How Ominous is the Premonition of Future Global Warming?
Debashis Chatterjee, Sourabh Bhattacharya

TL;DR
This paper critically assesses the future climate predictions of general circulation models (GCMs) using a Bayesian model selection approach, finding that current models may overstate the severity of future global warming.
Contribution
It introduces a Bayesian multiple testing framework for evaluating GCM predictions, applying Gaussian process emulation to assess the validity of future warming scenarios.
Findings
Selected GCM models do not convincingly support current warming patterns.
Results challenge the alarming future global warming predictions.
Forecasts do not indicate drastic future temperature increases.
Abstract
Global warming, the phenomenon of increasing global average temperature in the recent decades, is receiving wide attention due to its very significant adverse effects on climate. Whether global warming will continue even in the future, is a question that is most important to investigate. In this regard, the so-called general circulation models (GCMs) have attempted to project the future climate, and nearly all of them exhibit alarming rates of global temperature rise in the future. Although global warming in the current time frame is undeniable, it is important to assess the validity of the future predictions of the GCMs. In this article, we attempt such a study using our recently-developed Bayesian multiple testing paradigm for model selection in inverse regression problems. The model we assume for the global temperature time series is based on Gaussian process emulation of the black…
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Taxonomy
TopicsGlobal Energy and Sustainability Research · Atmospheric and Environmental Gas Dynamics · Science and Climate Studies
