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Currently, the opportunistic method to estimate rainfall using commercial microwave links (CMLs) has been shown as an efficient way to complement traditional instruments in terms of spatial‐temporal resolution and coverage. In this paper, we collected data from 26 CMLs in Jiangyin City, Jiangsu Province, and conducted experiments on rainfall field reconstruction and nowcasting. First, the raw CML data were processed to invert the path‐averaged rainfall intensity. Second, the algorithms of inverse distance weighting (IDW) and ordinary kriging (OK) interpolation were employed to reconstruct the rainfall field. Then a 10‐min prediction of the rainfall field was achieved using a nowcasting model based on the long short‐term memory neural network and a setup window was introduced to improve the prediction performance of the first few minutes. The reconstruction results show that the average correlation coefficient (ACC) and the average root mean square error (ARMSE) between the IDW‐based results and daily cumulative rainfall from rain gauges (RGs) are 0.89 and 8.69 mm, respectively, while the ACC and ARMSE between the OK‐based results and RG data are 0.89 and 9.13 mm, respectively. The nowcasting results show that the ACC between the prediction results with a 5‐min setup window and the IDW‐retrieved rainfall fields can reach 0.91 at the first minute and gradually decrease to 0.20 within 10 min. Furthermore, the model has better nowcasting performance for stratiform precipitation and mixed precipitation compared to convective precipitation. Plain Language Summary: Accurate and real‐time rainfall monitoring and forecasting are of great significance for disaster prevention and control, agriculture, meteorological research, and related fields. However, traditional rainfall measurement methods are insufficient for meeting the demands of comprehensive precipitation observations because of poor spatial‐temporal resolution and limited coverage. Currently, measuring rainfall using additional microwave attenuation caused by raindrops has been shown as an efficient way to complement traditional instruments. Based on commercial microwave link (CML) rainfall measurement technology, this paper carries out rainfall field reconstruction and nowcasting experiments in Jiangyin City, China. The results show the CML network enables accurate rainfall field reconstruction and nowcasting. Key Points: Based on the commercial microwave link (CML) rainfall monitoring network in Jiangyin, China, accurate rainfall inversion by CMLs is achievedThe two‐dimensional rainfall fields are accurately reconstructed using the inverse distance weighting and ordinary kriging interpolation algorithmsA long short‐term memory‐based rainfall field nowcasting model is proposed to achieve 10‐min continuous predictions of rainfall fields [ABSTRACT FROM AUTHOR]

Both long‐term but small number of national stations and short‐term but large number of regional stations have been frequently used to study the extreme hourly precipitation (EXHP) in China. However, few studies focus on the differences of the two for revealing the features of EXHP. In this study, the characteristics of EXHP in Zhejiang Province are investigated using three rainfall data sets at three threshold criteria. The comparison between different data sets shows that increasing the station density can better reflect the climatic spatial distribution of EXHP thresholds if long‐term data is absent. The majority of EXHP can be classified into four weather types: the southwesterly wind type (30.7%–48.5%), the trough type (12.2%–23.6%), the tropical cyclone (TC) type (11.4%–17.5%) and the easterly wind type (4.9%–17.9%). The selection of stations is more sensitive to the proportions of the four weather types than the statistical years and threshold criteria. The monthly and diurnal variations of EXHP, as well as their differences revealed by the three data sets, are varied by weather type. Only using national stations cannot distinguish the spatial differences between the TC type and the easterly wind type, and there is an underestimation for southwesterly wind type and trough type in the mountainous area of southwest Zhejiang. The statistical year and station height are the main reasons for the differences in the duration of EXHP events calculated by different data sets, with the TC type having the largest effect and the southwesterly wind type the smallest. Plain Language Summary: Station data is the most common and reliable data for studying the characteristics of precipitation in China. There are two sources of station data available, that is, national station data with long time series but sparse and regional stations with short time series but numerous. However, few studies have compared the differences between these two sources of data for revealing the characteristics of extreme hourly precipitation (EXHP). In this study, the possible impact of different data sets for revealing the characteristics of EXHP under four weather types are investigated in Zhejiang Province. Zhejiang is located on the southeast coast of China with a long coastline and many mountains. Results suggest that increasing the station density can better reflect the spatial distribution of the EXHP thresholds if long‐term data is absent. EXHP events with strong synoptic‐scale forcing are more sensitive to the results obtained by different data sets. As the national stations are mostly located in the plains, the high frequency centers of EXHP are biased in each weather type if only using national stations, especially in southwest Zhejiang and near the coast. In summary, this paper provides additional perspectives for understanding the characteristics of regional EXHP by using the most common observations. Key Points: The selection of stations is sensitive to the proportions of the four main weather types in Zhejiang where extreme hourly rainfall occursExtreme hourly precipitation events with strong synoptic‐scale forcing are more sensitive to results obtained using different data setsThe sparse national stations located on the plains could hardly reflect the spatial distribution of extreme rainfall in mountainous Zhejiang [ABSTRACT FROM AUTHOR]

