Analysis of ground‐based and remotely retrieved precipitation data reveals that heavy Meiyu precipitation events (HMPEs) produce a relatively independent rain belt over eastern China. A rotating calipers algorithm is applied to quantify the spatial scales of HMPEs. We find that HMPEs have regular spatial scales with an average length, width, and extent of about 1,400 km, 500 km, and 40.00 × 10⁴ km², respectively, through a comprehensive assessment of different types of HMPE, illustrating that HMPEs have a size similar to that of the subsynoptic‐scale Meiyu front (1,500–2,000 km). Convective activities along the Meiyu front zone and the upper westerly jet stream strongly affect the position and orientation of rain belts of HMPEs. The Meiyu front zone, strong vertical motions, and large transport of warm moisture have a comparable spatial scale to the HMPE rain belts over eastern China.

Understanding the effects of zonal variation of the East Asian subtropical westerly jet (EAWJ) on spatial features of heavy precipitation events requires characterization of the shape, orientation, position, and scale of both the EAWJ and rain belts. Applying a rotating calipers algorithm, jet-axis tracking, wavelet analysis, and K-means clustering algorithm, spatial structures of both the EAWJ and rain belts were quantified for each heavy rainfall event lasting 3 days (3-day-HRE) in 1983–2020. The results reveal that approximately 90% of the EAWJs related to 3-day-HREs had a statistically significant wave structure of ∼6000–12 000 km over East Asia and the North Pacific. These EAWJs had tilted, wavy, and flat patterns and strongly affected the position, orientation, and spatial scales of the 3-day-HRE rain belts by modifying the vapor transport trajectory and vertical rising motions. All types of EAWJ had an orientation similar to that of the rain belts and an average distance to the rain belts of ∼500–1500 km at 105°–125°E and ∼500 km at 125°E–180°. Correspondingly, the rain belts of 3-day-HREs had the largest frequency over eastern China and southern Japan. Zonally asymmetric Rossby waves arising from the land–sea thermal contrast, atmospheric diabatic heating, and topography dominantly contributed to the formation of a meandering or flat EAWJ. A zonally oscillating trough–ridge system, featuring an equivalent barotropic structure with large geopotential height anomalies reaching the lower troposphere, weakens or blocks vapor transport and is ultimately responsible for the strongly varying spatial scales and orientations of rain belts. Significance Statement: A solid theoretical basis that variations in the EAWJ intimately covary with the location and orientation of rain belts means that understanding the relationships between the EAWJ’s zonal variations and the spatial features of monsoonal rain belts is conducive to better predicting the weather and climate over East Asia. We quantitatively explored the effects of EAWJ zonal variations on the position, orientation, and scale of rain belts and found that a tilted, wavy, or relatively flat pattern of the EAWJ strongly affected the rain belt spatial features by modifying the vapor transport trajectory. A zonally oscillating trough–ridge system, featuring an equivalent barotropic structure throughout the troposphere, is responsible for the varying spatial scale of rain belts.

The Yangtze River Delta (YRD), China’s main cultural and economic center, has become one of the most seriously polluted areas in the world with respect to nitrogen oxides (NO_x), owing to its rapid industrialization and urbanization, as well as substantial coal consumption. On the basis of nitrogen dioxide (NO₂) density data from ozone monitoring instrument (OMI) and ground-based observations, the effects of industrial fluctuations due to the financial crisis on local NO₂ pollution were quantitatively assessed. The results were as follows. (1) A distinct V-shaped fluctuation of major industrial products, thermal generating capacity, electricity consumption, and tropospheric NO₂ densities was associated with the global financial crisis from May 2007 to December 2009, with the largest anomalies 1.5 times more than standard deviations at the height of the crisis period from November 2008 to February 2009. (2) Among all industrial sectors, thermal power plants were mainly responsible for fluctuations in local NO₂ pollution during the crisis period. Thermal generating capacity had its greatest decrease of 12.10% at the height of the crisis compared with that during November 2007–February 2008, leading to local tropospheric NO₂ density decreasing by 16.97%. As the crisis appeased, thermal generating capacity increased by 29.63% from November 2009 to February 2010, and tropospheric NO₂ densities correspondingly increased by 30.07%. (3) Among all industrial sectors in the YRD, the thermal power sector has the greatest coal consumption of about 65.96%. A decline in thermal power of about 10% can induce a decrease of about 30% in NO_x emissions and NO₂ densities, meaning that a relative small fluctuation in industrial production can lead to a large decrease in tropospheric NO₂ densities over industrially developed areas like the YRD region. Since electricity is mainly obtained from local coal-burning thermal plants without NO_x-processing equipment, installing NO_x-removal devices for all thermal power plants is an important and feasible way of controlling local NO_x pollution at present.

Great difficulty in characterizing the spatial pattern and scale of regional surface urban heat islands (RSUHIs) over urban agglomerations is mainly attributed to the RSUHI extent exceeding urban boundaries and strong variations in the background climate state and land cover. A new method that successfully addresses these problems by applying the spatial similarity of the land surface temperature (LST) annual cycle in urban agglomerations is proposed to characterize the RSUHI spatial pattern and scale in the Yangtze River Delta of China. This method has good adaptability to complex terrain and climate variations and simultaneously identifies the RSUHI spatial pattern and scale. The RSUHI spatial extent averaged 3.7 × 10⁴ km² in 2003–2020, which is 1.5–2.0 times the urban extent, and had a fluctuating but increasing tendency. Rapid urbanization and the spatial pattern‐shifting LST anomalies were mainly responsible for the fluctuating RSUHI extent during 2003–2020.