With analysis of local climate zone (LCZ) classification, approximately 52.0% of underlying surfaces in Beijing are covered by buildings with LCZ 5 (open midrise) accounting for the highest proportion, and LCZ D (low plants) is the most distributed among natural surface types. Compared to natural underlying surfaces, building underlying surfaces have higher values in the high temperature (HT) and heat wave (HW) days, HW intensity, and maximum HW duration. In recent decades, HT days on building underlying surfaces in Beijing start earlier and end later than those on natural underlying surfaces. Building underlying surfaces make greater contribution to urban heat island intensity of apparent temperature than to that of temperature, yet it is opposite for natural underlying surfaces.

A ground-based microwave radiometer (MWR) can retrieve temperature and vapor density profiles with a temporal resolution at the minute level, which is significant for studying atmospheric thermodynamic stratification and its evolution. Improving MWR retrieval accuracy is crucial for MWR application research. Based on 9-year observations of MWR and radiosonde in Wuhan, China, this study adopts regression model and artificial neural network (ANN) methods to correct MWR temperature and vapor density deviations against radiosondes in diverse skies. Due to the impacts of solar heating and raindrops, MWR temperature presents a cold bias from radiosondes in clear and cloudy skies, but a warm bias in rainy skies, while the MWR vapor density is generally wetter than radiosondes, especially in rainy skies. The validation results show that both regression and ANN models can reduce the biases of MWR temperature and vapor density against radiosondes to around zero in diverse skies, and the MWR vapor density RMSE in rainy skies shows a marked decrease. After correcting using the regression model, the RMSE of MWR temperature (vapor density) declines by 14% (7%), 7% (4%), and 12% (29%) in clear, cloudy, and rainy skies, respectively, and the correction effect of the ANN model is slightly better than the regression model, with corresponding decreases of 19% (8%), 10% (8%), and 12% (30%), respectively. However, the consistency of MWR retrievals with radiosondes is rarely improved after the corrections of regression and ANN models. These results indicate that the regression and ANN models have a reasonable ability to correct MWR retrieval deviation in diverse skies, and there is remaining room for further improvement in MWR retrieval accuracy.

Jiulong is located on the east side of the Qinghai-Tibet Plateau(QTP)and is a region prone to southwest vortex.Cloud detection with new-type detection equipment in this region helps enhance the knowledge of cloud characteristics in the southwest vortex-prone region.In this study,based on the ground-based microwave radiometer data from June to August of 2018-2019 in Jiulong,the observational charac-teristics of cloud occurrence frequency(COF),liquid water path(LWP),and supercooled liquid water path(SLWP)for non-precipitating clouds during the summer seasons are investigated.The results are as follows.The monthly average COF of summer non-precipitating clouds in Jiulong is between 67%-82%,with low and middle clouds being the main types,and high clouds being less common.For low clouds,the COF is low in daytime and high in nighttime,while it is the opposite for middle and high clouds.The vertical distribution of COF presents an unimodal pattern,with a peak of 8.1%at a height of about 2 km.Due to the diurnal variation of atmospheric thermal stratification,the uni-modal pattern of COF shows diurnal differences.Moreover,the average LWP of summer non-precipitating clouds in Jiulong is 0.433 kg·m-2,with the average LWPs of low,middle,and high clouds being 0.665,0.240,and 0.102 kg·m-2,respectively.The diurnal variation of LWP in low clouds is similar to their COF,while the diurnal variations of LWP in middle and high clouds are not significant.Additionally,the aver-age SLWP of cold clouds among summer non-precipitating clouds in Jiulong is 0.154 kg·m-2,with the average SLWPs of low,middle,and high clouds being 0.065,0.166,and 0.102 kg·m-2,respectively.On the whole,the proportion of SLWP in LWP is about 34.3%-38.8%.The proportion of SLWP increases with the height of the cloud,which makes the diurnal variations of SLWP in middle and high clouds similar to that of LWP.Compared with central China,the characteristics of summer non-precipitating clouds in Jiulong are significantly different,and this is closely related to the different characteristics of atmospheric water vapor between the two regions.

