This article provides an overview of the progress in monitoring and nowcasting techniques for severe convective weather (SCW), as well as the development of operational nowcasting systems. It focuses on summarizing the progress of monitoring and nowcasting techniques using deep learning (DL) models based on multisource data and points out the challenges and opportunities. Based on multisource observations such as those from dual-polarization weather radars and geostationary satellites, the monitoring capabilities of SCW types and intensities, convective initiation, and identification and tracking of convective storm cells are further improved using storm structural feature recognition, fuzzy logic, DL, and other technologies. The application of deep generative models has significantly improved the accuracy and lead time of SCW nowcasting. The performance of China Meteorological Administration’s SWAN 3.0 (Severe Weather Analysis and Forecasting) system has been steadily improving and has been widely used in operations in China. In the future, it is necessary to make full use of fine observation and numerical forecast data at the hundred-meter resolution to enhance the understanding of the mechanisms of SCW at the meso-γ- and microscales. Physical-informed artificial intelligence (AI) models, as well as large scale AI models should be developed for nowcasting to continuously improve the monitoring and nowcasting capabilities, leading to the full utilization of forecasters’ comprehensive judgment role and enhancing their ability to predict extreme weather.

The Earth System Numerical Simulation Facility, also known as EarthLab, is a national-class key scientific and technological infrastructure project in China during the Twelfth Five-Year Plan period. The project was officially completed in Huairou Comprehensive National Science Center in October 2022. The objectives of the project are: (1) to explore the physical, chemical and biological processes of the atmosphere, as well as the hydrosphere, cryosphere, lithosphere and biosphere on Earth’s surface, and their interactions, and probe the effects of those interactions on the overall Earth system and regional environment over China; (2) to merge simulated and observed data to improve the accuracy of climate and environmental predictions, thereby providing scientific support for national efforts in disaster prevention and mitigation, addressing climate change, and improving atmospheric environmental governance; and (3) to promote interdisciplinary integration among various branches of Earth system science and propel China’s all-embracing advancements in this field to an internationally renowned level. This article will review the international development trends of Earth system numerical simulation facilities, and particularly introduce the composition and functions, the main achievements and future plans of China’s “Earth System Numerical Simulation Facility”.

In this study, an objective algorithm to identify meso-γ-scale vortexes (MVs) using radial velocity observations from an S-band radar is developed. Then, for the 237 Extreme Hourly Precipitation (EXHP; > 75 mm) records at the surface weather stations in the Pearl River Delta (PRD) during five warm seasons, the properties and environmental conditions of the EXHP-associated MVs are analyzed. Further, the spatiotemporal distributions of the MV, instantaneous rain rate, and EXHP are illustrated for three events with the most abundant EXHP records. The major findings are as follows. About 42% EXHP records are accompanied by 57 MVs, including 84% of weak shear intensity, 12% of weak mesocyclone intensity, and 4% of moderate mesocyclone intensity, with the rotational speeds between 5 and 12 m s⁻¹, 12 and 16 m s⁻¹, and 16 and 21 m s⁻¹, respectively. The duration and core depth of the MVs are highly correlated (coefficient of 0.67) with averages of 39 min and 699 m, respectively. The hourly rainfall accumulation of an EXHP tends to increase with the influencing duration of MVs on the EXHP, while a majority of MVs might result from the EXHP-associated forcing such as condensational latent heating. Relative to the EXHP events with MVs in the United States, those in the PRD feature smaller environmental 0–3 km storm relative helicity (SRH) and 0–1 km vertical wind shear (VWS). However, compared to the non-rotational EXHP in the PRD, the rotational EXHP are associated with significantly higher 0–1 km VWS, 0–3 km SRH, humidity, and larger convective available potential energy. In the three selected events, rainstorms exhibit an irregular shape, a quasi-circular shape, and a quasi-banded shape of strong echo, respectively. The MVs are often located inside the strong radar reflectivity region, and some are next to its bow-shaped portion. Those longer-lived MVs with stronger rotation are collocated with the extreme 6-min rainfall accumulation (≥ 10 mm) in space and time, suggesting presence of positive feedback between low-level rotation and short-term rain rate. In the event influenced by a tropical storm, four MVs appear at almost the same location in succession and move along roughly the same path, forming an MV back-building process.

