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The results from this study indicate that N. lugens has the potential to develop high resistance to buprofezin. A resistance management program with rotation of buprofezin and other pesticides may efficiently delay or slow down resistance development in the insect. Further investigation is also necessary to understand the resistance mechanisms in N. lugens.

This study characterizes the intraseasonal variability (ISV) in the Southeastern United States (SE US) rainfall in boreal summer and delineates the associated dynamical processes featuring three-way interactions among the SE US rainfall, the central US low-level jet (LLJ), and the North Atlantic subtropical high (NASH). The analysis reveals that the ISV of the SE summer rainfall peaks at the 10‒20-day timescales. The physical mechanisms for the three-way interactions on the 10‒20-day timescales are proposed. When the NASH attains a minimum strength, the reduced size of the NASH is accompanied with an eastward retreat of the western ridge of the NASH, leading to a decrease in the zonal pressure gradient and consequently a weakening of the LLJ 1 day after. The weakened LLJ and the eastward-shifted NASH western ridge induces anomalous cyclonic circulation over the SE US, moves preferred regions of moisture convergence from central US to the SE US, and 3 days later the SE US rainfall attains its maximum strength. The excessive latent heating associated with the enhanced SE US rainfall excites an anomalous anticyclone northeast of the rainfall region, resulting in an increase in the NASH intensity that peaks 2 days after the maximum SE US rainfall. The NASH subsequently expands with its western ridge moving westward, zonal pressure gradient restored, and LLJ strength recovered. An anomalous anticyclone then emerges over the SE US and suppresses rainfall, marking the shift from an intraseasonal wet phase to dry phase in this region. A more rigorous proof of these causalities demand carefully designed numerical experiments and further statistical analysis in future. Our results suggest that improved prediction of SE US summer rainfall across intraseasonal scales depends critically on the model representation of the three-way coupling among the NASH, the central US LLJ, and the SE US rainfall.

Because of its dense population, extreme precipitation, in particular hourly extreme precipitation (HEP), is receiving increasing attention from both academic and public bodies in eastern China. Based on a continuous 50‐year record of hourly precipitation and reanalysis data, we show here for the first time that changes in the HEP occurrence are dominated by changes in the duration of the Meiyu front system. Further analyses reveal that greater occurrence of HEP in northeastern China, the lower reach of Yangtze River, and southern China during the warm season is largely due to a longer duration of the post‐Meiyu I stage when Meiyu front stays in northern China and meridional circulation dominates the eastern coastal area of China. These results improve our understanding of the changing behavior of extreme rainfall in China and shed light on the prevention of flash floods.

Unforced variability in global mean surface air temperature can obscure or exaggerate global warming on interdecadal time scales; thus, understanding both the magnitude and generating mechanisms of such variability is of critical importance for both attribution studies as well as decadal climate prediction. Coupled atmosphere‐ocean general circulation models (climate models) simulate a wide range of magnitudes of unforced interdecadal variability in global mean surface air temperature (UITglobal), hampering efforts to quantify the influence of UITglobal on contemporary global temperature trends. Recently, a preliminary consensus has emerged that unforced interdecadal variability in local surface temperatures (UITlocal) over the tropical Pacific Ocean is particularly influential on UITglobal. Therefore, a reasonable hypothesis might be that the large spread in the magnitude of UITglobal across climate models can be explained by the spread in the magnitude of simulated tropical Pacific UITlocal. Here we show that this hypothesis is mostly false. Instead, the spread in the magnitude of UITglobal is linked much more strongly to the spread in the magnitude of UITlocal over high‐latitude regions characterized by significant variability in oceanic convection, sea ice concentration, and energy flux at both the surface and the top of the atmosphere. Thus, efforts to constrain the climate model produced range of UITglobal magnitude would be best served by focusing on the simulation of air‐sea interaction at high latitudes.