The unprecedented and long-lasting abnormal monsoon rainfall attacked Pakistan in the summer of 2022, causing severe flooding. This study investigated the sub-seasonal characteristics and mechanisms of this distinctively extreme precipitation event. The historical rainfall in July and August and extreme precipitation mainly occurred in northern Pakistan. Both the monthly rainfall in July and August 2022 and the extreme precipitation during the summer were far exceeding the historical record and involved unique spatial distribution. The rainfall in July 2022 is nationwide and mainly located in northern Pakistan, while the rainfall in August and extreme precipitation occurred in southern Pakistan. Different physical processes are responsible for the precipitation in July and August 2022. In July, the South Asian high (SAH) and Iranian high extended eastward. Meanwhile, the anticyclonic circulation anomalies occurred in northwestern Pakistan and the easterly winds enhanced in the south side of the Tibetan Plateau (TP), which strengthened water vapor transporting from the Bay of Bengal and cooperated with the cyclonic system over the Arabian Sea to enhance the precipitation over Pakistan. In August, the SAH further extended eastward and the Western Pacific Subtropical High extended westward to the TP. Meanwhile, the European blocking (EB) developed, and a deep trough appeared over northwestern Pakistan. This weakened the easterly flow along southern TP but enhanced the southerly flow accompanying the cyclone over the Bay of Bengal and the Arabian Sea, and thus guided the water vapor transporting to southern Pakistan and enhanced the precipitation. The extreme precipitation in July was mainly attributed to the unusually strong Indian monsoon, while the extreme precipitation in August was the result of a combination of the Indian monsoon and EB. The study provided important information about extreme precipitation in Pakistan, which will help policymakers take measures to deal with the effects of flooding.

Extreme rainfall events are becoming increasingly severe under a warming climate. North China has experienced several catastrophic rainfall events, of which the rainstorm in 2023 was particularly severe inducing unprecedented damage. Since 1980, the neighboring Mongolian Plateau (MP) has been warming at a rate three times the global average, faster than the surrounding regions. Whether a link exists between extreme rainfall in North China and the fast MP warming is unknown. Here, using global variable‐resolution atmospheric model with convection‐permitting capability over North China, we find the rapid warming trends, particularly over the MP, are highly conducive to extreme rainfall over North China. In the 2023 case, the fast MP warming induced an anomalous terrestrial high, which in the Western North Pacific Subtropical High created a strong high‐pressure system over North China. This system obstructed northeastward movement of Typhoon Doksuri, concentrating moisture supply which prolonged and intensified the extreme.

Air pollution is a severe environmental problem in the Indian subcontinent. Largely caused by the rapid growth of the population, industrialization, and urbanization, air pollution can adversely affect human health and environment. To mitigate such adverse impacts, the Indian government launched the National Clean Air Programme (NCAP) in January 2019. Meanwhile, the unexpected city-lockdown due to the COVID-19 pandemic in March 2020 in India greatly reduced human activities and thus anthropogenic emissions of gaseous and aerosol pollutants. The NCAP and the lockdown could provide an ideal field experiment for quantifying the extent to which various levels of human activity reduction impact air quality in the Indian subcontinent. Here, we study the improvement in air quality due to COVID-19 and the NCAP in the India subcontinent by employing multiple satellite products and surface observations. Satellite data shows significant reductions in nitrogen dioxide (NO₂) by 17% and aerosol optical depth (AOD) by 20% during the 2020 lockdown with reference to the mean levels between 2005–2019. No persistent reduction in NO₂ nor AOD is detectable during the NCAP period (2019). Surface observations show consistent reductions in PM_2.5 and NO₂ during the 2020 lockdown in seven cities across the Indian subcontinent, except Mumbai in Central India. The increase in relative humidity and the decrease in the planetary boundary layer also play an important role in influencing air quality during the 2020 lockdown. With the decrease in aerosols during the lockdown, net radiation fluxes show positive anomalies at the surface and negative anomalies at the top of the atmosphere over most parts of the Indian subcontinent. The results of this study could provide valuable information for policymakers in South Asia to adjust the scientific measures proposed in the NCAP for efficient air pollution mitigation.

