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As wind‐borne migration of insects is strongly influenced by atmospheric circulation and weather systems, the relationships between insect population abundance and meteorological conditions are substantial. The brown planthopper (BPH), Nilaparvata lugens (Stål), is one of the major wind‐borne insects hampering rice production in Asia, and its migration is significantly influenced by the Asian monsoon, a main component of the Asian climate system. However, the degree and mechanisms of the effects of monsoon on BPH migration have been little studied. In this paper, the effect of the Asian monsoon on the northward migration of BPH from the Indochina Peninsula to northern South China (NSC) was investigated based on the BPH light‐trap data and meteorological data for 39 years. The results show that the level of BPH migration in May could indicate the degree of annual pest outbreaks in NSC and that the southeast monsoon was more critical in this northward migration than the previously recognized southwest monsoon. The significance of the southeast monsoon stemmed from the strong effect of South China Sea subtropical high on BPH migration under a unique weather system distribution, the Polar low–Continental low–West Pacific subtropical high pattern. Furthermore, based on the key areas of migration obtained from the composite analysis, the multivariable linear regression prediction model could effectively predict the occurrence of BPH in NSC. These results indicate the importance of interactions between monsoons during BPH northward migration, which reflects the complex relationship between BPH migration and atmospheric motion. [ABSTRACT FROM AUTHOR]

This paper reviews progress in the study of Tibetan Plateau (TP) climate dynamics over the past decade. Several theoretical frameworks, including thermal adaptation and the TP sensible heat (SH) driving air-pump, have been developed to identify the mechanisms responsible for the circulation anomaly produced by thermal forcing of the TP. Numerical simulations demonstrate that the thermal effects of large-scale orography, including the Tibetan and Iranian Plateaus (TIP), are crucial for the formation of the East Asian and South Asian summer monsoons (SASM) because the surface SH of the TIP is the major driver of the water vapor transport required for the genesis of the north branch of the SASM.The large-scale orography of the TP affects the Asian climate through thermal forcing in spring and summer, and mechanical forcing in winter. The TP forcing can also influence the Asian summer monsoon (ASM) onset over the Bay of Bengal (BOB) by enhancing the BOB warm pool at the surface and by modulating the South Asian High (SAH) in the upper troposphere. On intra-seasonal timescales, the TP thermal forcing significantly modulates spring rainfall in southern China and generates the biweekly oscillation of the SAH in summer. Despite climate warming, the atmospheric heat source over the TP, particularly the spring SH, exhibits a clear weakening trend from the 1980s to 2000s. This weakening of the spring SH contributed to the anomalous 'dry in the north' and 'wet in the south' rainfall pattern observed over East China. Also discussed are challenges to further understanding the mechanism of TP forcing on the multi-scale variability of the ASM. [ABSTRACT FROM AUTHOR]

The simulation skill of the perturbed parameter ensemble (PPE) of HadGEM3‐GC3.05 on the mean climate pattern of the Asian summer monsoon (ASM) is evaluated in this study. The sensitivities of the model bias to the perturbed parameters are investigated based on metrics. The results show that the PPE mean (PPE‐20M) could effectively capture the general ASM precipitation and wind patterns, with a correlation coefficient of 0.78. PPE‐20M mainly shows positive precipitation biases over the tropical western Pacific, southern slope of the Tibetan Plateau, Indochina Peninsula, and South China and negative precipitation biases over the Indian continent and Bay of Bengal. The magnitude of the precipitation biases is more sensitive than its pattern to the variation of the perturbed parameters. Four parameters (ent_fac_dp, qlmin, ps_cloud‐ph, and psm) are found to be crucial for simulating the ASM precipitation intensity, and their combined effects are related to the simulated precipitation biases. Plain Language Summary: The simulation of the Asian summer monsoon (ASM) has attracted much attention in recent decades. However, state‐of‐the‐art coupled models still show similar systematic biases when simulating monsoon precipitation from CMIP3 to CMIP6. Recently, a perturbed parameter ensemble (PPE) method has been applied in the development of HadGEM3‐GC3.05 with the aim of improving the overall simulation skill of the coupled model. The PPE can also be used to understand the related physical processes in the model simulations. Thus, in this study, we aim to evaluate the simulation skills of PPE on the mean climate distributions of ASM. Four parameters were found to be the most critical in the precipitation simulations, which could be potential tunable parameters to reduce the biases of precipitation intensity over the monsoon regions. This study provides possible pathways to reduce model bias that could benefit the model development community. Key Points: The perturbed parameter ensemble mean captures the climate pattern of the Asian summer monsoon (ASM) but mainly overestimates precipitation over the western PacificFour parameters (ent_fac_dp, qlmin, ps_cloud‐ph, and psm) are crucial for simulating ASM precipitation in coupled runThe joint effect of these parameters, especially the deep entrainment amplitude, are dominant control for the bias in the western Pacific [ABSTRACT FROM AUTHOR]