Thermodynamic and liquid water profiles can be retrieved by a ground-based microwave radiometer (MWR) in nearly all weather conditions, which is useful for detecting mesoscale phenomena. This paper reviews the advances in remote sensing of atmospheric profiles and cloud properties by MWR in central China. Comparative studies indicate that MWR retrieval accuracy is different under various skies, especially those that decay under precipitation. The off-zenith method is proven to be capable of reducing the impact of precipitation and snow on MWR retrieval accuracy. Application studies demonstrate that MWR retrievals are helpful for early warning of rainstorms, hailstorms, and thunderstorms. Moreover, MWR retrievals provide a way to study cloud properties. The temporal variations of cloud occurrence frequency (COF) and liquid water path (LWP) are different for low, middle, and high clouds, and the vertical distribution of COF is also different in autumn and other seasons. Note that MWR can infer valid retrievals over the eastern Tibetan Plateau due to the weak precipitation over there. Also, cloud properties over the eastern Tibetan Plateau present differences from those over central China, and this is related to the different characteristics of atmospheric water vapor between these two regions. To bring more benefits for mechanism study and early warning of severe weather and numerical weather prediction, the decayed accuracy of MWR zenith retrievals under precipitation should be resolved. And combining MWR with other instruments is necessary for MWR application in detecting multi-layer clouds and ice clouds.

Here, we analyze the characteristics and the formation mechanisms of low-level jets (LLJs) in the middle reaches of the Yangtze River during the 2010 mei-yu season using Wuhan station radiosonde data and the fifth generation of the European Centre for Medium-Range Weather Forecasts (ERA5) reanalysis dataset. Our results show that the vertical structure of LLJs is characterized by a predominance of boundary layer jets (BLJs) concentrated at heights of 900–1200 m. The BLJs occur most frequently at 2300 LST (LST=UTC+ 8 hours) but are strongest at 0200 LST, with composite wind velocities >14 m s −1 . Synoptic-system-related LLJs (SLLJs) occur most frequently at 0800 LST but are strongest at 1100 LST, with composite wind velocities >12 m s −1 . Both BLJs and SLLJs are characterized by a southwesterly wind direction, although the wind direction of SLLJs is more westerly, and northeasterly SLLJs occur more frequently than northeasterly BLJs. When Wuhan is south of the mei-yu front, the westward extension of the northwest Pacific subtropical high intensifies, and the low-pressure system in the eastern Tibetan Plateau strengthens, favoring the formation of LLJs, which are closely related to precipitation. The wind speeds on rainstorm days are greater than those on LLJ days. Our analysis of four typical heavy precipitation events shows the presence of LLJs at the center of the precipitation and on its southern side before the onset of heavy precipitation. BLJs were shown to develop earlier than SLLJs.

Droplet size distribution (DSD) is an important parameter reflecting microphysical characteristics of rainfalls, research on vertical structures of DSD is helpful to understand rainfall evolution processes and improve radar quantitative precipitation estimations. Vertical structures of DSDs under different rain rates over different regions during the Meiyu period in 2020 have been investigated using the co-located two-dimensional video disdrometer (2DVD) and micro rain radar (MRR) at the stations of ZiGui, JingZhou and NanJing. It is found that, when raindrops fall, the number concentration of small raindrops and their contribution to rain rates decrease, while the number concentration of medium and large raindrops and their contribution to rain rates increase, which finally leads to that medium raindrops contribute most significantly to surface rain rates. Vertical structures of DSDs under different rain rates are different. For weak rainfall, there are narrow DSDs and the equilibrium of raindrop evaporation and coalescence causes small variation in DSD parameters. For heavy rainfall, there are significantly widened and increased DSDs, because obvious collision process increases the concentration of medium-large raindrops when raindrops falls and thus causes large variation in DSD parameters. Statistical analysis shows that DSDs present significant difference over different regions: the highest number concentration and the smallest raindrop diameter at ZiGui, medium number concentration and medium diameter at Jinzhou, the lowest number concentration and the largest diameter at Nanjing. Moreover, μ-Λ relationships present regional difference, and the fitted values of rain rates with local Z-R relationships over different regions agree well with the observations of 2DVD.

