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The monsoon holds great significance in Asian-Australian civilization. Recent studies realized the link between the monsoon onset and the seasonal migration of the Intertropical Convergence Zone (ITCZ). However, no clear ITCZ band is observed in the Asian-Australian sector due to the strong influence of topography. Instead, there exists a large-scale (∼1,500 km) tropical convective cell––a perennial system that we hereafter coin as the “intertropical convective cell (ITCC).” Using ERA5 reanalysis and satellite-based outgoing longwave radiation products, here we show by objective detection and tracking that the ITCC exhibits eight phases during its seasonal migration along the Asian-Maritime land bridge. Particularly, its sudden northward jump in boreal spring coincides well with the earliest (abrupt) onset of the Asian rainy season, while its equatorward retreat heralds the overall (gradual) monsoon withdrawal. These findings demonstrate the close link of the ITCC behavior to the spring-fall asymmetry of the monsoon. Dynamically, the off-equatorial ITCC features a monsoon regime with a cross-equatorial overturning circulation, differing markedly from its equatorial regime with two weak overturning cells on each side. Further budget analyses prove our hypothesis that the north-south charging gradient of the moist static energy determines the ITCC's spring-fall asymmetric propagation, illuminating the physical origin of the spring-fall asymmetry in the monsoon. Our results demonstrate the usefulness of the ITCC framework in understanding the Asian-Australian monsoon complexity in a fresh and holistic manner. The framework will facilitate monsoon diagnosis, modeling and subseasonal-to-seasonal forecasting in the Asian-Australian sector. © 2024 The Authors.

Understanding the present and future features of atmospheric rivers (ARs) is critical for effective disaster prevention and mitigation efforts. This study comprehensively assesses the performance of ARs in Phase 6 of the Coupled Model Intercomparison Project (CMIP6) models on both seasonal and interannual timescales within the historical period and investigates the future projection of ARs under different emission scenarios on a global scale. The multi-model mean results obtained using the PanLu detection algorithm consistently exhibit agreement with the observational AR climatology and capture interannual fluctuations as well as the relationships with large-scale drivers. The future projections reveal increased AR frequency, intensity, duration, and spatial extent and decreased landfall intervals with regional variations and seasonal fluctuations. Besides, the AR frequency increase will accelerate around the middle of the century, attributed to a non-linear rise in surface temperature. Furthermore, mid-latitude ARs are gradually shifting toward higher latitudes in both hemispheres under SSP585, with Greenland experiencing a substantial increase in AR frequency and AR-induced precipitation. The hydrological implications arising from more frequent ARs are manifested more prominently in AR-induced heavy precipitation (HP), with regions historically characterized by lower AR occurrence also receiving a higher percentage of precipitation from ARs. At last, an incremental decomposition highlights the dominant role of thermal effects and relatively limited contributions from dynamical effects in AR changes. Besides, the interplay between regionally divergent temperature amplification results in different dynamically driven AR responses across the globe. Understanding atmospheric rivers (ARs) is crucial for disaster prevention and mitigation. This study evaluates the performance of CMIP6 simulation on historical ARs on seasonal and interannual timescales, assesses their fu