In the past century, the development of tropical cyclone (TC) forecasting technology in China has experienced several main stages, such as cloud identification, weather chart analysis, statistical forecasting, statistics–dynamic forecasting, numerical forecasting and their integrated application. As a result, the capability in forecasting TC in China has significantly improved in both accuracy and stability, with noticeable stepwise features corresponding to the developments in forecasting technology. Looking ahead, forecasting of TCs has entered a new phase to breakthrough the bottlenecks of fine structure and long lead time forecasting. The integrated development of physical law understanding and artificial intelligence technology is anticipated to catalyze a new leap in capability.

For numerical weather prediction (NWP), data assimilation (DA) combines short-term forecasts and various atmospheric observations to achieve optimal initial conditions, based on which subsequent forecasts are launched. With the rapid advancements in numerical models and observing systems, DA has been significantly evolved. Modern methods now can account for uncertainties of state variables across various spatiotemporal scales, incorporate multi-scale observation error statistics, and enforce dynamical constrains and model balances. Meanwhile, observations from various platforms, such as ground-based, aircraft, and satellite, have been assimilated. These include data from polar-orbiting and geostationary satellites, radar-derived radial winds and reflectivity, Global Navigation Satellite System (GNSS) radio occultations, etc. To further utilize the advanced observing systems and DA techniques for high-impact weather predictions, target observation strategies have been developed to identify areas where additional observations can yield the greatest predict improvements. Based on the advancements of DA theories and methods, China’s operational systems have made significant progress, establishing advanced operational DA systems. Over the past decade, the forecast skill of 5-d global weather prediction has improved by approximately 15%. The article reviews a century of development in DA, and discusses future directions, including the advanced DA methods, operational frameworks, integration of novel observations, and the synergy between DA and artificial intelligence.

This paper reviews the development of ensemble weather forecast and the primary techniques employed in the main ensemble prediction systems (EPSs) designed by China and other countries. Here, the emphasis is placed on the advancements in China Meteorological Administration (CMA) global and regional EPSs, with particular attention to operational technologies such as initial and model perturbation methods and the applications of ensemble forecast. Through comparative verification with EPSs from other leading international NWP centers, CMA’s ensemble prediction system demonstrates forecast skill comparable to its global counterparts. With EPSs progressing to convective scales and coupling between sea, land, air, and ice, the paper addresses the key challenges in ensemble forecast technologies on the aspects of operation, science, integrated with Artificial Intelligence (AI), the integration of weather and climate, and user requirements. Finally, the summaries and future perspectives of ensemble forecast are given.

This paper provides a brief summary of the representative research outcomes on the Arctic–midlatitude connection since the founding of the Chinese Meteorological Society in 1924. (1) The revelation of the North Atlantic Oscillation, the Arctic Oscillation, and the Arctic Dipole anomaly represents three significant milestones in the study of large-scale Arctic–midlatitude teleconnections. (2) Before the mid-1990s, Chinese scholars revealed the key pathways by which Arctic cold air affects cold wave processes in East Asia, the key areas for cold waves, and the dynamical processes of cold high pressure during cold waves. These findings are outstanding representatives of Arctic–midlatitude connection research and have profoundly influenced the development of meteorology in China and the prediction of cold wave processes in winter. (3) The melting of Arctic sea ice and Arctic warming anomalies influence mid-latitude weather events and climate variations by affecting the evaporation of water vapor from the ocean surface, turbulent heat flux between atmosphere and ocean, the meridional temperature gradient of the atmosphere, zonal winds, the location and intensity of the storm track, the propagation of large-scale horizontal teleconnection patterns and planetary waves between the troposphere and stratosphere. (4) The melting of Arctic sea ice plays important roles in modulating the interdecadal variations of the winter atmospheric circulation, leading to alternative occurrence of a warm Arctic–cold Eurasia (2004/05–2012/13) and a warm Arctic–warm Eurasia (2013/14–2018/19). The former strengthens the connection between the Arctic and mid-latitudes, while the latter corresponds to a noticeable weakening of the Arctic–midlatitude connection. (5) The melting of Arctic sea ice facilitates the frequent occurrence of Arctic cold anomalies in the middle and lower troposphere during summer, leading to the formation of blocking circulation anomalies in high-latitude regions that are conducive to the occurrence of heatwaves and wildfires in some regions of high-latitudes. (6) The frequency of summer heatwaves averaged over the Qinghai–Xizang Plateau to the mid and low latitude areas of eastern China has a direct dynamical link with the frequent occurrence of summer Arctic cold anomalies in the middle and lower troposphere. The systematic northward shift of the troposphere zonal winds over East Asia is the intrinsic mechanism that connects the Arctic cold anomalies with the heatwaves in East Asia. Future research on Arctic–midlatitude connections should pay more attention to the role of Arctic sea ice melting in the low-frequency variability of atmospheric circulation, particularly emphasizing the impacts of both different spatial anomalies and anomalous amplitudes in Arctic sea ice concentrations. It is necessary to quantitatively examine the role of Arctic sea ice melting in extreme weather and climate events.

