Science Source

Separating signal and noise in atmospheric temperature changes: The importance of timescale

Compares global‐scale changes in satellite estimates of the temperature of the lower troposphere (TLT) with model simulations of forced and unforced TLT changes
Uses observed estimates of the signal component of TLT changes and model estimates of climate noise to calculate timescale‐dependent signal‐to‐noise ratios (S/N)
States that these ratios are small (less than 1) on the 10‐year timescale, increasing to more than 3.9 for 32‐year trends
States that this large change in S/N is primarily due to a decrease in the amplitude of internally generated variability with increasing trend length
States that — because of the pronounced effect of interannual noise on decadal trends — a multi‐model ensemble of anthropogenically‐forced simulations displays many 10‐year periods with little warming
Concludes that a single decade of observational TLT data is inadequate for identifying a slowly evolving anthropogenic warming signal
Results show that temperature records of at least 17 years in length are required for identifying human effects on global‐mean tropospheric temperature