The spatial distribution of soil moisture, especially the temporal variation at seasonal and interannual scales, is difficult for many land surface models （LSMs） to capture partly due to the deficiencies of the LSMs and the highly spatial variability of soil moisture, which makes it problematic to simulate the moisture for climate studies. However the soil moisture plays an important role in influencing the energy and hydrological cycles between the land and air, so it should be considered in land surface models. In this paper, a soil moisture simulation in China with a T213 resolution （about 0.5625°× 0.5625°） is compared to the observational data, and its relationship to precipitation is explored. The soil moisture distribution agrees roughly with the observations, and the soil moisture pattern reflects the variation and intensity of the precipitation. In particular, for the 1998 summer catastrophic floods along the Yangtze River, the soil moisture remains high in this region from July to August and represents the flood well. The seasonal cycle of soil moisture is roughly consistent with the observed data, which is a good calibration for the ground simulation capacity of the Atmosphere-Vegetation Interaction Model （AVIM） with respect to this tough problem for land surface models.
The interaction between climate and vegetation along four Pole-Equator-Pole （PEP） belts were explored using a global two-way coupled model, AVIM-GOALS, which links the ecophysiological processes at the land surface with the general circulation model （GCM）. The PEP belts are important in linking the climate change with the variation of sea and land, including terrestrial ecosystems. Previous PEP belts studies have mainly focused on the paleoclimate variation and its reconstruction. This study analyzes and discusses the interaction between modern climate and vegetation represented by leaf area index （LAI） and net primary production （NPP）. The results show that the simulated LAI variation, corresponding to the observed LAI variation, agrees with the peak-valley variation of precipitation in these belts. The annual mean NPP simulated by the coupled model is also consistent with PIK NPP data in its overall variation trend along the four belts, which is a good example to promote global ecological studies by coupling the climate and vegetation models. A large discrepancy between the simulated and estimated LAI emerges to the south of 15°N along PEP 3 and to the south of 18°S in PEP 1S, and the discrepancy for the simulated NPP and PIK data in the two regions is relatively smaller in contrast to the LAI difference. Precipitation is a key factor affecting vegetation variation, and the overall trend of LAI and NPP corresponds more obviously to precipitation variation than temperature change along most parts of these PEP belts.
