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Observations from 550 surface stations in China during 1961-2000 are used to evaluate the skill of seven global coupled climate models in simulating extreme temperature and precipitation indices. It is found that the models have certain abilities to simulate both the spatial distributions of extreme climate indices and their trends in the observed period. The models' abilities are higher overall for extreme temperature indices than for extreme precipitation indices. The well-simulated temperature indices are frost days (Fd), heat wave duration index (HWDI) and annual extreme temperature range (ETR). The well-simulated precipitation indices are the fraction of annual precipitation total due to events exceeding the 95th percentile (R95T) and simple daily intensity index (SDII). In a general manner, the multi-model ensemble has the best skill. For the projections of the extreme temperature indices, trends over the twenty-first century and changes at the end of the twenty-first century go into the same direction. Both frost days and annual extreme temperature range show decreasing trends, while growing season length, heat wave duration and warm nights show increasing trends. The increases are especially manifested in the Tibetan Plateau and in Southwest China. For extreme precipitation indices, the end of the twenty-first century is expected to have more frequent and more intense extreme precipitation. This is particularly visible in the middle and lower reaches of the Yangtze River, in the Southeast coastal region, in the west part of Northwest China, and in the Tibetan Plateau. In the meanwhile, accompanying the decrease in the maximum number of consecutive dry days in Northeast and Northwest, drought situation will reduce in these regions. [ABSTRACT FROM AUTHOR]

Modelling of the carbon dynamics in arable soils is complex and the accuracy of the predictions is unknown before the model is applied to each specific site. Objectives were (i) to test the accuracy of predictions of the carbon dynamics using the Rothamsted Carbon (RothC) Model in a field trial in Quzhou, North China Plain, using different methods for initialization and estimation of carbon input into the soil and (ii) to test the applicability of the RothC model for plots with either conventional tillage (CT) or no-tillage (NT) systems. A field trial was conducted with applications of differing amounts of N (0, 112 or 187 kg N ha−1 year−1), P (0, 75 or 150 kg P2O5 ha−1 year−1) and wheat straw (0, 2.25 or 4.5 t DM ha−1 year−1) in differing combinations with either CT or NT for 18 years. CT and NT affected stocks of soil organic carbon (SOC) similarly. Carbon inputs from crops were either estimated from published regression functions that relate C inputs to crop yield including rhizodeposition (models 1 and 2) or published root:aboveground biomass ratios (model 3). Model 1, which was not calibrated to the site conditions, was successful in predicting the carbon dynamics in seven out of nine treatments (model efficiencies EF ranged from 0.28 to 0.87), whereas for two treatments, EF (−0.35 and−2.3) indicated an unsuccessful prediction. The prediction of the C dynamics in NT experiments using model 1 was generally successful, but this may have been due to the fact that NT did not have a specific effect on SOC stocks for this trial. Model 2, which was the same as model 1 except for an optimization of the stock of inert organic matter using one treatment, predicted SOC stocks in the remaining eight treatments overall better than model 1. Model 3 was less successful than models 1 and 2 in all treatments (−19 ≤ EF ≤ 0.56). The results indicate that the RothC model may successfully predict C dynamics—for the site studied even without prior calibration as in model 1—, but care should be taken in choosing an appropriate approach for estimating C inputs into the soil. [ABSTRACT FROM AUTHOR]