The Indian monsoon is of utmost concern to agriculture, the economy, and the livelihoods of billions in South Asia. However, little attention has been paid to the possibility of distinct subseasonal episodes phase-locked in the Indian monsoon annual cycle. This study addresses this gap by utilizing the self-organizing map (SOM) method to objectively classify six distinct subseasonal stages based on the 850-hPa wind fields. Each subseasonal stage ranges from 23 to 90 days. The Indian summer monsoon (ISM) consists of three substages, the ISM-onset, ISM-peak, and ISM-withdrawal, altogether contributing to 82% of the annual precipitation. The three substages signify the rapid northward advance, dominance, and gradual southward retreat of southwesterlies from mid-May to early October. The winter monsoon also comprises three substages (fall, winter, and spring), distinguishable by the latitude of the Arabian Sea high pressure ridge and hydrological conditions. This study proposes two compact indices based on zonal winds in the northern and southern Arabian Sea to measure the winter and summer monsoons, respectively. These indices capture the development and turnabouts of the six SOM-derived stages and can be used for subseasonal monsoon monitoring and forecasts. The spring and the ISM-onset episodes are highly susceptible to compound hazards of droughts and heatwaves, while the greatest flood risk occurs during the ISM-peak stage. The fall stage heralds the peak season for tropical storms over the Arabian Sea and the Bay of Bengal. The annual start and end dates of the ISM-peak are highly correlated (0.6–0.8) with the criteria-based dates proposed previously, supporting the delineation of the Indian monsoon subseasonal features. © 2023 American Meteorological Society.

Tropical cyclone (TC) stalling has been widely perceived to yield a greater threat of flooding. Understanding the effect of stalling and its long-term trends will enhance adaptation strategies to cyclone-associated disasters. We show that stalling prolongs western North Pacific TCs to live 24 hr longer and produces 23% greater 24-hr rainfall accumulations in a more concentrated area, which is more prominent over a 72-hr rolling period. More importantly, we discover a northward migration of TC stalling (∼0.7°N decade−1) over 1979–2020, bringing increasingly higher flood risks to the highly-populated East Asian coast. Further diagnoses suggest the role of binary cyclone interactions in TC stalling, whereby the second larger TC slows down the smaller one by weakening the northwestward steering flows. The northward shift of TC stalling can be explained by a similar trend in binary TC cases and environmental fields. Our findings are robust across various best track and precipitation products.

This study addresses how moisture in continental precipitation is recycled globally from a moisture-tracking perspective. Using a state-of-the-art three-dimensional Lagrangian model and optimized water accounting diagnostics, we complete a 40-year (1971-2010) tracking of moisture from continental precipitation in the present-day climate. Climatologically, we conclude that 62% of continental precipitation stems from evapotranspiration through Lagrangian tracking––a measure is known as the global “continental precipitation recycling (CPR)” ratio. The result bridges the long-standing gap between the explicit (i.e., moisture trajectory-based) and implicit (i.e., water budget-based) estimates of the global CPR ratio in the literature. On the 1° grid scale, non-local terrestrial sources dominate precipitation in almost 70% of the land areas, most prominent in the continental interior. The CPR ratio consistently exhibits a contrasting seasonality between the mid-to-high latitudes and monsoon regions worldwide, from which two kinds of moisture source-regulated hydroclimate are generalized. Given the importance of CPR, we identify terrestrial source hotspots for continental precipitation that deserve careful governance. Using the backward “WaterSip” and a newly proposed forward “WaterDrip” diagnostics, we conceptualize and quantify two important types of cascading moisture recycling (CMR), whereby the moisture from an earlier source precipitates over an intermediate source and then re-evaporates to sustain precipitation further downwind. The watershed-scale CMR metrics uncover the interdependence among the regional water cycles. Findings here advance the scientific understanding of the atmospheric water cycle as seen through Lagrangian tracking, and offer insights into transboundary watershed management and land-use planning to improve freshwater sustainability.