To explore the history of the changes in monsoon precipitation and their driving mechanisms in the context of global warming, climatology studies using tree-ring stable oxygen isotopes (δ18O) were carried out in Shanxi Province, China. Based on a tree-ring δ18O series from Pinus tabulaeformis Carr. on Heng Mountain, a 230-year June–July precipitation sequence from 1784 to 2013 AD was reconstructed that explained 45% of the total variance (44% after adjusting the degrees of freedom). The reconstructed sequence captured the characteristics of the variations in precipitation. Periods of drought occurred mainly in 1820–1840 AD, 1855–1865 AD, 1895–1910 AD, 1925–1930 AD, and 1970–1995 AD, and wet periods occurred mainly in 1880–1895 AD, 1910–1925 AD, and 1935–1960 AD. The dry and wet years in the precipitation reconstruction corresponded well to the years in which disaster events were documented in historical records. A spatial correlation analysis with Climatic Research Unit (CRU)-gridded precipitation data indicated that the reconstructed precipitation provided good regional representation and reflected large-scale June–July precipitation changes in northern China. In addition, the reconstructed precipitation sequence was also significantly correlated with the dry and wet index (DWI) and other tree-ring dry/wet reconstructions from the surrounding areas. The correlation between the reconstructed precipitation and the Asian monsoon index showed that the precipitation can indicate the intensity of the Asian summer monsoon. Moreover, a significant negative correlation was found between the El Niño–Southern Oscillation (ENSO) and the reconstructed precipitation. At the decadal scale, the negative phase of the Pacific Decadal Oscillation (PDO) and the positive phase of the Atlantic Multidecadal Oscillation (AMO) may co-promote summer precipitation in the study area. [ABSTRACT FROM AUTHOR]

In early summer 2020, the Meiyu‐Baiu rainfall was markedly enhanced, triggering devastating floods in Japan and central China. We examined the underlying processes using a climate model and analysis. The enhanced Meiyu‐Baiu rainfall was reasonably predicted by the climate model initialized at the end of April. The sensitivity experiment indicated that Indian Ocean (IO) warming enhanced the Meiyu‐Baiu rainfall. Moreover, we found that the warm IO condition can be traced back to the super Indian Ocean Dipole (IOD) in 2019. The IO warmth was influenced by successive processes: record strong downwelling Rossby waves excited by the IOD and tripole sea surface temperature anomalies in the tropical IO‐western Pacific, their arrival to the southwestern IO in spring, and associated modulation of monsoon flow. The results suggest that the seasonal predictability of the Meiyu‐Baiu rainfall in 2020 originated from the super IOD. Plain Language Summary: In early summer 2020, Japan and central China suffered from serious floods due to torrential rainfall associated with the intensified Meiyu‐Baiu front, which extends from central China to southern Japan. The results of climate model simulations indicated that a warm condition of the Indian Ocean (IO) was an underlying condition for the enhanced rainfall. We found that the warm IO condition can be traced back to the strong Indian Ocean Dipole (IOD) episode in 2019, which featured a pair of colder‐than‐normal and warmer‐than‐normal ocean temperatures west of the Sumatra coast and in the western IO, respectively. This IOD contributed to the IO warming in the following seasons through oceanic dynamics and monsoon modulation. Key Points: The markedly enhanced rainfall in the Meiyu‐Baiu frontal zone in early summer 2020 was associated with the warm IO conditionThe warm IO condition can be traced back to the super IOD event in 2019Ocean dynamics and associated modulation of monsoon flow in the IO sector facilitated IO warming [ABSTRACT FROM AUTHOR]

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