The influences of the wintertime AO (Arctic Oscillation) on the interdecadal variation of summer monsoon rainfall in East Asia were examined. An interdecadal abrupt change was found by the end of the 1970s in the variation of the AO index and the leading principal component time series of the summer rainfall in East Asia, The rainfall anomaly changed from below normal to above normal in central China, the southern part of northeastern China and the Korean peninsula around 1978. However,the opposite interdecadal variation was found in the rainfall anomaly in North China and South China.The interdecadal variation of summer rainfall is associated with the weakening of the East Asia summer monsoon circulation. It is indicated that the interdecadal variation of the AO exerts an influence on the weakening of the monsoon circulation. The recent trend in the AO toward its high-index polarity during the past two decades plays important roles in the land-sea contrast anomalies and wintertime precipitation anomaly. The mid- and high-latitude regions of the Asian continent are warming, while the low-latitude regions are cooling in winter and spring along with the AO entering its high-index polarity after the late 1970s. In the meantime, the precipitation over the Tibetan Plateau and South China is excessive, implying an increase of soil moisture. The cooling tendency of the land in the southern part of Asia will persist until summer because of the memory of soil moisture. So the warming of the Asian continent is relatively slow in summer. Moreover, the Indian Ocean and Pacific Ocean which are located southward and eastward of the Asian land, are warming from winter to summer. This suggests that the contrast between the land and sea is decreased in summer. The interdecadal decrease of the land-sea heat contrast finally leads to the weakening of the East Asia summer monsoon circulation. 相似文献
GPS Solutions - The GPS satellite transmitter antenna phase center offsets (PCOs) can be estimated in a global adjustment by constraining the ground station coordinates to the current International... 相似文献
General circulation model outputs are rarely used directly for quantifying climate change impacts on hydrology, due to their coarse resolution and inherent bias. Bias correction methods are usually applied to correct the statistical deviations of climate model outputs from the observed data. However, the use of bias correction methods for impact studies is often disputable, due to the lack of physical basis and the bias nonstationarity of climate model outputs. With the improvement in model resolution and reliability, it is now possible to investigate the direct use of regional climate model (RCM) outputs for impact studies. This study proposes an approach to use RCM simulations directly for quantifying the hydrological impacts of climate change over North America. With this method, a hydrological model (HSAMI) is specifically calibrated using the RCM simulations at the recent past period. The change in hydrological regimes for a future period (2041–2065) over the reference (1971–1995), simulated using bias‐corrected and nonbias‐corrected simulations, is compared using mean flow, spring high flow, and summer–autumn low flow as indicators. Three RCMs driven by three different general circulation models are used to investigate the uncertainty of hydrological simulations associated with the choice of a bias‐corrected or nonbias‐corrected RCM simulation. The results indicate that the uncertainty envelope is generally watershed and indicator dependent. It is difficult to draw a firm conclusion about whether one method is better than the other. In other words, the bias correction method could bring further uncertainty to future hydrological simulations, in addition to uncertainty related to the choice of a bias correction method. This implies that the nonbias‐corrected results should be provided to end users along with the bias‐corrected ones, along with a detailed explanation of the bias correction procedure. This information would be especially helpful to assist end users in making the most informed decisions. 相似文献
Regarded as an effective method for treating the global warming problem, carbon emissions abatement (CEA) allocation has become a hot research topic and has drawn great attention recently. However, the traditional CEA allocation methods generally set efficient targets for the decision-making units (DMUs) using the farthest targets, which neglects the DMUs’ unwillingness to maximize (minimize) some of their inputs (outputs). In addition, the total CEA level is usually subjectively determined without any consideration of the current carbon emission situations of the DMUs. To surmount these deficiencies, we incorporate data envelopment analysis and its closest target technique into the CEA allocation problem. Firstly, a two-stage approach is proposed for setting the optimal total CEA level for the DMUs. Then, another two-stage approach is given for allocating the identified optimal total CEA among the DMUs. Our approach provides more flexibility when setting new input and output targets for the DMUs in CEA allocation. Finally, the proposed approaches are applied for CEA target setting and allocation for 20 Asia-Pacific Economic Cooperation economies.