Eastern China is perennially hit by mesoscale convective systems (MCSs), yet it remains an open question as to whether and how their general properties change throughout the annual cycle. By leveraging high-resolution satellite observations and a hybrid tracking algorithm, we present a 20-year (2001–2020) climatology of MCSs over eastern China during eight subseasonal-to-seasonal (S2S) monsoon stages. MCSs contribute up to 50% of the stage-total precipitation and over 60% of the rainband-zone precipitation during the Pre-Meiyu and Meiyu episodes, and their contributions remain non-trivial during the transition seasons. We discover two contrasting regimes of MCSs that alternate immediately upon the Pre-Meiyu and the Fall onsets. The wintertime regime features fast-propagating shallow systems initiated at night in a strongly sheared and dry environment. The summertime regime, instead, features an outbreak of MCSs in the south, where the systems often initiate in the afternoon and propagate 2–3 times slower than the cold-season ones. Based on multivariate clustering analysis, the nighttime MCSs that dictate the winter stages often initiate over a deep nocturnal boundary layer with moist rear inflows upgliding above it. In contrast, the afternoon-initiated MCSs under the summertime regime feature a pronounced convective available potential energy (CAPE) "tongue" and upslope flows in their southeast quadrant. The southwesterly moist ascending flows are likely to shallow the convective inhibition at the tip of the CAPE tongue and facilitate the intense updrafts of the MCSs. Findings here may offer insights into S2S weather prediction and facilitate agricultural and water management throughout the year. © 2022 The Authors.

The monsoons are often viewed as sea-breeze circulations driven by solar radiations and land-sea thermal contrast, and modified by compressibility and rotation effects. This highly idealized model is recently improved by considering a fully coupled land-ocean-atmosphere nature of the monsoon. In East Asia, the monsoons are further shaped by the unique geographical setting and weather dynamics. During the Meiyu season, a quasi-stationary monsoon front stretching thousands of kilometers wide perennially causes torrential rains and severe floods. This brings us to a few core questions: Where did all those water vapors come from when apparently local evaporation does not suffice to supply all of them? How can we understand the monsoons better from the perspective of moisture? This thesis contains four main chapters address the above questions. By backtracking the moisture two weeks before precipitation using a reanalysis-driven semi-Lagrangian model, we established a moisture source-receptor (SR) network for multiple regions in East Asia during the warm season. The network reveals an equal (or even greater) importance of non-local terrestrial sources compared to the oceanic sources. The network also demonstrates pronounced intraseasonal variabilities and is further shaped by the El Niño Southern Oscillation. Four main moisture corridors are found to sustain the heavy monsoon rainbands in East Asia. Interesting circumglobal wave trains attributable to the pathways are discovered at a two-week lead time. Applying a more sophisticated 3-D Lagrangian moisture tracking model on the global scale, we find that 62% of continental precipitation is sustained by terrestrial evaporation. The world’s leading moisture sources and a new concept of cascading moisture recycling are also proposed. The final study discovers a dual regime of MCSs closely tied to the monsoon annual cycle and reveals the prevailing environments for convective initiation under the two regimes.

Methods to define the East Asian monsoon usually involve ad hoc and diverse criteria. This study adopts a simple and coherent approach based on the self-organizing map to systematically derive the monsoon annual cycle based on 850-hPa wind fields. The derived onset dates in the warm season agree well with the literature despite lacking documentation for winter-season stages. Linear regression suggests an inverse relationship between the length of the Spring (Meiyu) stage and that of the Pre-Meiyu (Mid-summer) stage, suggesting predictability of the Meiyu and Fall onsets. The Aleutian Low, the western North Pacific subtropical high, and the upper-level westerlies play important roles in the Spring, Pre-Meiyu, and Meiyu onsets. Observations reveal strong rain belt events form right after the monsoonal wind onsets in the warm season. The proposed approach to deriving monsoon stages and onsets would be useful for monsoon climate studies and operational monsoon diagnosis and forecasting. © 2020. The Authors.

Methods to define the East Asian monsoon usually involve ad hoc and diverse criteria. This study adopts a simple and coherent approach based on the self-organizing map to systematically derive the monsoon annual cycle based on 850-hPa wind fields. The derived onset dates in the warm season agree well with the literature despite lacking documentation for winter-season stages. Linear regression suggests an inverse relationship between the length of the Spring (Meiyu) stage and that of the Pre-Meiyu (Mid-summer) stage, suggesting predictability of the Meiyu and Fall onsets. The Aleutian Low, the western North Pacific subtropical high, and the upper-level westerlies play important roles in the Spring, Pre-Meiyu, and Meiyu onsets. Observations reveal strong rain belt events form right after the monsoonal wind onsets in the warm season. The proposed approach to deriving monsoon stages and onsets would be useful for monsoon climate studies and operational monsoon diagnosis and forecasting. © 2020. The Authors.