The observation errors in precipitation gauges contribute to diminished precision in precipitation data sets. To reduce the impact of these errors, the World Meteorological Organization Solid Precipitation Intercomparison Experiments recommended the Double Fence Intercomparison Reference as a reference standard for precipitation measurements. This study proposed a new rain, snow, and mixed precipitation adjustment method for national standard precipitation gauges, using DFIR‐measured precipitation as the standard values. This method was used to adjust for systematic errors, including wind‐induced errors, wetting loss, and trace precipitation, in precipitation data collected by 785 stations in China from 1961 to 2020. After bias adjustment, the annual precipitation increased by 6.1–177.9 mm (with an average of 52.7 mm), accounting for 3.3%–52.1% (8.9%) of the total precipitation. The average annual error‐adjustment amounts for wind‐induced error, wetting loss, and trace precipitation were 21.9 (3.6% of total precipitation), 26.6 (4.7%), and 4.2 mm (1.3%), respectively. The adjustment percentage in winter was higher than that in summer, with the high‐adjusted‐percentage regions predominantly located in areas with drought, high proportion of snowfall, and strong wind speeds. Additionally, the annual average error‐adjustment amounts for rain, snow, and mixed precipitation respectively accounted for 5.2%, 38.2%, and 17.1% of their corresponding total amounts, indicating the significance of bias adjustment, particularly for snow and mixed precipitation, in the northern and Qinghai‐Tibet Plateau regions. Therefore, bias adjustment is necessary to enhance the accuracy of the precipitation data set in China. Key Points: Propose a new adjustment method using the Double Fence Intercomparison Reference as a reference standard to improve precipitation accuracyThe wind‐induced error was smaller than wetting loss, which may be attributed to the decrease in surface wind speed across ChinaThe bias adjustments for snow and mixed precipitation were important for the cold and arid northern and Qinghai‐Tibet Plateau regions [ABSTRACT FROM AUTHOR]

Extreme torrential rainfall events are low‐probability events. A "China‐Record Extremely Heavy Rainfall" (CREHR) event with rain rate of 201.9 mm/hr occurred on 20 July in Zhengzhou in North China. Using high‐density meteorological observations, ERA5 reanalysis data, remote sensing data from China's FY‐4A satellite, and numerical simulation, we revealed that sufficient warm–humid airflows were continuously transported to the Zhengzhou area via multiple pathways that were mainly modulated by the large‐scale western Pacific subtropical high to the north along with the anomalies of the westerly belt and a meso‐scale binary typhoon system. At the local scale, under the combined action of the vertical circulation that caused low‐level convergence and high‐level divergence, and the rapid uplift of water vapor related to the blocking by mountainous terrain, this CREHR event was eventually triggered. Particularly, our present work shows the roles of both typhoon Cempaka and meso‐scale convective systems to south of Henan province can not be ignored, producing a strong super‐thick water vapor transport layer. The existence of the binary typhoon raises the level of uncertainty involved in the water vapor transport of this CREHR event. Plain Language Summary: Extreme torrential rainfall events are low‐probability events. The rainfall from 16:00 to 17:00 Beijing time on 20 July in Zhengzhou in North China reached 201.9 mm, which was a record in mainland China—a so‐called "China‐Record Extremely Heavy Rainfall" (CREHR) event. By using high‐density meteorological observations, ERA5 reanalysis data, remote sensing data from China's FY‐4A satellite, and numerical simulation, we found that sufficient warm–humid airflows were continuously transported to the Zhengzhou area via multiple pathways that were mainly modulated by the large‐scale western Pacific subtropical high to the north along with the anomalies of the westerly belt and a meso‐scale binary typhoon system. At the local scale, under the combined action of the vertical circulation that caused low‐level convergence and high‐level divergence, and the rapid uplift of water vapor related to the blocking by mountainous terrain, this CREHR event was eventually triggered over northern mainland China. Our findings reveal that the existence of the binary typhoon circulation raises the level of uncertainty involved in the water vapor transport of this CREHR event, which has implications for improving our ability to predict and provide early warnings for severe rainstorms and related disasters in cities with such a complex context. Key Points: Sufficient warm‐humid airflows were continuously transported to the Zhengzhou area via multiple water vapor pathwaysMultiple pathways were mainly modulated by the large‐scale western Pacific subtropical high, the westerly belt and mesoscale binary typhoonsNorthward movement of multiple meso‐scale convective systems caused a strong super‐thick water vapor transport layer [ABSTRACT FROM AUTHOR]

Accurate prediction of tropical cyclone (TC) induced rainfall is of great importance to disaster prevention but quite challenging to operational forecasters. This study quantifies the spatial characteristics of the hourly rainfall caused by TCs at several individual weather stations over the south China coast. We use the historical TC datasets from 2004 to 2018 and the hourly rainfall data from six weather stations to investigate the stations' rainfall distribution characteristics induced by TCs within a distance of 700 km to the weather stations. The hourly rainfall data during the study period from six coastal stations: Zhuzilin (ZZL), Shekou Ferry Terminal (SFT), and Wutong Village (WTV) in Shenzhen, and Hong Kong Observatory (HKO), Sha Tin (SHA), and Tai Mo Shan (TMS) in Hong Kong are used to investigate the statistical relationship. Results show that the most hazardous areas for TC‐induced rainfall are TCs within a distance of 200 km relative to the stations. High intensity TCs in the southwest quadrant may bring torrential rainfall to stations within 500 km distance, and low intensity TCs are likely to induce torrential rainfall to stations within 300 km distance when they are in the northeast and northwest quadrants. If TCs are over the region with the azimuth of 60–150° and distance out of 200 km to the six stations, there is almost no rainfall influence on those stations. The findings of this study are valuable to provide information for the local operational forecasters when predicting the potential rainfall along the south China coast due to future TCs. Key Points: The most hazardous areas for tropical cyclones (TCs) induced rainfall are TCs within a distance of 200 km to the stationTCs are more likely to bring torrential rainfall to a coastal station when they are in the southwest quadrant of the stationTCs have almost no impact on rainfall when the azimuth is between 60 and 150° and distance is out of 200 km from the station [ABSTRACT FROM AUTHOR]