利用常规气象观测资料、 1°×1° NCEP再分析资料、 FY-2E逐时云顶亮温(TBB)资料和1 h降水资料, 对2012年7月24-31日内蒙古全区性暴雨过程进行了分析.结果表明: (1)此次暴雨天气过程发生在南亚高压东伸、 贝加尔湖阻塞形势稳定和西太平洋副热带高压位置偏北的大尺度环流背景条件下.(2)地面辐合以及700 hPa切变和涡旋是暴雨发生的影响系统, 中尺度对流系统(MCS)是暴雨过程中短时强降水的直接制造者, 中尺度雨团出现在MCS边缘TBB梯度最大处冷空气一侧.(3)暴雨发生时南海季风涌活跃, 为暴雨的发生提供了充沛水汽条件, 暴雨发生前对流层低层存在大量不稳定能量, 高空急流入口区右侧与低空急流出口区左侧相叠置耦合, 以及地形的强迫动力抬升机制, 触发了暴雨天气.(4)内蒙古西部地区水汽输送条件较差是该地区较少发生暴雨的主要原因.

冰晶和雪花的产生及融化是一个还未解决的问题。本文指出了研究冰晶雪花融化问题的重要意义,介绍了日本、美国、英国等国科学家在野外及实验室模拟冰晶、雪花融化的一些主要研究结果。对各类冰晶、雪花融化后形成水滴或分裂成多个水滴的个数作者利用实验资料作了分析比较。最后,对如冰系统理论,云中冰晶、雹胚来源,微下击暴流,中尺度对流系统层状区中尺度环流特征与融化的关系及高压传输线上冰、雪融化问题的解决思路也作了有关介绍。

降水与云的发生发展密切相关，研究强对流云特征，对降水机理分析、降水监测和预报具有重要意义。2022年7月15日地处西北半干旱区的甘肃陇东出现一次特大暴雨过程，多站日降水量和小时降水量均突破历史极值，本文基于FY-4A、FY-4B静止卫星扫描成像辐射计（advanced geostationary radiation imager， AGRI）数据，FY-3D极轨卫星微波湿度计（micro-wave humidity sounder， MWHS）和微波温度计（micro-wave temperature sounder， MWTS）融合产品，分析此次特大暴雨事件中云宏微观特征、云系演变特征及大气环境条件。结果表明：（1）暴雨云系的云顶类型为过冷水云、混合云、不透明冰云和多层云等，发生强降水的云顶类型以不透明冰云为主，云顶高度达14 km以上；暴雨云系云体深厚，主要为小粒径冰云且伴有强烈上升气流。（2）此次暴雨事件存在对流云团新生、合并及加强过程，对流云团稳定维持是导致特大暴雨发生的主要原因，降水与云顶相当黑体亮温（black body temperature， TBB）及其变化的关系密切，TBB低值区对应强降水，且强降水发生前TBB迅速下降。（3）强降水发生前大气层结表现出浅层对流不稳定的特征，中低层强烈增湿是对流不稳定发展的主要原因，低层绝对湿度的差异造成了不稳定条件及降水量级的差异。

2022年5月4—6日，新疆伊犁河谷出现极端暴雨天气，多站降水量突破历史极值。使用地面自动站逐时降水资料、美国国家环境预报中心/美国国家大气研究中心（National Centers for Environmental Prediction/National Center for Atmospheric Research，NCEP/NCAR）1°×1°再分析资料，分析此次极端暴雨事件的水汽特征和不稳定机制。结果表明：1）在500 hPa中纬度短波和低层辐合切变环流背景下，伊犁河谷可能发生极端暴雨天气，向西开口的“喇叭口”地形特征导致地形辐合和强迫抬升，增强了局地暴雨发生的动力触发机制。2）水汽主要来源于地中海、红海及里咸海地区，存在偏西和西南两条主要输送路径。低层偏西路径水汽输送强度大于中高层的西南路径，西边界为主要水汽输入边界，水汽输入贡献比约为85%，且从地面至700 hPa的强水汽辐合有利于水汽快速积聚。3）降水前对流层低层存在对流不稳定为暴雨天气积聚不稳定能量，对强降水的发生起重要作用；降水期间，对流层低层受对流不稳定影响，而对流层中高层受条件对称不稳定影响，这两种不稳定机制共同作用造成此次极端暴雨事件的发生。

黄河生态带建设是各地落实国家黄河战略开展的重要行动。本文以正面临林地、草地、湿地衰退，沙漠化、水土流失、盐碱化、生物栖息受影响等七大复合性生态问题的黄河流域内蒙古段为例，从整体性、系统性、独特性三方面提出了多维复合空间视角下黄河生态带构建的理论框架和实现途径。在流域层面，将林地、草地、湿地三类生态空间的环境质量评价结果和沙漠化、水土流失、盐碱化、生物四种生态过程的安全性评价结果叠加，构建低、中、高安全水平的流域综合生态安全格局。在河流层面，研判出黄河干流大堤外10 km和一级支流两侧2 km岸边带内低安全水平区域面积占比最高，由此判别出黄河生态带的构成和空间范围。进一步结合不同地域景观特征划定其保护修复与治理区划。