The East Asian Summer Monsoon (EASM) is a crucial monsoon system that profoundly influences the summer climate in Southeast China (SEC). Classification of monsoon rainfall patterns is vital to physical diagnosis, rainfall prediction and identification of sites that are prone to rainfall-triggering floods. With the great endeavors on understanding the complexity of the EASM in the past decades, the traditionally accepted rainfall patterns in SEC and the relevant analyses appear outdated or even inadequate. Having highly-improved observations at hand helps update the monsoon rainfall patterns in SEC and the potential predictability. The present study employs a nonlinear neural network classification technique, the Self-organizing map (SOM), to identify the rainfall patterns in SEC based on gauge data. Three distinct rain belts over the Huai River basin (HRB), lower Yangtze River basin (LYRB) and South Coast region (SCR) are found. Their subseasonal variability highly agrees with the stepwise progression of the East Asian Summer Monsoon (EASM) front in space and time. Analysis reveals that precipitation in the SCR and HRB rain belts undergo a regime shift after the mid-1990s, whereas the 1990s is the most active decade for the LYRB rain belt. These systematic changes are in abreast with similar changes in EASM and other climate events documented in the literature. Additionally, a SOM-based algorithm is developed to further divide gauge stations into three groups featuring homogeneous rain belt patterns. Promising predictability of group-averaged daily rainfall is then achieved, with about 39% to 50% of the total variance explained by circulation-informed regression models, verified by both cross-validation and blind prediction. Through further diagnosis in the useful predictors, the western North Pacific subtropical high, blocking high anomalies over northeast China and the upper-level divergence over SEC, are found to best explain the variability of the rain belts. Th

There has been growing interest in studying precipitation recycling and identifying relationships between moisture sources and receptors. The network built upon the relationships is crucial for the knowledge of the atmospheric water cycle, weather prediction, and adaptation to hydroclimatic disasters. This study aims to provide an interesting perspective of a Source-to-Receptor (SR) network to study the dynamics of the East Asian Summer Monsoon (EASM). By prescribing 24 sources and 6 EASM subregions, the SR network during the wet season is quantified using the two-dimensional physically-based Dynamical Recycling Model (DRM). Results reveal that in addition to oceanic sources, land sources including the often-overlooked plateau regions play an important role in supplying moisture to most EASM subregions. A seesaw relationship of the Indian Ocean/South Asia sector from April to June and the Pacific Ocean/East Asia sector from July to September is evidenced in the intraseasonal variation of the SR network for EASM subregions including South China coast and Taiwan, Yangtze River basin, South Japan and Korean Peninsula. Conversely, weaker intraseasonal variation is seen in the SR network for the Yellow River basin and North China. During heavy rainfall days, the zonal oscillation of western North Pacific Subtropical High (WNPSH) is deemed crucial to modulate the SR network through enhanced contributions from Bay of Bengal, Indochina, Indian subcontinent and Southwest China (the Philippine Sea and western North Pacific) during the positive (negative) phase. Coupled circulations such as two distinct pressure dipoles and coherent upper-level wave trains from mid-latitudes are responsible for bridging the moisture routes. Lastly, preceding winter/springtime El Niño is likely associated with the enhanced (weakened) moisture supply from the southwesterly (Pacific Ocean) sources. Longer-term variabilities such as the Pacific Decadal Oscillation is also considered influential to