Research on climate change projection aims to provide decision-makers with more reliable and less uncertain information about future climate changes. This paper reviews the main progress made in China over the past decade regarding climate change projections and discusses future perspectives in this field. Climate model projections indicate that both regional average temperatures and precipitation in China will increase, with the largest increases occurring under the scenarios with highest emissions. In the future, extreme cold events in China are expected to decrease, while extreme heat events will become more frequent; extreme precipitation will significantly increase in intensity and frequency. Additionally, compound extreme events will also see a notable increase, particularly the rarest extreme events, which will rise more significantly in the future. Statistical bias-calibration, model weighting, constraint based on detection and attribution, and emergent constraint have been widely applied in regional climate change projections in China. Overall, constrained projections do not alter the qualitative conclusions of the raw model projections, but adjust the magnitude of change. The observational constraint methods have demonstrated the ability to reduce uncertainty in projections across different regions and variables in China. To further advance regional climate change projection research in China, it is essential to deepen understanding of the climate system and its feedback processes, improve the quality of observational data and the performance of climate model simulations, and enhance the application of emerging technologies such as machine learning.

With the rapid development of satellite observation technology, scientists have been able to make relatively accurate estimates of the energy budget at the top of the Earth’s atmosphere. However, the estimation error in the Earth’s surface energy imbalance is still more than an order of magnitude greater than the changes in radiative forcing caused by the increase in greenhouse gases. Among the various components contributing to the energy imbalance estimation at the Earth’s surface, downward shortwave solar radiation represents one of the most important sources of error. At the same time, surface solar radiation (SSR) is not only an important driving data for simulating land surface processes, but also an important indicator for the utilization of renewable solar photovoltaic energy. Therefore, accurate observation of SSR has become a key variable in reducing the associated error. The long-term variations of SSR have always been a major scientific concern for researchers across various fields. This paper starts with a comparison of existing SSR data products, discusses the bias and uncertainty issues in the long-term variations of SSR, and clarify the importance of developing high-quality SSR observation baseline data products. On this basis, the paper introduces a series of researches in recent years, based on the most complete SSR station observation data to date, systematically considering its inhomogeneity and sampling problems, performing systematic homogenization processing and AI reconstruction on station series, and estimating the long-term variations and uncertainty levels of SSRs at global and regional scales. These studies offer new evidence for global and regional climate change observation, detection attribution, and future projection. Finally, the paper presents an outlook on the existing and future challenges in the research on SSR data and its long-term variations.

The Earth system is a complex, nonlinear, and highly coupled system that integrates the atmosphere, land, ocean, cryosphere, lithosphere, and biosphere through various physical, chemical, and biological processes. The Earth System Model (ESM) is an advanced mathematical–physical representation of this intricate system. It extends beyond the traditional climate system models that focus primarily on the physical representation of atmospheric, terrestrial, and oceanic states to encompass environmental and ecological dynamics. Consequently, ESMs are essential tools not only for weather and climate prediction but also for studying environmental and ecological evolution, human-induced climate impacts, and optimizing strategies for climate and ecological management.

