Juan Li

Drivers of multi‐centennial global monsoon variability remain debated, with internal variability poorly understood. Using nine CMIP6 pre‐industrial millennial simulations, we find that the Atlantic meridional overturning circulation (AMOC) correlates with multi‐centennial fluctuations in the Afro‐Asian summer monsoon (AfroASM), which includes the North African (NAFSM) and Asian (ASM) summer monsoons, but shows minimal correlation with other regional monsoons. Increased AMOC variability may amplify AfroASM fluctuations and strengthen NAFSM‐ASM coherence. Precipitation sensitivity to AMOC reaches 0.5%/Sv (ASM) and 1.57%/Sv (NAFSM). Mechanistically, we suggest that AMOC could influence NAFSM via Atlantic meridional temperature gradient and ASM via land‐sea thermal contrast and NAFSM's incursion into the Arabian Sea, altering rainfall through atmospheric circulation. Conversely, AMOC does not significantly alter temperature gradients in other regional monsoons, explaining minimal rainfall responses. These results highlight internally generated AMOC variability as critical factor for understanding Afro‐Asian hydroclimate variability.

In the summer of 2022, the Yangtze River basin (YRB) experienced the most intense and prolonged extreme high-temperature event since 1961, featured by three successive episodes of 18–29 June (P1), 6–17 July (P2), and 3–26 August (P3). An assessment of two operational subseasonal-to-seasonal models reveals that the spatial pattern of surface air temperature (SAT) anomalies over the YRB can be predicted with lead times of 11–12, 8–9, and 15–20 days for P1, P2, and P3, respectively. However, both models underestimate the intensity of maximum SAT anomalies, especially during P3. In P1 and P2, both models fail to reproduce the propagation of Eurasian transient waves at the lead time of 15 days, hindering the development of high-pressure anomalies over East Asia. In P2, additional biases in reproducing the boreal summer intraseasonal oscillation (BSISO)-like convection anomalies promote the further northward shift of the high-pressure anomaly. These model errors result in poor simulations of local diabatic heating, which is the primary contributor to SAT anomalies over the YRB in P1 and P2. In P3, well-reproduced mid- to high-latitude Eurasian transient waves and BSISO-like convection are favorable for simulating SAT anomalies over YRB. Nonetheless, the underestimation of regional adiabatic heating associated with vertical motion in P3 limits the skill in predicting the intensity of SAT anomalies over the YRB. Thus, the ability of accurately capturing the two predictability sources of Eurasian transient waves and tropical Indo-Pacific convections is the key to improve the subseasonal prediction of this prolonged extreme high-temperature event over the YRB. Significance Statement: A record-breaking prolonged extreme high-temperature event occurred over the Yangtze River basin (YRB) in the summer of 2022, featuring three distinct subseasonal episodes. Evaluation of two subseasonal-to-seasonal models from the European Centre for Medium-Range Weather Forecasts and China Meteorological Administration shows that the distribution patterns of surface air temperature anomalies over the YRB can be predicted with lead times of 11–12 days for P1, 8–9 days for P2, and 15–20 days for P3, whereas the intensity of maximum anomalies is consistently underestimated. Mid- to high-latitude Eurasian transient waves and tropical Indo-Pacific convections are identified as key sources of subseasonal predictability for this extreme event. These results offer valuable insights for improving subseasonal prediction skills for future extreme high-temperature events over the YRB.

Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives of billions who depend on or are affected by monsoons, as it is essential for the water cycle, food security, ecology, disaster prevention, and the economy of monsoon regions. Given the extensive literature on Asian monsoon climate prediction, we limit our focus to reviewing the seasonal prediction and predictability of the Asian Summer Monsoon (ASM). However, much of this review is also relevant to monsoon predictions in other seasons and regions. Over the past two decades, considerable progress has been made in the seasonal forecasting of the ASM, driven by an enhanced understanding of the sources of predictability and the dynamics of seasonal variability, along with advanced development in sophisticated models and technologies. This review centers on advances in understanding the physical foundation for monsoon climate prediction (section 2), significant findings and insights into the primary and regional sources of predictability arising from feedback processes among various climate components (sections 3 and 4), the effects of global warming and external forcings on predictability (section 5), developments in seasonal prediction models and techniques (section 6), the challenges and limitations of monsoon climate prediction (section 7), and emerging research trends with suggestions for future directions (section 8). We hope this review will stimulate creative activities to enhance monsoon climate prediction.

Eastward propagation is an essential feature of the Madden–Julian oscillation (MJO). Yet, it remains a challenge to realistically simulate it by global climate system models, and the reasons are not fully understood. This study evaluates the capability of 20 Coupled Model Intercomparison Project phase 6 (CMIP6) models in simulating MJO’s eastward propagation and its intrinsic links with the dynamic–thermodynamic structures and the background mean states, aiming at better understanding the sources of the simulation errors. The metrics to evaluate the MJO internal dynamics consists of six parameters: 1) the east–west asymmetry in the low-level circulation, 2) the boundary layer moisture convergence propagation, 3) the vertical tilt of equivalent potential temperature or moist static energy, the vertical structures of 4) diabatic heating and 5) available potential energy generation, and 6) upper-level diabatic heating and divergence. We also gauge the performance of three MJO-related background mean-state fields, including precipitation, sea surface temperature, and low-level moist static energy. It is argued that these parameters are relevant internal and external factors that could affect MJO eastward propagation. We find that the boundary layer moisture convergence is most tightly coupled with the eastward propagation of MJO and controls the premoistening, destabilization, and the leading low-level diabatic heating and available potential energy generation. The CMIP6 models exhibit significant improvements against CMIP5 models in simulating MJO dynamic–thermodynamic structures and the mean states. The diagnostics in this study could help to identify the possible processes related to CMIP6 models’ shortcomings and shed light on how to improve simulation of MJO eastward propagation in the future.