三峡库区地处长江流域腹地,是典型的气象灾害频发区和生态环境脆弱区,夏季小时强降水(Hourly Heavy Rainfall,HHR)因突发性强、预测难度大等极易致灾.利用中国气象局国家气象信息中心提供的逐小时降水量观测资料,分析1992-2021年三峡库区夏季HHR和强降水事件(Heavy Rain-fall Event,HRE)的精细化时空分布特征.结果表明,三峡库区夏季HHR局地性强、强度大,其降水量对夏季总降水量贡献大,且主要源于降水频次的贡献,库区东南部是高值中心.近30 a来,三峡库区夏季HHR降水量呈不显著增加趋势;HHR的降水量和频次日变化均呈双峰型,峰值分别出现在清晨和下午,且日峰值时间位相与地形相关.三峡库区夏季HRE以短历时(1～6 h)为主,其降水量多为20～60 mm,而长历时(>12 h)发生少,其降水量多为60～100 mm.短历时HRE多开始于下午,其最大小时降水量也多发生于下午,而中历时(7～12 h)和长历时HRE多开始于夜间,二者的最大小时降水量均多发生于清晨.

长江流域(Yangtze River Basin,YZRB)是中国降水集中地.在气候变暖背景下,短时强降水(Short-Duration Heavy Rainfall,SDHR)有增加趋势.2020年主汛期(6—8月)YZRB出现多轮强降水,发生了新中国成立以来仅次于1954年、1998年的流域性大洪水.本文利用中国气象局国家气象信息中心逐小时降水资料,分析了长江上游(YR-A)、长江中游(YR-B)和长江下游(YR-C)三个区域SDHR时空分布以及不同类型短时强降水事件(Short-Duration Heavy Rainfall Event,SDHRE)的统计特征.得到结论如下:1)受地形影响,YZRB山区降水频次增加、降水强度增强,且地形作用会增加山区SDHR的频次,进而增强山区SDHR的降水量;YZRB降水强度的空间分布依赖于SDHR降水量的空间分布.2)YZRB三个区域SDHR降水量和频次的日变化均表现为双峰型,双峰时间在YZRB区域自西向东有从夜间移向白天的趋势,这与对流活动日变化的区域差异有关;SDHR的降水量和频次具有相似的日变化,说明SDHR的降水量主要源自其降水频次的贡献.3)在三种类型SDHRE中,增长型频次最高(约62.6％),突发型频次次之(约26.9％),而持续型频次最少(约10.5％);突发型SDHRE的高发降水量最小(约30 mm),持续型SDHRE的高发降水量最大(约90 mm),而增长型SDHRE的高发降水量介于两者之间(40～60 mm).4)不同类型SDHRE降水量的空间分布主要依赖于SDHRE频次的空间分布,增长型SDHRE因频次高于突发型和持续型,其降水量也高于后两种类型,但大别山地区因其地形作用成为持续型SDHRE的高发区,而突发型SDHRE更易在局地形成降水强度高值.

