The present subproject has two objectives:
Within the AMIP (Subproject #25), SUNYA has conducted "GCM-to-observation" and "GCM-to-GCM" comparisons with focus on systematic errors of climatological mean and variability of AGCMs' simulated east Asia climate (EAC). The models are capable of reproducing the observed large-scale features, but exhibit significant biases in simulating the seasonal precipitation characteristics (Liang et al., 1997; Samel et al., 1996), especially the magnitudes and locations of maximum precipitation, and their time evolution during summer (Wang et al., 1997a).
When averaged over 105E-122E, there exist two peaks in the observed latitudinal distribution of May monthly mean rainfall across 10S-45N. The maximum (~8mm/day) occurs at the equator and around 22N, and both peaks are associated with strong positive vertical motions. In June, the two peaks merge as a result of the northward movement of ITCZ; the peak value of 9 mm/day rainfall covers a broader latitudinal zone and is identified with greatly enhanced upward motion (versus May). For AMIP models, for example, NCAR-CCM3 catches the two-peaks structure in May, although the equatorial peak has a larger value and the midlatitude rainfall peak is located further to the north at 32N. In addition, the model fails to simulate the northward movement of the ITCZ so that the two rainfall systems appear to be stationary and do not merge in June. Note that these features are consistent with a lack of strong vertical motion, in particular in South China Sea. It is interesting to find that this model bias is significantly reduced when CCM3 is coupled with an ocean circulation model. For example, the vertical motion and precipitation over 10-20N are much enhanced, thus reflecting the importance of air-sea interaction in influencing the precipitation over east Asia.
We have been analyzing the 1471-1950 flood/drought proxy data over
eastern China to study decadal climate variability (Liang et al., 1995;
Wang et al., 1997b) and to compare the results with those simulated
from 1000-years GFDL CGCM simulations of precipitation. [Note that the
proxy data contain implicit changes in climate forcing (such as
volcanic eruptions, greenhouse gases) while the model simulation,
although without climate forcing changes, has inherent variability
associated with internal dynamics of the climate system.] Similar
interannual and
For air-sea interaction, we need time-averaged surface heat balance components (latent, sensible and longwave and shortwave radiative fluxes) and surface wind, surface air temperature and SST.
For decadal climate variability, we need monthly mean time series of precipitation and temperature over eastern China. We plan also to use the 2xCO2 simulated temperature and precipitation to compare the changes in climate variability. In addition, at a latter stage, we need to compare the soil moisture if the CMIP data are available.
Liang, X.-Z., A. N. Samel, and W.-C. Wang, 1995: Observed and GCM simulated decadal variability of monsoon rainfall in east China. Climate Dynamics, 11, 103-114.
Liang, X.-Z., K. R. Sperber, W.-C. Wang, and A. N. Samel, 1997: Predictability of SST forced climate signals in two atmospheric general circulation models. Climate Dynamics (in press).
Samel, A. N., S.-W. Wang, and W.-C. Wang, 1995: A comparison between observed and GCM simulated summer monsoon characteristics over China. J. Climate, 8, 1690-1696.
Wang, W.-C., H.-H. Hsu, W.-S. Kau, X.-Z. Liang, LinHo, C.-T. Chen, A. N. Samel, C.-H. Tsou, P.-H. Lin, and K.-C. Ko, 1997a: GCM simulations of the east Asia climate. Proceedings of the Third East Asia-West Pacific Meteorology and Climate Conference, Chung-li, Taiwan, May 16-18, 1996.
Wang, W.-C., P.-Y. Zhang, Q.-S. Ge, and J.-Y. Zheng, 1997b: Reconstruction of historical climate in China. (in manuscript)