Northeast China is a region characterized by frequent and concentrated snowfalls, with one of the peaks occurring in March. Given profound impacts of snowfall on natural systems and social economies, understanding the snowfall variability in this region is of great value. This study documents a notable increase in the intensity of interannual variability (IIV) in March snowfall over Northeast China after the late 1990s, with the IIV during 1997–2021 doubling that of the period 1972–1996. This increase in the snowfall IIV is associated with the enhancement of a barotropic anomalous cyclones over the mid–high latitude Asian continent. Furthermore, the relationship of snowfall variability with the sea ice in the East Siberian–Chukchi Seas shifts from a weak to a significant negative correlation. During 1997–2021, associated with the sea ice reduction in the East Siberian–Chukchi Seas during March, anomalous anticyclones dominated the troposphere of the North Pacific, accompanied by barotropic cyclonic anomalies prevailing over mid–high latitude Asia. The barotropic cyclonic anomalies facilitated a southward displacement of the East Asian polar front jet and a westward shift of the East Asian trough, as well as the convergence of anomalous westerlies and southerlies in the lower troposphere of Northeast China. These conditions favor the interactions of cold airs with moist air flows, leading to an increase in snowfall over Northeast China. In contrast, during 1972–1996, the sea ice-related atmospheric circulation anomalies over the North Pacific were weaker and located northeastward. As a result, their coupling with the Asian atmospheric circulations was reduced, thereby weakening the connection of sea ice with the snowfall variability in Northeast China. Further investigation suggests that the intensification of the interaction between the East Siberian–Chukchi Sea ice and the North Pacific atmospheric circulations may be attributed to the climatological change of the North Pacific storm track.

As a part of the special issue commemorating the centennial of the Journal of Meteorological Research, this article reviews the advances of convection and cloud parameterizations in numerical models, focusing on the significant contributions of Chinese scientists in this field. This review begins by outlining the development of convection parameterization, including the Kuo scheme, moist convective adjustment scheme, the widely used mass flux schemes, and the machine learning-based schemes. It details the schemes developed and revised by Chinese scientists, as well as the resulting improvements to the numerical models by these schemes. Following this, this review delves into the progress of cloud parameterization schemes and elaborates on the achievements of Chinese scientists in both cloud macrophysics and microphysics schemes. At the end, the review discusses the possible future avenues in the development of convection and cloud parameterization, highlighting the pivotal role anticipated for deep learning, and suggests pathways for the advancement of hybrid models and multi-scale climate modeling methods.

Blowing snow is a typical natural hazard in high-altitude and snow-prone regions, and its impact could be significantly reduced by accurate forecasts. The empirical study on the conditions for blowing snow hazards on the Sichuan–Tibet Highway in high-altitude mountainous areas are conducted in this paper. The study reveals that blowing snow events primarily occur from December to the following February, with the affected roads mainly located in mountainous areas above altitudes of 3000 m. Based on physical characteristics, snow cover is categorized into three types with different processes of snowdrifts: newly fallen or wind-transported snow, slightly consolidated snow, and compacted snow undergoing freeze–thaw cycles, each exhibiting distinct snowdrift formation processes. Field measurement results indicate that the average threshold wind speeds for initiating blowing snow are 9.65, 14.77, and 23.15 m/s at the 10-m height for these three snow types, respectively. Additionally, analyzing the effects of temperature and snowfall timing on threshold wind velocity, a multi-tiered susceptibility model for blowing snow is developed. This model offers enhanced practical applicability for classifying different types of snow and provides more detailed insights into the variations in threshold wind speed during both the early and later stages of snowfall events, compared to models that rely solely on constant thresholds or temperature-based criteria.