为了提升国产地基微波辐射计反演大气温湿廓线的精度,增强本地部署设备的观测性能,研究实现了地基微波辐射计的神经网络直接样本反演法和观测亮温预处理的神经网络间接样本反演法.将算法应用于武汉华梦科技有限公司研制的HRA002型国产地基微波辐射计,在武汉国家基本气象站开展了与探空以及美国3台MP-3000A微波辐射计的对比观测试验.试验结果显示,HRA002直接样本反演采用改进网络反演水汽密度、相对湿度均方差分别降低约0.94 g·m-3、5％;观测亮温经过预处理后与模拟亮温的相关性提升明显,预处理前后反演的低层温度、水汽密度和相对湿度与探空观测的均方差分别从2.4 K、3.26 g·m-3和18.79％改善为1.58 K、2.18 g·m-3和14.55％,略高于直接样本反演;与3台MP-3000A的反演结果相比,HRA002采用直接样本反演方法的温度廓线总体优于MP-3000A,HRA002采用间接样本反演方法的水汽密度和相对湿度总体上平均偏差占优而均方差稍逊.研究结果表明改进后的直接样本反演法更贴合辐射计硬件性能,反演精度较高;亮温预处理显著提升了间接样本反演精度,在反演精度总体接近的情况下,弥补了直接样本反演法需要长期观测数据的缺陷;综合采用上述两种算法能够提升国产地基微波辐射计本地化、个体化的观测性能,在反演大气参量廓线方面具有可用性.

The eastern slope of the Tibetan Plateau is a crucial corridor of water-vapor transport from the Tibetan Plateau to Eastern China. This is also a region with active cloud initiation, and the locally hatched cloud systems have a profound impact on the radiation budget and hydrological cycle over the downstream Sichuan Basin and the middle reach of the Yangtze River. It is noteworthy that there is a strong diversification in the characteristics and evolution of the ESTP cloud systems due to the complex terrain. Therefore, in this study, ground-based Ka-band millimeter-wave cloud radar measurements collected at the Ganzi (GZ), Litang (LT), Daocheng (DC), and Jiulong (JL) sites of the ESTP in 2019 were analyzed to compare the vertical structures of summer nonprecipitating clouds, including cloud occurrence frequency, radar reflectivity factor, cloud base height, cloud top height, and cloud thickness. The occurrence frequency exhibits two peaks on the ESTP with maximum values of ~20% (2–4 km) and 15% (7–9 km), respectively. The greatest (smallest) occurrence frequency occurs in the JL (GZ). The cloud occurrence frequency of all sites increases rapidly in the afternoon, and the occurrence frequency of the DC presents larger values at 2–4 km. In contrast, the occurrence frequency in the JL shows another increase from 2000 LT to midnight at 7–11 km. Stronger radar echoes occur most frequently in the LT at 5–7 km, and hydrometeor sizes and phase states vary dramatically in mixed-phase clouds. A small number of radar echoes occur at midnight in the JL. A characteristic bimodality of the cloud base height and top height for single-layer, double-layer, and triple-layer clouds was observed. Clouds show a higher base height in the GZ and higher top height in the JL. The ESTP is dominated by thin clouds with thicknesses of 200–400 m. The cloud base height, top height, and thickness exhibit an increase in the afternoon, and higher top height occurs more frequently from midnight to the next early morning in the JL because of its mountain-valley terrain.

Southwest China is with complex topography including basins, mountains, hills and plains, where abrupt heavy rainfall events (AHREs) occur frequently and are difficult to quantitatively estimate due to limited ground‐based observations. Using the data of ground rain gauges and GPM dual‐frequency precipitation radar during April to September in 2014–2020, this study investigates vertical structures of AHREs over southwest China. Both mass‐weighted mean diameter ( D m ) and reflectivity ( Z e ) of AHREs increase rapidly in ice‐phase process but slowly in liquid‐phase process. For convective rainfall of AHREs, abundant water vapour and strong atmospheric convective motion cause higher D m and Z e but lower generalized intercept parameter ( dBN w ) than those for stratiform rainfall. Moreover, ice‐phase process is active while liquid‐phase process is weak in the mountains, but the situation is opposite in the plains, which results in large‐size and low‐concentration raindrops in the mountains while small‐size and high‐concentration raindrops in the plains. Furthermore, statistical models of vertical profile of reflectivity (VPR) indicate that VPR patterns are affected by surface rain intensity and present different trends around the 0°C level between stratiform and convective rainfalls. In addition, higher rain top height in the mountains is conducive to ice‐phase process while lower terrain height in the plains is favourable for liquid‐phase process. Therefore, the VPR pattern depends on rain type, terrain and rainfall intensity, and its fine model is beneficial for understanding microphysical process of AHREs and improving quantitative precipitation estimation by ground‐based radars.