利用常规观测资料、自动加密站观测资料、NCEP（1°×1°）再分析资料、FY-2E卫星云图以及多普勒雷达资料，对2016 年8月16—18日内蒙古中西部区域性极端大暴雨天气的成因进行分析。结果表明：暴雨落区位于副热带高压边缘、700～850 hPa“人” 字型切变线、河套气旋前部等压线密集处的叠置区；深厚的湿层以及极端暴雨发生前6 h中低层显著增湿为暴雨的发生输送了充沛的水汽；散度辐合中心和上升运动中心叠置且加强，更有利于强烈上升运动形成，是暴雨发生发展和维持的动力机制；暴雨爆发前对流有效位能（CAPE）有明显跃升，暖云层厚度加大，有利于降水效率的提高；暴雨时段内有两个中尺度对流系统（MCS）以相同路线沿着副热带高压584 dagpm线边缘、阴山山脉东西方向自西向东移动；短时强降水（＞30 mm·h-1）和云顶亮温（TBB）低值中心区（≤-52 ℃）以及TBB等值线密集区有良好的对应关系。

利用常规观测资料、 NCEP 1°×1°再分析资料、 逐时和逐5 min自动站降水资料以及昆明CINRAD/CC多普勒雷达资料， 针对滇中地区2021年主汛期不同影响系统下的3次短时强降水过程， 对比分析了降水特征、 环流形势、 大气环境特征以及雷达回波的结构、 形状、 演变的基本特征。结果表明： 3次短时强降水过程影响系统差异主要在于500 hPa天气系统不同， 700 hPa都有切变线影响， 但是形成原因各异， 地面均有辐合线或弱冷锋配合。3次过程的环境条件在不稳定层结、 近地层水汽、 垂直风切变方面与中国其他地区短时强降水发生的环境条件具有一致性， 但是在大气整层可降水量、 对流有效位能、 SWEAT指数等方面存在明显差异。对流回波的形状有点状回波、 块状回波、 带状回波、 絮状回波等。对流风暴分为高质心型、 低质心型以及混合型； 短时强降水有单独出现某种对流风暴类型的阶段， 也有多种对流风暴类型同时出现的阶段； CAPE值和SWEAT指数与对流风暴类型具有一定的相关关系。强回波剖面呈柱状结构或者塔状结构， 35 dBz强回波接地， 而没有悬垂特征。短时强降水多产生于长时间停滞型或移动缓慢型的对流回波， 还有部分短时强降水产生于“列车效应”中。短生命周期的单体生消形成的短时强降水持续时间绝大部分在1 h以内， 但是单体合并组织和反复生消或者“列车效应”形成的短时强降水持续时间常在1~3 h。高质心型对流风暴产生的瞬时雨强可达10 mm·（5min）^-1以上， 低质心型和混合型对流风暴可产生的雨强范围较大， 大多在3~10 mm·（5min）^-1， 少数也可达到10 mm·（5min）^-1以上。

研究山西极端暴雨发生规律对开展预报预警、灾害防御具有重要意义。本文利用常规观测资料和欧洲中期天气预报中心（European Centre for Medium-Range Weather Forecasts，ECMWF）第五代大气再分析资料（ERA5），采用标准化距平作为异常度，运用环流分析和物理量诊断等方法，研究1981—2018年6—9月山西17次极端暴雨的气候特征、环流影响系统和水汽异常特征。结果表明：山西极端暴雨主要出现在7—8月，暴雨区主要位于中南部，2010年以来极端暴雨明显多发；影响系统主要是700 hPa低涡和台风系统，有偏南和偏东两支水汽通道。极端暴雨过程中，低层水汽含量明显偏高，从暴雨区平均比湿的过程最大值看，大部分过程850 hPa超过14.2 g·kg^-1，700 hPa则可超过9.8 g·kg^-1、对应暴雨区平均异常度达1.6 以上；水汽的极端性在低层水汽通量辐合中心表现突出，17次极端暴雨700、850 hPa暴雨区水汽通量辐合中心过程最大值的异常度均值分别达-8、-6，其中台风减弱低压影响下的极端暴雨850 hPa水汽通量辐合中心最大异常度达-12。根据以上环流和水汽特征建立极端暴雨概念模型，并给出极端暴雨低层水汽含量和水汽通量辐合强度预报参考指标。

