Validation and forecasting accuracy in models of climate change

Abstract

Forecasting researchers, with few exceptions, have ignored the current major forecasting controversy: global warming and the role of climate modelling in resolving this challenging topic. In this paper, we take a forecaster's perspective in reviewing established principles for validating the atmospheric-ocean general circulation models (AOGCMs) used in most climate forecasting, and in particular by the Intergovernmental Panel on Climate Change (IPCC). Such models should reproduce the behaviours characterising key model outputs, such as global and regional temperature changes. We develop various time series models and compare them with forecasts based on one well-established AOGCM from the UK Hadley Centre. Time series models perform strongly, and structural deficiencies in the AOGCM forecasts are identified using encompassing tests. Regional forecasts from various GCMs had even more deficiencies. We conclude that combining standard time series methods with the structure of AOGCMs may result in a higher forecasting accuracy. The methodology described here has implications for improving AOGCMs and for the effectiveness of environmental control policies which are focussed on carbon dioxide emissions alone. Critically, the forecast accuracy in decadal prediction has important consequences for environmental planning, so its improvement through this multiple modelling approach should be a priority.

Long‐Term Forecasting of Global Carbon Dioxide Emissions: Reducing Uncertainties Using a Per Capita Approach

“…Fildes and Kourentzes (2011) discuss the various concepts of forecasting as they apply to emission scenarios and climate model predictions, and apply forecast evaluation methods to regional and global temperature series. Fildes and Kourentzes (2011) discuss the various concepts of forecasting as they apply to emission scenarios and climate model predictions, and apply forecast evaluation methods to regional and global temperature series.…”

“…Econometric forecast evaluation tools are beginning to be applied to a variety of modeling work related to global warming. Fildes and Kourentzes (2011) discuss the various concepts of forecasting as they apply to emission scenarios and climate model predictions, and apply forecast evaluation methods to regional and global temperature series. As they point out, application of forecast evaluation methods is only in the early stages with regard to climate-modeling efforts generally, despite the importance of these prediction systems for policymaking.…”

Neural network ensemble operators for time series forecasting

“…This has implications for multiple forecasting applications where NN ensembles have been used. Some examples include diverse forecasting applications such as: economic modelling and policy making (McAdam and McNelis, 2005;Inoue and Kilian, 2008), financial and commodities trading (Zhang and Berardi, 2001;Chen and Leung, 2004;Versace et al, 2004;Bodyanskiy and Popov, 2006;Yu et al, 2008), fast-moving consumer goods (Trapero et al, 2012), tourism (Pattie and Snyder, 1996), electricity load (Hippert et al, 2001;Taylor and Buizza, 2002), temperature and weather (Roebber et al, 2007;Langella et al, 2010), river flood (Campolo et al, 1999) and hydrological modelling (Dawson and Wilby, 2001), climate (Fildes and Kourentzes, 2011), and ecology (Araújo and New, 2007) to name a few. Zhang et al (1998) lists multiple other forecasting applications where they have been employed successfully.…”

Surface temperature forecast skill comparison for the west coast of Saudi Arabia

“…One of the motivations for selecting four coastal stations (in SA) is to assess the relative temperature forecast skill of several meso/regional-scale weather and climate forecasting models, since these models are known to have biases in forecasting surface temperatures in the planetary boundary layer due to land-sea contrast in coastal areas (see, for instance, Cox et al, 1998;Fildes and Kourentzes, 2011;Kerr, 2011;O'Brien et al, 2012). To reduce and isolate the impacts of model simulations of the strong diurnal cycle present for stations in the inland SA, the selected four stations belong to the same climatic zone in the coastal areas, even though a strong north-south temperature gradient exists (Al-Jerash, 1985).…”