The relationship between sub-daily precipitation and urbanization is widely concerned because short-term precipitation is sensitive to urbanization and difficult to predict. Using the data of summer hourly precipitation and urban development during 2007-2019 at four urban stations and an atmospheric background monitoring station in central China, this study investigates the characteristics of hourly precipitation and hourly extreme precipitation (HEP) under different urbanization background. It is found that high urbanization level may benefit precipitation intensity but not for accumulated precipitation amount and precipitation frequency, and it is also conducive to the occurrence of hourly precipitation within [20, 50) mm. Precipitation amount and frequency for hourly precipitation within [5, 50) mm have similar diurnal variation at fixed station, yet the diurnal variation of precipitation intensity is insignificant. The differences in temporal variation of precipitation are related to urbanization and terrain. Both high urbanization level and speed are conducive to summer HEP; especially summer HEP intensity may increase gradually under sustainable urbanization development. Although growth-type HEP occurs frequently with main contribution to total HEP precipitation amount in central China regardless of urbanization level, the frequency and contribution of continuous-type HEP tends to increase under high urbanization level and speed.

The variation of boundary layer circulation caused by the influence of complex underlying surface is one of the reasons why it is difficult to forecast hourly heavy rainfall (HHR) in the middle Yangtze River Valley (YRV). Based on the statistics of high-resolution observation data, it is found that the low resolution data underestimate the frequency of HHR in the mountain that are between the twain-lake basins in the middle YRV (TLB-YRV). The HHR frequency of mountainous area in the TLB-YRV is much higher than that of Dongting Lake on its left and is equivalent to the HHR frequency of Poyang Lake on its right. The hourly reanalysis data of ERA5 were used to study the variation of boundary layer circulation when HHR occurred. It can be found that the boundary layer circulation corresponding to different underlying surfaces changed under the influence of the weather system. Firstly, the strengthening of the weather system in the early morning resulted in the strengthening of the southwest low-level air flow, which intensified the uplift of the windward slope air flow on the west and south slopes of the mountainous areas in the TLB-YRV. As a result, the sunrise HHR gradually increases from the foot of the mountain. The high-frequency HHR period of sunrise occurs when the supergeostrophic effect is weakened, the low-level vorticity and frontal forcing are strengthened, and the water vapor flux convergence begins to weaken. Secondly, the high-frequency HHR period of the sunset is caused by stronger local uplift and more unstable atmospheric stratification, but the enhanced local uplift is caused by the coupling of the terrain forcing of the underlying surface and the enhanced northern subgeostrophic flow, which causes the HHR to start closer to the mountain top at sunset than at sunrise.

The impact of structural variations in the atmospheric boundary layer (ABL) during the regional transport of air pollutants on its local pollution changes deserves attention. Based on multi-source ABL detection and numerical simulation of air pollutants over the Twain-Hu Basin (THB) during 4–6 January 2019, the mechanism of the rapid growth of atmospheric pollutant concentrations in Xianning by the synergistic effect of regional transport and ABL evolution is explored, and the main conclusions are obtained as follows. The vertically stratified atmosphere is noticeable at nighttime, and the heavy humidity of near-surface fog within the stable boundary layer (SBL) promoted the generation and cumulative growth of secondary PM2.5 components during the pollution formation stage. The horizontal transport characteristics of atmospheric pollutant concentration peak were observed in the residual layer (RL) of 500–600 m. At the pollution maintenance stage, the convective boundary layer (CBL) developed during the daytime, and northerly wind transported high-concentration pollutants from the north to the THB. Under the combined action of horizontal transport and turbulent mixing, the high-concentration atmospheric pollutants in the mixing layer (ML) from the ground to the 500 m height were mixed uniformly and maintained accumulation growth. The next day, the strong vertical turbulent mixing caused the downward transport of high-concentration pollutants in the RL during nighttime due to the development of the CBL again, resulting in a doubling of near-surface pollutant concentration in a short time. With the development of ABL turbulence, local pollution dissipated rapidly without the continuous input of pollutants from external regions. This study emphasizes the importance of multi-scale processes impact on pollution variation, that is, regional transport of atmospheric pollutants at the CBL development stage for the rapid growth of PM2.5 concentration in the ML.