This study advances the use of the Self‐organizing Map (SOM) to identify the summer monsoon rainfall patterns over Southeast China (SEC), using 272 gauge records from May to August. Three distinct rain belts over the Huai River basin (HRB), the Lower Yangtze River basin (LYRB) and the South Coast region (SCR) are found. Their subseasonal variability strongly agrees with the northward progression of the East Asian Summer Monsoon (EASM) front in a stepwise fashion. We find that precipitation in the SCR and HRB rain belts exhibit significant changes in the mid‐1990s, while the 1990s is the most active decade for the LYRB rain belt. Promising predictability of average daily rainfall over these three regions is obtained, with about 39% to 50% of the total variance explained by the circulation informed regression models. Both leave‐one‐year‐out cross‐validation and blind prediction verify the regression performance. The western North Pacific Subtropical High phases, mid‐latitude blocking high anomaly over northeast China and upper‐level divergence in SEC are found to best explain the variability of the rain belts. The newly proposed Russia‐China wave patterns (western/central Russia → north of Tibetan Plateau → SEC) and teleconnection between the El Niño‐Southern Oscillation and the rain belts also offer additional predictability. Findings from this work may advance the understanding of the EASM rain belts, and offer insights to the source of bias for numerical simulations of daily summer monsoon rainfall in the region.

This study advances the use of the Self‐organizing Map (SOM) to identify the summer monsoon rainfall patterns over Southeast China (SEC), using 272 gauge records from May to August. Three distinct rain belts over the Huai River basin (HRB), the Lower Yangtze River basin (LYRB) and the South Coast region (SCR) are found. Their subseasonal variability strongly agrees with the northward progression of the East Asian Summer Monsoon (EASM) front in a stepwise fashion. We find that precipitation in the SCR and HRB rain belts exhibit significant changes in the mid‐1990s, while the 1990s is the most active decade for the LYRB rain belt. Promising predictability of average daily rainfall over these three regions is obtained, with about 39% to 50% of the total variance explained by the circulation informed regression models. Both leave‐one‐year‐out cross‐validation and blind prediction verify the regression performance. The western North Pacific Subtropical High phases, mid‐latitude blocking high anomaly over northeast China and upper‐level divergence in SEC are found to best explain the variability of the rain belts. The newly proposed Russia‐China wave patterns (western/central Russia → north of Tibetan Plateau → SEC) and teleconnection between the El Niño‐Southern Oscillation and the rain belts also offer additional predictability. Findings from this work may advance the understanding of the EASM rain belts, and offer insights to the source of bias for numerical simulations of daily summer monsoon rainfall in the region.

The East Asian Summer Monsoon (EASM) is a crucial monsoon system that profoundly influences the summer climate in Southeast China (SEC). Classification of monsoon rainfall patterns is vital to physical diagnosis, rainfall prediction and identification of sites that are prone to rainfall-triggering floods. With the great endeavors on understanding the complexity of the EASM in the past decades, the traditionally accepted rainfall patterns in SEC and the relevant analyses appear outdated or even inadequate. Having highly-improved observations at hand helps update the monsoon rainfall patterns in SEC and the potential predictability. The present study employs a nonlinear neural network classification technique, the Self-organizing map (SOM), to identify the rainfall patterns in SEC based on gauge data. Three distinct rain belts over the Huai River basin (HRB), lower Yangtze River basin (LYRB) and South Coast region (SCR) are found. Their subseasonal variability highly agrees with the stepwise progression of the East Asian Summer Monsoon (EASM) front in space and time. Analysis reveals that precipitation in the SCR and HRB rain belts undergo a regime shift after the mid-1990s, whereas the 1990s is the most active decade for the LYRB rain belt. These systematic changes are in abreast with similar changes in EASM and other climate events documented in the literature. Additionally, a SOM-based algorithm is developed to further divide gauge stations into three groups featuring homogeneous rain belt patterns. Promising predictability of group-averaged daily rainfall is then achieved, with about 39% to 50% of the total variance explained by circulation-informed regression models, verified by both cross-validation and blind prediction. Through further diagnosis in the useful predictors, the western North Pacific subtropical high, blocking high anomalies over northeast China and the upper-level divergence over SEC, are found to best explain the variability of the rain belts. Th