Analysis of 26 simulations from 11 general circulation models (GCMs) of the Atmospheric Model Intercomparison Project (AMIP) II reveals a basic inability to simultaneously predict the Yangtze River Valley (YRV) precipitation (Pr-YRV) annual cycle and summer interannual variability in response to observed global SST distributions. Only the Community Climate System Model (CCSM) and L'Institut Pierre-Simon Laplace (IPSL) models reproduce the observed annual cycle, but both fail to capture the interannual variability. Conversely, only Max Planck Institute (MPI) simulates interannual variability reasonably well, but its annual cycle leads observations by 2 months. The interannual variability of Pr-YRV reveals two distinct signals in observations, which are identified with opposite subtropical Pacific SST anomalies in the east (SSTe) and west (SSTw). First, negative SSTe anomalies are associated with equatorward displacement of the upper-level East Asian jet (ULJ) over China. The resulting transverse circulation enhances low-level southerly flow over the South China Sea and south China while convergent flow and upward motion increase over the YRV. Second, positive SSTw anomalies are linked with westward movement of the subtropical high over the west-central Pacific. This strengthens the low-level jet (LLJ) to the south of the YRV. These two signals act together to enhance Pr-YRV. The AMIP II suite, however, generally fails to reproduce these features. Only the MPI.3 realization is able to simulate both signals and, consequently, realistic Pr-YRV interannual variations. It appears that Pr-YRV is governed primarily by coherent ULJ and LLJ variations that act as the atmospheric bridges to remote SSTe and SSTw forcings, respectively. The Pr-YRV response to global SST anomalies may then be realistically depicted only when both bridges are correctly simulated. The above hypothesis does not exclude other signals that may play important roles linking Pr-YRV with remote SST forcings through certain atmospheric bridges, which deserve further investigation.
Wang, C., Liang, X-Z., & Samel, A. N. (2011). AMIP GCM simulations of precipitation variability over the Yangtze River Valley. Journal of Climate, 24(8), 2116--2133. https://doi.org/10.1175/2011JCLI3631.1