Potential prediction is an important research content of thunderstorm gale weather forecast, and it is still a challenge because the environmental field of thunderstorm gale presents different characteristics under different weather conditions. Using the 12-year thunderstorm gale data of Hubei province in central China and the reanalysis data of National Center for Environmental Prediction (NCEP), this study analyzed the percentile distribution of environmental physical quantities of thunderstorm gale, and the continuous probability method was adopted to establish the probability forecast models of thunderstorm gale in four different types of weather situation, which are in the rear of trough type, in front of trough type, in the periphery of the western Pacific subtropical high type and easterly airflow type. Finally, probability prediction was realized by objective classification criterion in operation. The results show that the method based on objective classification and continuous probability can significantly improve the probability of thunderstorm gale detection, and also reduce the missing alarm rate of thunderstorm gale. Moreover, the quantitative test of 16 weather processes under four types of weather situations also shows that the continuous probability method has a higher probability of detection than the bisection method, and significantly reduces the missing alarm of extreme wind by the bisection method.

It is an important to study atmospheric thermal and dynamic vertical structures over the Tibetan Plateau (TP) and their impact on precipitation by using long-term observation at representative stations. This study exhibits the observational facts of summer precipitation variation on subdiurnal scale and its atmospheric thermal and dynamic vertical structures over the TP with hourly precipitation and intensive soundings in Jiulong during 2013–2020. It is found that precipitation amount and frequency are low in the daytime and high in the nighttime, and hourly precipitation greater than 1 mm mostly occurs at nighttime. Weak precipitation during the daytime may be caused by air advection, and strong precipitation at nighttime may be closely related with air convection. Both humidity and wind speed profiles show obvious fluctuation when precipitation occurs, and the greater the precipitation intensity, the larger the fluctuation. Moreover, the fluctuation of wind speed is small in the morning, large at noon and largest at night, presenting a similar diurnal cycle to that of convective activity over the TP, which is conductive to nighttime precipitation. Additionally, the inverse layer is accompanied by the inverse humidity layer, and wind speed presents multi-peaks distribution in its vertical structure. Both of these are closely related with the underlying surface and topography of Jiulong. More studies on physical mechanism and numerical simulation are necessary for better understanding the atmospheric phenomenon over the TP.

Abstract. The evaluation of precipitable water vapor (PWV) derived from the advanced Medium Resolution Spectral Imager (MERSI-II) onboard FengYun-3D is performed with the PWV from Integrated Global Radiosonde Archive (IGRA) based on 626 sites (54214 match-ups) in total during 2018–2021. The averaged PWVs from MERSI-II and IGRA both present the distribution opposite to latitude, with great PWV mostly found in the tropics. In general, a good consistency exists between the PWVs of MERSI-Ⅱ and IGRA, and their correlation coefficient is 0.9400 and root mean squared error (RMSE) is 0.31 cm. The peak values of mean bias (MB) and the mean relative bias (MRB) are 0.00 cm and −2.38 %, with the standard deviations of 0.25 cm and 16.8 %, respectively. For most sites, the PWV is underestimated with the MB between −0.28 cm and 0.05 cm. However, there is also overestimated PWV, which is mostly distributed in the surrounding areas of the Black Sea and the middle of South America. The peak values of MB are found in February and July over the Southern and Northern Hemisphere, respectively. More than 66.91 % of retrievals falling within the except error (EE) envelope during all months. Overall, the MRB and RMSE become larger with the increasing temporal and distance discrepancy, and it is contrast for EE and correlation coefficient. Besides, the distance discrepancy impacts the evaluation more. The application of PWV product over Qinghai-Tibet Plateau shows that the transport of water vapor along the Brahmaputra Grand Canyon is obvious and it is more significant in July.

