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Original Paper Issue
On the Inconsistency of Cloud Liquid Water between Reanalyses and Satellite Observations over East Asia
Journal of Meteorological Research 2025, 39(4): 1025-1038
Published: 17 May 2025
Abstract Collect

Cloud water plays an important role in the global atmospheric water cycle and weather modification, but cloud is one of the most uncertain parameters in the study of weather and climate. The cloud water products from different data sources may have considerable discrepancies. In this study, the total cloud liquid water (termed as cloud liquid water path, LWP) obtained from satellite observations [Advanced Himawari Imager (AHI) and Advanced Microwave Scanning Radiometer (AMSR)] and three sets of modern reanalysis data (ERA5, JRA-55, and MERRA-2) are compared and analyzed. Moreover, characteristics of vertical distributions of cloud liquid water content (LWC) in different regions over East Asia are analyzed by using the profile data from the reanalyses. The main findings are as follows: (1) in extensive warm marine clouds, AHI and AMSR have a good agreement (with the correlation coefficient larger than 0.7) but with an overestimation from AHI; (2) under warm cloud conditions, the LWP in ERA5 shows a significant positive bias (about 0.065 kg m−2) over land, while MERRA-2 is closer to the satellite product compared with ERA5 and JRA-55; and (3) Southwest China (SW) is the area with most abundant LWC. The LWC is mainly concentrated in the middle and lower troposphere in the study area, and the LWC in ERA5 is higher than that in MERRA-2 and JRA-55. Overall, satellite observations and reanalyses exhibit significant inconsistency for cloud LWP, which needs further investigation and understanding.

Original Paper Issue
Snow-Enhancement Conditions and Seeding Simulation of Stratiform Clouds in the Bayanbulak Test Area in China
Journal of Meteorological Research 2024, 38(6): 1078-1092
Published: 23 August 2024
Abstract Collect

In this study, we employed a three-dimensional mesoscale cold-cloud seeding model to simulate the microphysical impacts of artificial ice crystals used as cloud seeding catalysts. Our objective was to elucidate the mechanism of snowfall enhancement in stratiform clouds in the Bayanbulak test area of Xinjiang, China. The results indicated that the optimal seeding time was the early stages of weather system development. In this case, the optimal seeding zone was identified as the northwest of the test area, especially near the cloud top (altitudes between 3500 and 4000 m, temperatures range −11 to −15°C), and the ideal concentration of catalyst was with ice crystal density of 1.0 × 107 kg−1 within the target area. Under such conditions, the total precipitation rate in the seeding-affected area increased to 50.1 mm h−1. The results also showed that the favorable seeding region was featured by high content of supercooled water and low population of natural ice crystals, where artificial ice crystals could substantially increase the snowfall. This augmentation typically appeared in a unimodal pattern, with the peak formed within 2–3 h after seeding. Seeding in the ice–water mixed zone of a supercooled cloud facilitated rapid ice crystal growth to snowflake pieces via the Bergeron process, which in turn consumed more supercooled water via collision–coalescence with cloud water droplets. Simultaneously, the intensive consumption of supercooled water impeded the riming process and reduced the formation of graupel particles within the cloud. The dispersion of artificial ice crystals extended over tens of kilometers horizontally; however, in the vertical direction most particles remained approximately 1 km below the seeding layer, due to limited vertical ascent rate in the stratiform clouds restricting upward movement of artificial ice crystals. The above results help better understand the snowfall enhancement mechanism in stratiform clouds and facilitate related weather modification practice.

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