Tag Archives: Statistical Analysis

Methods Case Study, Gladstone, Queensland, Australia

Dr Bill Johnston [1]

Dr. Bill Johnston’s scientific interests include agronomy, soil science, hydrology and climatology. With colleagues, he undertook daily weather observations from 1971 to 1979.

Abstract

Main Points

  • The weather station at Gladstone Radar marks the approximate southern extremity of the Great Barrier Reef.
  • Temperature and rainfall data are used to case study an objective method of analysing trend and changes in temperature data.
  • The 3-stage approach combines covariance and step-change analysis to resolve site change and covariable effects simultaneously and is widely applicable across Australia’s climate-monitoring network.
  • Accounting for site and instrument changes leaves no residual trend or change in Gladstone’s climate.

Background

In Part 1 of this series, temperature and rainfall data for Gladstone Radar (Bureau of Meteorology (BoM) site 39326) are used to case-study a covariate approach to analysing temperature data that does not rely on comparisons with neighbouring sites whose data may be faulty.

Advantages of the method are:

  • The approach is based on physical principles and is transparent, objective and reproducible across sites.
  • Temperature data are not analysed as time-series in the first instance, which side steps the problem of confounding between serial site changes and the signal of interest.
  • Changes in data that are unrelated to the causal covariate are identified statistically and cross-referenced where possible to independent sources such as aerial photographs and archived plans and documents. Thus the process can’t be manipulated to achieve per-determined trends.
  • The effect of site-changes and other inhomogeneties are verified statistically in the covariate domain. Thus the approach is objective and reproducible.
  • Covariate-adjusted data are tested for trend and other systematic signals in the time-domain.

Further, statistical parameters such as significance of the overall fit (Preg), variation explained R2adj and significances of coefficients provide an independent overview of data quality.

An important link – find out more

The page you have just read is the basic cover story for the full paper. If you are stimulated to find out more, please link through to the full paper – a scientific Report in downloadable pdf format. This Report contains far more detail including photographs, diagrams, graphs and data and will make compelling reading for those truly interested in the issue.

click here to download the full case study including photographs and tables of data used.

Note: Line numbers are provided in the linked Report for the convenience of fact checkers and others wishing to provide comment. If these comments are of a highly technical nature, relating to precise Bomwatch protocols and statistical procedures, it is requested that you email Dr Bill Johnston directly at scientist@bomwatch.com.au referring to the line number relevant to your comment.   

[1] Dr. Bill Johnston’s scientific interests include agronomy, soil science, hydrology and climatology. With colleagues, he undertook daily weather observations from 1971 to 1979.