Satellite-based emission inversions of atmospheric pollutants and greenhouse gases provide indispensable information and data foundation for a comprehensive understanding of the sources of these key atmospheric compositions and for the precise implementation of emission reduction measures. Great advances have been made in the field of emission inversion over the past two decades, with Chinese domestic scholars making substantial contributions, which have provided important scientific support for environmental protection and carbon neutrality in China. In celebrating the 100th anniversary of the Chinese Meteorological Society, this paper systematically reviews the research progress of Chinese scholars in satellite-based emission inversion in the past two decades, based on 85 journal papers. Several widely used inversion methods, including data assimilation, local mass balance, Gaussian models, two-dimensional models and machine learning, are briefly summarized. Emission inversion studies of atmospheric pollutants, including nitrogen oxides (NO_x), ammonia (NH₃), formaldehyde (HCHO), glyoxal (CHOCHO), sulfur dioxide (SO₂) and carbon monoxide (CO), as well as greenhouse gases, including carbon dioxide (CO₂) and methane (CH₄) performed by Chinese scholars are then presented. Finally, the historical evolution of inversion methods and target species, challenges in current satellite-based emission inversion and future research directions are discussed to promote more accurate quantification of atmospheric pollutants and greenhouse gas emissions.

Circulation anomalies in one region sometimes cause circulation anomalies in other regions, and the correlation between such regional circulation anomalies is referred to as the atmospheric teleconnection. Chinese scientists have conducted extensive research on the atmospheric teleconnection patterns, particularly those related to the Asian–Pacific monsoon. This review first introduces the basic concepts and historical development of atmospheric teleconnections, and then presents an overview of the studies related to the Asian–Pacific monsoon in recent years, especially those on the subseasonal timescale. The paper systematically summarizes 26 teleconnection patterns, including their main features and associated pioneering works. Particular emphasis is placed on the East Asian–Pacific teleconnection pattern that propagates poleward along the low-level southwesterly monsoonal winds. The wave train-type teleconnection patterns propagating along the upper-level westerly jets are also briefly reviewed.

Under the background of global warming, significant changes have occurred in the regional climate and extreme events in China. A deep understanding of the changing patterns and driving mechanisms of regional climate and extreme events is of great scientific significance for climate change adaptation and disaster risk management. This study reviewed and summarized the latest scientific advancements, and compared the consistency and differences in climate change responses between eastern and western China. The research indicates that since 1961, temperature and precipitation in China have shown an overall increasing trend, with precipitation changes displaying distinct regional characteristics. A notable feature of climate change in western China is “warming–wetting,” mainly in Northwest China and the northern Qinghai–Xizang Plateau, while some areas in Southwest China exhibit aridification characteristics of “warming–drying.” In eastern China, precipitation has remained a “southern flood–northern drought” pattern. However, since 2010, this pattern has gradually changed due to a significant increase in precipitation in Northeast and North China. With climate warming, the frequency and intensity of extreme high temperatures, heavy rainfall, and drought events have significantly increased. Human activity, primarily from greenhouse gas emissions, is the main driving factor behind observed increases in average temperatures and extreme temperatures. Noticeably, internal variability of the climate system has also contributed to changes in regional precipitation. Additionally, this study outlines key scientific issues and challenges for future research of climate change in China.

