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Because of the interactive margin between the East Asian summer monsoon and westerly circulation, summer rainfall in northern China (NC) exhibits high variability. By employing reanalysis data and geostationary satellite data from the Fengyun-2G (FY-2G) satellite and using the linear baroclinic model (LBM) and Hybrid Single-Particle Lagrangian Integrated Trajectory model, this study suggests a tripole pattern in summer rainfall over NC and the Indian subcontinent (IS) that is related to the Indian summer monsoon. The distributions of atmospheric circulation indicate three teleconnections: one is from the IS via the Indo-China Peninsula (ICP) and NC, enhancing the Pacific–Japan (PJ) pattern; another is from the IS via west-central Asia and NC, arousing a Eurasian wave pattern; and the third is an IS–TP–NC pattern via the Tibetan Plateau (TP). Those teleconnections modulate vorticity and atmospheric stability over NC. In addition, along with the circulation distribution related to those teleconnections, two pathways of moisture transport related to the IS rainfall are suggested, except for moisture transport via the Bay of Bengal: one is from the Indo-Pacific to NC due to enhancing cyclones over the Indo-Pacific and a PJ-like pattern; and another is from the IS to NC via the TP within the midtroposphere, which modulates midtroposphere moisture fluxes and atmospheric stability over NC. Both teleconnections and moisture transport result in anomalous rainfall over NC. This study reveals a new mechanism and pathway of the Indian summer monsoon impacting NC rainfall, possibly explaining the reason behind the high variability in NC rainfall.

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ABSTRACT:In the present study, the performance of the National Centers for Environmental Prediction/Department of Energy (NCEP/DOE) Atmospheric Model Intercomparison Project (AMIP-II) reanalysis (NCEP-2) and NCEP Climate Forecast System Reanalysis (CFSR) seasonal temperature data for China was quantitatively evaluated by using detrended fluctuation analysis. The results indicate that the quality of the NCEP-2 temperature data is the highest in autumn, while the quality of CFSR data set is the highest in summer. Both the quality of NCEP-2 and that of CFSR temperature data is the lowest in winter. The quality is very low in eastern Tibetan Plateau and most of Xinjiang at a significance level of 0.05 for the NCEP-2 and CFSR reanalysis temperature data including three elements: the daily average temperature (T mean ), the daily maximum temperature (T max ) and the daily minimum temperature (T min ). The performance of the NCEP-2 T mean data is poorer than those of the NCEP-2 T max and T min data for all four seasons, while the performance of CFSR T mean is better than that of CFSR T max and T min for all four seasons. In addition, the NCEP-2 T max , T min and CFSR T mean , T max data perform well in most of central and eastern China for all four seasons. The quality of the CFSR T mean is better than that of the NCEP-2 T mean for all four seasons. However, the NCEP-2 T max and T min data have higher credibility than that of the CFSR T max and T min data for all four seasons. Therefore, it is important to consider the reliability of the NCEP-2 and CFSR daily temperature reanalysis data in different districts and seasons when drawing conclusions from the different reanalysis data.KEY WORDS detrended fluctuation analysis; scaling exponent; long-range correlation; quality of reanalysis data