Nov 18, 2011
Separating signal and noise in atmospheric temperature changes: The importance of timescale
by
,
Journal of Geophysical Research: Atmospheres
- 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