Ensemble prediction has been an important tool for weather forecasting, sub-seasonal to seasonal prediction, seasonal prediction, interannual prediction and even simulation of climate change, which has garnered widespread attention in the field of meteorology. This paper introduces the ensemble prediction scheme of China Meteorological Administration Climate Prediction System version 3 (CMA-CPSv3). In this scheme, we adopt the approach of combining stochastic perturbations of physical process tendencies in the atmosphere and the air-sea flux with time-lagged initial value perturbation. Based upon the version 2 of High-Resolution Beijing Climate Centre Climate System Model (BCC-CSM2-HR), we have developed a multi-layer random perturbation ensemble prediction system with relatively good ensemble sample dispersion, stability, and reliability. Results of evaluation for hindcasts over the past 20 years show that this ensemble prediction system significantly improves the prediction of precipitation and 2 m air temperature over China, as well as the El Niu00F1o-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Asian Monsoon. In particular, the random perturbation of air-sea flux shows a positive effect on improving the prediction skills of ENSO and Southeast Asian Monsoon (SEAM) and Western North Pacific Summer Monsoon (WNPSM) indices. This study offers useful insights for further characterizing uncertainty in other component models of the climate system.
This study explores the direct assimilation of Level-1 observations from the Hyperspectral Infrared Atmospheric Sounder (HIRAS-u2161) aboard the Fengyun-3E (FY-3E) satellite into a global real-time atmospheric analysis system. A dedicated operational processing chain for HIRAS-u2161 data has been developed within the Gridpoint Statistical Interpolation (GSI) assimilation framework, incorporating data preprocessing, quality control, bias correction, cloud detection and variational assimilation. By combining the CrIS-FSR channel selection method with Jacobian sensitivity analysis of HIRAS-u2161, a subset of 28 temperature-sensitive channels is identified from the long-wave infrared band. Assimilation experiments demonstrate that this channel subset significantly improves temperature assimilation and effectively suppresses errors in humidity. This approach contributes to better temperature analyses in the mid-to-upper troposphere while preserving positive effects in the lower troposphere. A maximum reduction of 2% in the Root Mean Square Error (RMSE) of temperature analyses is observed over the northern Hemisphere. This study marks the first successful operational assimilation of FY-3E/HIRAS-u2161 data into the global real-time atmospheric analysis system, providing reliable technical support for the operational assimilation of Fengyun satellite hyperspectral infrared data.
To reveal the environmental conditions, triggering mechanisms, and predictability of extreme short-term heavy rainfall in urban areas under weak synoptic-scale forcing, a comprehensive analysis of an abrupt heavy precipitation event that occurred in the main urban area of Zhengzhou on 22 July 2024 is conducted. Data from dense automatic weather stations, ERA5 reanalysis data, short-term forecast products from various numerical models, and multi-source novel observational data including FY-4B geostationary satellite imagery, dual-polarization radar, wind profile radar, cloud radar, and GNSS/PWV are used. The results indicate that this event occurred at the edge of the western Pacific subtropical high, where the synoptic forcing was weak. Westerlies prevailed at 500 hPa, while warm and moist southerlies prevailed in the lower levels. The surface was controlled by a warm low-pressure system. Prior to the heavy rainfall, the environment in Zhengzhou was characterized by extreme high-temperature and high-humidity, with the Convective Available Potential Energy (CAPE) exceeding 5000 J/kg and the Precipitable Water Vapor (PWV) above 80 mm, indicating persistent enhancement of atmospheric instability. FY-4B infrared imagery revealed that the heavy precipitation was caused by the development and southward movement of a Mesoscale Convective System (MCS) originating from northern Henan. During its mature stage, the MCS exhibited a significant expansion of cold cloud, with the heavy rainfall concentrated in the region of large brightness temperature gradient at the leading edge of the MCS. Further analysis suggests the rainfall was triggered by boundary-layer processes in a phased manner, i.e., the urban heat island effect initially induced a meso-u03B3-scale surface low pressure over the main urban area, triggering the initial convection. The outflow from the cold pool of this convective system converged with the ambient warm, moist flow, triggering