The 2022 floods in Pakistan resulted in severe losses and garnered global attention. This study aims to enhance the understanding of extreme precipitation (EP) events in Pakistan by examining the characteristics and mechanisms behind the persistent EP during summer, utilizing daily precipitation data from the Climate Prediction Center (CPC). Results showed that the monsoon precipitation in 2010, 2020 and 2022 are the highest three years on record. Notably, these peak events in 2010 (concentrating in the north) and 2022 (concentrating in the south) spanned from July through August. Conversely, the extreme precipitation in August 2020 was concentrated in northern Pakistan. For the circulation patterns, the intensification of the South Asian High and the western Pacific subtropical high with a strong Indian monsoon is a unifying feature, but the Iranian high and monsoon low-pressure system on the south of Pakistan was different. Additionally, the EP in July 2010 and August 2022 were also influenced by the teleconnection associated with European Blocking. La Niña events and the negative-phase Indian Ocean Dipole (IOD) also played a role in affecting summer EP, with the strongest La Niña occurring in 2010 and a notable triple-dip La Niña coinciding with a significant negative IOD phase in 2022. La Niña contributed to the formation of an anomalously strong anticyclone over the northwest Pacific and easterly winds along the southern Himalayas, impacting moisture transport to Pakistan. Conversely, the negative IOD phase amplified EP in Pakistan by enhancing the northward movement of convective systems and westerly winds over the Indian Ocean. Furthermore, reduced snow cover on the Tibetan Plateau in the springs of 2010 and 2022 likely induced a stronger thermal dynamical effect, acting as a heat source in summer and increasing precipitation in Pakistan.

Sudden turn from drought to flood (STDF) is a unique representation of intra-seasonal extreme events and occurs frequently. However, it is notoriously difficult to represent in climate simulations due to the accumulation of model errors. This study uses a regional climate model (RCM) with different initialization and nudging schemes to explore effective approaches for capturing a STDF event. Results show that the conventional continuous integration with single initialization cannot reproduce the STDF event, while nudging or re-initialization can. Furthermore, spectral nudging and re-initialization outperform the conventional continuous simulation in reproducing precipitation features, but grid nudging induces the largest biases for precipitation though it has the smallest biases for other meteorological elements. Scale separation analysis shows that the large-scale features of the conventional continuous simulation drift far from the actual fields and force erroneous small-scale features, whereas the nudging and re-initialization successfully prevent the model from drifting away from the forcing fields at large-scales. The different performance for simulating precipitation among spectral nudging, re-initialization and grid nudging can be attributed to that the former two methods generate their own small-scale information via the RCM, while grid nudging over-suppresses the small-scale information while retaining the large-scale features. The difference in small-scale features affects the simulation of different moisture fluxes and convergences, as well as clouds, and then results in diverse precipitation. These results illustrate that both the consistency with large-scale features and the local variability from small-scale features are both robust factors for reproducing precipitation features during extreme events using RCMs.

The Three-River Source Region (TRSR), the core of the “Asian Water Tower”, plays a critical role in Asian water cycle and sustains the water security of billions downstream. Using the self-organizing map method, this study identifies four synoptic patterns (SP1–SP4) during the wet seasons during 1979–2020 over TRSR and investigates the precipitation characteristics, physical mechanisms, and contributions to the total precipitation increase under different synoptic patterns. Results show that SP2 dominates in occurrence frequency and accounts for 36.41% of total precipitation. Although less frequent, SP1 and SP4 produce higher rainfall intensities, accounting for 28.25% and 19.90% of the total precipitation, respectively. SP3 has the lowest frequency and weakest precipitation, contributing only 15.44%. Mechanistically, SP1 features strong moisture transport and uplift linked to deep monsoon trough and westerly ridge, yielding the highest rainfall. SP4, influenced by a strong westerly trough combined with a monsoon trough, produces the second-highest rainfall. In contrast, SP2 and SP3 are linked to weaker monsoon activity and moisture supply, leading to limited precipitation. Trend analysis reveals that the total precipitation increase is largely driven by SP2 and SP3 via increased occurrence frequency and precipitation intensity, the latter fueled by increased precipitable water and enhanced upward motion. Conversely, SP4 exerts a negative contribution, as its declining frequency and precipitation intensity are driven by reduced moisture. This study provides a circulation-pattern-based framework for understanding the heterogeneous wetting of TRSR, offering essential guidance for interpreting past changes, improving future projections, and informing regional water management and climate adaptation.