Observed and Projected Changes to the Precipitation Annual Cycle
Anthropogenic climate change is predicted to cause spatial and temporal shifts in precipitation patterns. Is it also apparent in changes to the annual cycle of zonal mean precipitation? DOE investigators employed 1) CMIP5 preindustrial runs to estimate unforced internal climate variability; 2) historical simulations with estimated changes in anthropogenic and natural forcings over the period 1860–2100 to estimate the forced response to external forcings; and 3) two observational datasets of P: Global Precipitation Climatology Project (GPCP) and the Climate Prediction Center Merged Analysis of Precipitation (CMAP) from 1979 to 2014. They computed the zonal average P(ϕ, t) of combined land and ocean precipitation (where ϕ is latitude and t is the monthly time step) and calculated the amplitude and phase of the best-fit sine wave with period 12 months to determine the annual cycle at each latitude. Model fingerprints of externally forced changes to the amplitude and phase of the P seasonal cycle, combined with observations, enable a formal detection and attribution analysis.
The team found that the observed amplitude changes are inconsistent with model estimates of internal variability but not attributable to the model-predicted response to external forcing. However, the observed changes to the annual cycle phase are inconsistent (GPCP) with estimates of internal variability, and are consistent with model estimates of forced changes. This suggests the emergence of an externally forced signal.
Anthropogenic climate change is predicted to cause spatial and temporal shifts in precipitation patterns. These may be apparent in changes to the annual cycle of zonal mean precipitation P. Trends in the amplitude and phase of the P annual cycle in two long-term, global satellite datasets are broadly similar. Model-derived fingerprints of externally forced changes to the amplitude and phase of the P seasonal cycle, combined with these observations, enable a formal detection and attribution analysis. Observed amplitude changes are inconsistent with model estimates of internal variability but not attributable to the model-predicted response to external forcing. This mismatch between observed and predicted amplitude changes is consistent with the sustained La Niña–like conditions that characterize the recent slowdown in the rise of the global mean temperature. However, observed changes to the annual cycle phase do not seem to be driven by this recent hiatus. These changes are consistent with model estimates of forced changes, are inconsistent (in one observational dataset) with estimates of internal variability, and may suggest the emergence of an externally forced signal.