new convections accompanied by persistent small-scale vortices. The thunderstorm high pressure from northern Henan moved southward, forcing the rise of the leading-edge warm, moist air and triggering a widespread convective outbreak. Short-term forecasts from several numerical models failed to predict this event, reflecting their limitations in simulating the evolution of meso- and micro-scale systems under weak synoptic-scale forcing. In contrast, high spatiotemporal resolution observations demonstrate significant value for nowcasting. Wind profile radar detected the establishment of a westerly jet stream at 4u20145 km altitude 2u20143 h before the precipitation, and the 0u20146 km vertical wind shear increased from weak to moderate, favoring convective organization in the high-CAPE environment. GNSS/PWV data showed a sharp increase of over 4 mm about 1 h before the rainfall, indicating rapid low-level moisture convergence and uplift. Cloud radar observations captured a sharp decrease in cloud base height, signaling the critical phase of microphysical processes transitioning into heavy precipitation formation. In conclusion, under weak synoptic-scale forcing, the multi-stage triggering mechanism that involves urban heat island, cold pool outflow, and thunderstorm high pressure was the key to the occurrence of this extreme short-duration heavy rainfall. The continuous evolutionary signals revealed by multi-source novel observations provide crucial information for improving the nowcasting capability of such kinds of abrupt local heavy precipitation events.
Northern China is characterized by steep terrain, complex circulations and strong land-atmosphere interaction, which make it highly susceptible to frequent droughts. In recent years, extreme drought events have increased in this region under the background of global warming, posing a threat to socioeconomic sustainable development. To promote the prediction of extreme drought events, it is imperative to improve the performance of regional numerical models for the simulation of drought factors such as precipitation and temperature. Therefore, RegCM5.0 is localized and improved in this study to develop a drought prediction system. The improvements include surface type data update, thermal conductivity parameterization modification and cumulus convection scheme optimization. Results show that precipitation bias is reduced by 50% and 2 m air temperature bias is reduced by 1u2103. The correlation coefficients of precipitation and 2 m air temperature with observations increase from 0.61 to 0.72 (u03B1=0.001) and from 0.83 to 0.88 (u03B1=0.001), respectively. The correlation coefficients of simulated drought indexes such as SPI (Standardized Precipitation Index) and SPEI (Standardized Precipitation Evapotranspiration Index) with those from observations can reach above 0.50 (u03B1=0.05). A case study shows that the prediction system can accurately forecast the extreme drought event in the summer of 2020 and those extreme heat and drought events in 2024.
Based on the monthly Extended Reconstructed Sea Surface Temperature dataset (ERSST v5) provided by the National Oceanic and Atmospheric Administration (NOAA), this study investigates how the longitudinal position of La Niu00F1a affects summer precipitation in Southeast China during its developing phase from 1950 to 2023. The underlying physical mechanisms are also explored. The results show that an eastward shift of the La Niu00F1a cold center tends to induce a meridional dipole precipitation anomaly pattern over Southeast China, characterized by increased rainfall over the Yangtze River Basin and decreased rainfall over South China. In contrast, no significant precipitation anomalies are observed in Southeast China when La Niu00F1a shifts westward. Further analysis reveals that the eastward-shifted La Niu00F1a events are often accompanied by positive Sea Surface Temperature Anomalies (SSTA) in the equatorial western Pacific, which strengthen the zonal SSTA gradient and enhance equatorial easterly wind anomalies. These changes are favorable for the development of an anomalous anticyclonic circulation near the South China Sea, which enhances moisture transport to the Yangtze River Basin while suppressing convection over South China via its subsiding branch. Conversely, westward-shifted La Niu00F1a events are featured by a weaker zonal SSTA gradient and negligible atmospheric circulation responses, thus exerting little influence on precipitation in Southeast China. This study highlights the crucial role of La Niu00F1a's longitudinal position in modulating summer rainfall patterns over China and provides new physical insights into the ENSO-precipitation relationship. These findings offer important implications for improving flood-season precipitation prediction.
