Abstract

The Paris Agreement on climate change aims to limit ‘global average temperature’ rise to ‘well below 2 °C’ but reported temperature depends on choices about how to blend air and water temperature data, handle changes in sea ice and account for regions with missing data. Here we use CMIP5 climate model simulations to estimate how these choices affect reported warming and carbon budgets consistent with the Paris Agreement. By the 2090s, under a low-emissions scenario, modelled global near-surface air temperature rise is 15% higher (5%–95% range 6%–21%) than that estimated by an approach similar to the HadCRUT4 observational record. The difference reduces to 8% with global data coverage, or 4% with additional removal of a bias associated with changing sea-ice cover. Comparison of observational datasets with different data sources or infilling techniques supports our model results regarding incomplete coverage. From high-emission simulations, we find that a HadCRUT4 like definition means higher carbon budgets and later exceedance of temperature thresholds, relative to global near-surface air temperature. 2 °C warming is delayed by seven years on average, to 2048 (2035–2060), and CO2 emissions budget for a >50% chance of <2 °C warming increases by 67 GtC (246 GtCO2).

Highlights

  • Reflecting the 90—100 % consensus among relevant research[1, 2], the 5th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) stated that “warming of the climate system is unequivocal” and “It is extremely [95—100 %] likely that human influence has been the dominant cause of the observed warming since the mid-20th century”.(3) Such scientific findings can inform policy responses in concert with other factors such as risk aversion, discounting of the future and assessments of the severity of future climate impacts

  • As it is likely that stakeholders may have diverse interpretations as to what global average temperature refers, here we provide carbon budgets for different definitions of global average temperature, including definitions consistent with current observational products

  • Temperature bias still continues to grow with time in RCP2.6, and Figure 2 demonstrates that the masking bias component is likely dominated by the warming at high northern latitudes, which tend to warm much more than the global average and are poorly sampled

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Summary

Introduction

Reflecting the 90—100 % consensus among relevant research[1, 2], the 5th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) stated that “warming of the climate system is unequivocal” and “It is extremely [95—100 %] likely that human influence has been the dominant cause of the observed warming since the mid-20th century”.(3) Such scientific findings can inform policy responses in concert with other factors such as risk aversion, discounting of the future and assessments of the severity of future climate impacts. The IPCC 5th Assessment Report (AR5) assessed carbon budgets for various levels of warming in billions of tonnes of carbon (GtC) or of carbon dioxide (GtCO2) based on projections of global nearsurface air temperature change, which we refer to as “global-tas”, where tas means “temperature, air, at surface”, from complex Earth System Models (ESMs). Climate modelling studies use global-tas, whereas observational records typically combine non-global coverage of near-surface air temperature over land with sea-surface temperature (SST) over oceans into a single timeseries. Three main factors contribute to differences in “global average temperature” change between global-tas and observational records. Data providers must decide how to ce account for changes in sea ice. There may be a change from reporting estimated near-surface air temperatures to SSTs where ice has retreated. In the HadCRUT4 dataset[10] this approach probably results in an artificially low reported warming compared with the true air warming due to features of the normalisation procedure

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