australia (2017, methodology): “, 2009) and patched-point 155 meteorological weather stations from the SILO database (Jeffrey et al., 2001).”
Interpolation of Missing Temperature Data at Meteorological Stations Using P-BSHADE (2013, background): “Kriging and its variants (Goovaerts 1997; Isaaks and Srivastava 1989; Olea 1999) have been applied extensively to interpolation of climate data (Boer et al. 2001; Hudson andWackernagel 1994; Jeffrey et al. 2001).”
Drought-related tree death of savanna eucalypts: Species susceptibility, soil conditions and root architecture (2007, methodology): “To describe the relative intensity of rainfall deficit for the soil moisture sites, monthly rainfall values were obtained from modelled climate (SILO: Jeffrey et al. 2001).”
Exploring, exploiting and evolving diversity of aquatic ecosystem models: a community perspective (2015, background): “Modelling then allows for interpolation in space and time such as seen in climatology (Jeffrey et al. 2001).”
Estimation of monthly evaporative loss using relevance vector machine, extreme learning machine and multivariate adaptive regression spline models (2016, methodology): “…(S; MJ m2), maximum temperature (Tmax; C), minimum temperature (Tmin; C), atmospheric vapor pressure (VP; hPa) and total precipitation (P; mm) were acquired from the Scientific Information for Land Owners (SILO) databases (Jeffrey et al. 2001) (https://www.longpaddock.qld. gov.au/silo/about.html).”
Recent changes in southern Australian frost occurrence: implications for wheat production risk (2016, methodology): “This minimum temperature surface is available for the period 1889 to the present, at a grid resolution of 0.058 latitude by 0.058 longitude (~5 km 5 km) (Jeffrey et al. 2001).”
Optimising grain yield and grazing potential of crops across Australia’s high-rainfall zone: a simulation analysis. 1. Wheat (2015, methodology): “with reset each year) were run for each of 50 years (1959–2009) using local Patched Point climate data from the SILO database (Jeffrey et al. 2001).”
Climate change effects on pasture systems in south-eastern Australia (2009, methodology): “For each site, historical daily climate data for the 30-year baseline and 10-year lead-in period (i.e. 1 January 1961–31 December 2000) were obtained in April 2008 from the SILO database (www.longpaddock.qld.gov.au/silo/, Jeffrey et al. 2001).”
Re-inventing model-based decision support with Australian dryland farmers. 4. Yield Prophet® helps farmers monitor and manage crops in a variable climate. (2009, neutral): “Othermeteorological data were obtained from the nearest Bureau of Meteorology climate station (Jeffrey et al. 2001; www.nrw. qld.gov.au/silo/).”