Causes of Robust Seasonal Land Precipitation Changes

Historical simulations from the Coupled Model Intercomparison Project phase 5 (CMIP5) archive are used to calculate the zonal mean change in seasonal land precipitation for the second half of the twentieth century in response to a range of external forcings, including anthropogenic and natural forcings combined (ALL), greenhouse gas forcing, anthropogenic aerosol forcing, anthropogenic forcings combined and natural forcing. These simulated patterns of change are used as ngerprints in a detection and attribution study applied to four dierent gridded observational datasets of global land precipitation from 1951 to 2005. There are large dierences in the spatial and temporal coverage in the observational datasets, yet despite these dierences, the zonal mean patterns of change are mostly consistent except at latitudes where spatial coverage is limited. The results show some dierences between datasets, but the influence of external forcings is robustly detected in March, April and May (MAM), in December, January and February (DJF) and for annual changes for the three datasets more suitable for studying changes. For June, July and August (JJA) and September, October and November (SON), external forcing is only detected for the dataset that includes only long-term stations. Fingerprints for combinations of forcings that include the eect of greenhouse gases are similarly detectable to those for ALL forcings, suggesting that greenhouse gas in
uence drives the detectable features of the ALL forcing ngerprint. Fingerprints of only natural or only anthropogenic aerosol forcing are not detected. This, together with two-ngerprint results suggests that at least some of the detected change in zonal land precipitation can be attributed to human influences.