Atmospheric water vapor plays a key role in Earth's radiation balance and hydrological cycle, and the precipitable-water-vapor (PWV) product under clear-sky conditions has been routinely provided by the advanced Medium Resolution Spectral Imager (MERSI-II) on board Fengyun-3D since 2018. The global evaluation of the PWV product derived from MERSI-II is performed herein by comparing it with PWV from the Integrated Global Radiosonde Archive (IGRA) based on a total of 462 sites (57 219 matchups) during 2018–2021. The monthly averaged PWV from MERSI-II presents a decreasing distribution of PWV from the tropics to the polar regions. In general, a sound consistency exists between PWV values of MERSI-II and IGRA; their correlation coefficient is 0.951, and their root mean squared error (RMSE) is 0.36 cm. The histogram of mean bias (MB) shows that the MB is concentrated around zero and mostly located within the range from −1.00 cm to 0.50 cm. For most sites, PWV is underestimated with the MB between −0.41 and 0.05 cm. However, there is also an overestimated PWV, which is mostly distributed in the area surrounding the Black Sea and the middle of South America. There is a slight underestimation of MERSI-II PWV for all seasons with the MB value below −0.18 cm, with the bias being the largest magnitude in summer. This is probably due to the presence of thin clouds, which weaken the radiation signal observed by the satellite. We also find that there is a larger bias in the Southern Hemisphere, with a large value and significant variation in PWV. The binned error analysis revealed that the MB and RMSE increased with the increasing value of PWV, but there is an overestimation for PWV smaller than 1.0 cm. In addition, there is a higher MB and RMSE with a larger spatial distance between the footprint of the satellite and the IGRA station, and the RMSE ranged from 0.33 to 0.47 cm. There is a notable dependency on solar zenith angle of the deviations between MERSI-II and IGRA PWV products.

. Atmospheric water vapor plays a key role in the Earth's radiation balance and hydrological cycle, and the precipitable 10 water vapor (PWV) product under clear sky condition has been routinely provided by the advanced Medium Resolution 11 Spectral Imager (MERSI-II) onboard FengYun-3D since 2018. The global evaluation of the PWV product precipitable water 12 vapor (PWV) derived from MERSI-Ⅱ the advanced Medium Resolution Spectral Imager (MERSI-II) onboard FengYun-3D is 13 performed herein by comparing with the PWV from the Integrated Global Radiosonde Archive (IGRA) based on a total of 462 14 sites (57,219 match-ups) during 2018–2021. The monthly averaged PWV from MERSI-II presents a decreasing distribution 15 of PWV from the tropics to the polar regions. In general, a sound consistency exists between the PWVs of MERSI-Ⅱ and 16 IGRA, and their correlation coefficient is 0.951 and root mean squared error (RMSE) is 0.36 cm. The histogram of mean bias 17 (MB) shows that the MB is concentrated around zero and mostly located within the range from -1.00 cm to 0.50 cm. For most 18 sites, the PWV is underestimated with the MB between -0.41 cm and 0.05 cm. However, there is also overestimated PWV, 19 which is mostly distributed in the surrounding area of the Black Sea and the middle of South America. There is a slight 20 underestimation of MERSI-Ⅱ PWV for all seasons with the MB value below -0.18 cm, with the bias being the largest magnitude 21 in summer. This is probably due to the presence of thin clouds, which weaken the radiation signal observed by the satellite. 22 We also find that there is a larger bias in the Southern Hemisphere, with a large value and significant variation of PWV. The 23 binned error analysis revealed that the MB and RMSE increased with the increasing value of PWV, but there is an 24 overestimation for PWV smaller than 1.0 cm. In addition, there is a higher MB and RMSE with a larger spatial distance 25 between the footprint of the satellite and the IGRA station, and the RMSE ranged from 0.33 cm to 0.47 cm. There is a notable 26 dependency on solar zenith angle of the deviations between MERSI-Ⅱ and IGRA PWV products.