Assessing internal variability of global mean surface temperature from
observational data and implications for reaching key thresholds
Abstract
Observed global mean surface temperature (GMST) combines a forced
response with internal variability, and quantifying internal variability
is important in assessing the reaching of key thresholds, such as the
1.5 °C warming threshold in the Paris Agreement. This paper uses
observational data to estimate internal variability. Since the current
period of warming began in the 1970s, the 10-year mean of GMST has been
very close to the 30-year mean for the period it is centred in and can
therefore be considered as a robust indicator of the recent state of the
climate. The range between the 5th and
95th percentile of annual residuals of observed GMST
is 0.319 °C, substantially less than the corresponding range in large
model ensembles, implying that the first individual year above 1.5 °C
may occur later than indicated by climate models. The largest annual
residuals are mostly associated with large-amplitude El Niño-Southern
Oscillation (ENSO) events or major volcanic eruptions, with the
relationship between cool years and La Niña more consistent than that
between warm years and El Niño. The relationship between multi-year GMST
means for differing periods indicates that the probability that the 1.5
°C threshold has been crossed (using the IPCC definition of the midpoint
of the first 20-year period above the threshold) exceeds 50% once the
most recent observed 11-year mean reaches 1.43 °C.