Supercells are the most severe and long-lasting type of highly organized convective storms, with the greatest potential for producing extreme weather events and causing significant disasters. This article provides a comprehensive overview and recent highlights of supercell research, including the unique structure, environmental characteristics, and the formation and maintenance mechanisms of the mesocyclone. Buoyancy instability is a necessary ingredient of the supercell’s environment, whereas dynamic factors such as vertical wind shear and low-level storm relative helicity are more sensitive parameters for distinguishing supercells from non-supercells. The near-storm environmental parameters derived from multi-sensor observations are expected to enhance high-resolution nowcasting of supercell storms. Different types of supercells, including those producing distinct hazardous weather, exhibit unique reflectivity morphology and dynamical/microphysical structures. For instance, tornadic supercells have a strong low-level mesocyclone, while severe hail supercells feature a strong and deep mesocyclone. Mesocyclones associated with damaging winds are accompanied by significant mid-level radial convergence, while those responsible for heavy precipitation are typically located at low levels. The vertical vorticity of mesocyclone is generated through the tilting of environmental horizontal vorticity by storm-related intense updrafts. The horizontal vorticity that tilts into the mid-level mesocyclone originates from the environmental vertical wind shear (where wind direction and speed vary with height), which produces the horizontal vorticity along the inflow to the storms. In contrast, the horizontal vorticity contributing to the low-level mesocyclone derives from two distinct mechanisms, i.e., environmental vertical shear in the boundary layer and gust front-induced baroclinicity. It remains unclear which mechanism is more reasonable or dominant. Moreover, the maintenance and enhancement mechanisms of mesocyclones are complex and diverse in scenarios including mesocyclone embedding within heavy precipitation, storm mergers, and proximity to surface mesoscale boundaries (e.g., fronts, drylines, gust fronts, and their associated convergence zones). In recent years, based on super high-resolution numerical experiment results, the physical conceptual models of the supercell tornadogenesis have been updated. The newly revealed microphysical and dynamic characteristics from polarimetric Doppler radar observations enable more accurate hail size detection. However, the refined physical conceptual model of severe hail growth still requires improvement, and our understanding of the formation mechanisms of extreme wind gusts and flash floods associated with supercells remains limited.

Evaluation constitutes a crucial component in the creation and application of numerical models. As these models have escalated in complexity in recent years, there has been an increased demand for more accurate forecasting, thereby catalyzing substantial advancements in model verification and evaluation techniques. This paper begins with a review of recent domestic and international progress in model evaluation and verification. It subsequently delves into the significant contributions by Chinese scholars in evaluating the dynamical frameworks of next-generation numerical models, the multi-temporal and spatial variability of the East Asian monsoon, and the assessment of weather and climate conditions around the Qinghai–Xizang Plateau (QXP). Given the identification of precipitation as a key process, the paper presents a comprehensive review of evaluation efforts pertaining to diurnal variations in precipitation and the evolution of precipitation processes. The paper concludes by outlining potential future research outlooks, including the integration of multi-source observation data, the development of evaluation techniques specific to certain models and application contexts, and the synergy between model evaluation and machine learning technologies.

Arid and semi-arid regions constitute approximately one-third of the total land area in China and are vulnerable to the effects of global climate change. Over the past century, a large number of studies have investigated regional climate change and its impacts. However, the conclusions are inconsistent due to differing research perspectives, and this has highlighted the urgent need to obtain systematic, scientific knowledge through synthesis and induction. This study used the available literature to review and categorize the evolution of regional climate change and its effects in the arid and semi-arid regions of China over the last century. It analyzed three components: study data, methodologies, and subjects, and summarizes essential scientific insights from four aspects: the origin and expansion of arid and semi-arid regions, the characteristics of climate change in these areas, the drivers of climate change in arid and semi-arid zones, and the consequences of climate change in such environments. Finally, six key directions for future research on climate change and its effects on the arid and semi-arid regions of China are proposed. This study included scientific references and could be used to inform further studies on climate change and its impacts on the arid and semi-arid areas of China.

Thunderstorms are severe convective weather systems generating lightning, which can lead to various catastrophic weather when a large amount of lightning is produced. In the past decade, high spatiotemporal resolution lightning detection technology has been developed quickly, which have laid important foundation of the study of propagation and mechanisms of lightning, as well as the physical effects of lightning. Combined with Doppler dual polarization weather radar and high-resolution numerical models, thunderstorm dynamics, microphysics, electricity processes and their interrelationships have been well investigated, and some new insight into the thunderstorm charge distribution and its relation to the thunderstorm structure has been obtained. All these have promoted the establishment of lightning forecasting method and data assimilation scheme for improving thunderstorm forecasting. This paper reviews the recent research progresses in detection, mechanism and forecasting of thunderstorm and lightning in China in last decade from 4 aspects, including 1) high-resolution 3D lightning mapping technology and application, 2) lightning in different thunderstorms and its relationship with cloud dynamical and microphysical processes, 3) observation and simulation of thunderstorm charge structure, and 4) lightning prediction and lightning data assimilation for thunderstorm forecasting. Some of the major frontiers and challenges remaining in lightning and thunderstorms studies are also highlighted.