With the Microwave Humidity Sounder-2 (MWHS-2)/Fengyun (FY)-3D in operation, this is the first study to evaluate the impact of a joint assimilation of MWHS-2 radiances under all-sky conditions from both the FY-3C and FY-3D satellites on typhoon forecasting within regional areas. In this study, Typhoon Hagupit in 2020 was chosen to investigate the impacts of assimilating MWHS-2 radiances; the forecasting performances of the joint assimilation method were slightly better than the experiments assimilating MWHS-2 observations from FY-3C or FY-3D only, and the results of the latter two experiments were comparable, especially in terms of the landfall location of Hagupit. With additional assimilated cloud- and precipitation-affected MWHS-2 observations, improved typhoon track and intensity forecasts as well as forecasts of the precipitation caused by Hagupit were achieved due to the improved analyses of relative humidity, temperature and wind fields around Hagupit compared to the clear-sky assimilation experiments. In addition, the channel-selection scheme evidently affected the forecasting performance; that is, the radiances from the MWHS-2 118 GHz and 183 GHz channels provided opposite results in terms of the Hagupit track, and this finding needs further investigation in the future.

Different radiometer sensors have different frequencies, spatial resolutions, and time resolutions, which lead to inconsistencies in ice drift products retrieved by radiometer sensors. Based on the continuous maximum cross-correlation method, in this paper, we used China’s FY-3 and HY-2 satellite radiometer data to generate sea ice drift products; we further evaluated the consistency between them and sea ice drift products retrieved from AMSR2 and SSMIS satellite radiometer data, which could help in future retrieval accuracies of more radiometer sea ice drift products. The results show that ice drift products with good reliability can be obtained by retrievals using 37 and 89 GHz channels of FY-3 and HY-2 radiometer bright temperature data. Compared with the buoy data, the root mean square errors (RMSEs) of the 37 GHz HY-2 sea ice drift product (at an interval of 6 days) were 1.40 cm/s and 7.31° for speed and direction, respectively, and the relative errors (REs) were 5.78% and 6.44%, respectively. The RMSEs of the 37 GHz FY-3 sea ice drift product were 0.77 cm/s and 6.49° for speed and direction, respectively, and the REs were 4.38% and 9.23%, respectively. Moreover, comparisons between sea ice drift vectors derived from AMSR2 and SSMIS satellites showed good quantitative agreement.

Precipitation affects many aspects of our everyday life. It is the primary source of freshwater and has significant socioeconomic impacts resulting from natural hazards such as hurricanes, floods, droughts, and landslides. Fundamentally, precipitation is a critical component of the global water and energy cycle that governs the weather, climate, and ecological systems. Accurate and timely knowledge of when, where, and how much it rains or snows is essential for understanding how the Earth system functions and for improving the prediction of weather, climate, freshwater resources, and natural hazard events. The Global Precipitation Measurement (GPM) mission is an international satellite mission specifically designed to set a new standard for the measurement of precipitation from space and to provide a new generation of global rainfall and snowfall observations in all parts of the world every 3 h. The National Aeronautics and Space Administration (NASA) and the Japan Aerospace and Exploration Agency (JAXA) successfully launched the Core Observatory satellite on 28 February 2014 carrying advanced radar and radiometer systems to serve as a precipitation physics observatory. This will serve as a transfer standard for improving the accuracy and consistency of precipitation measurements from a constellation of research and operational satellites provided by a consortium of international partners. GPM will provide key measurements for understanding the global water and energy cycle in a changing climate as well as timely information useful for a range of regional and global societal applications such as numerical weather prediction, natural hazard monitoring, freshwater resource management, and crop forecasting.

This study examines the synoptic- and mesoscale processes leading to the generation of three extreme rainfall episodes with hourly rates of greater than 100 mm h−1 over the southern, middle, and northern portions of the eastern foothills of Mt. Taihang in North China on 19–20 July 2016. The extreme rainfall episodes took place over the 200–600-m elevation zones in the southern and northern portions but also over the lower elevations in the middle portion of the target region, sequentially during late morning, early evening, and midnight hours. Echo training accounted for the development of a linear convective system in the southern region after the warm and moist air carried by a southeasterly low-level jet (LLJ) was lifted to condensation as moving across Mt. Yuntai. In contrast, two isolated circular-shaped convective clusters, with more robust convective cores in its leading segment, developed in the northern region through steep topographical lifting of moist northeasterly airflow, albeit conditionally less unstable. Extreme rainfall in the middle region developed from the convergence of a moist easterly LLJ with a northerly colder airflow associated with an extratropical cyclogenesis. Results reveal that the LLJs and associated moisture transport, the intensifying cyclone interacting with a southwest vortex and its subsequent northeastward movement, and the slope and orientation of local topography with respect to and the stability of the approaching airflows played different roles in determining the timing and location, the extreme rainfall rates, and convective organizations along the eastern foothills of Mt. Taihang.

Currently, humidity information can be obtained from the Microwave Humidity Sounder-2 (MWHS-2) mounted on the polar-orbiting satellites FY-3C and FY-3D. However, making full use of the MWHS-2 data remains a challenge, particularly in the application of regional numerical weather models. This study is the first to include MWHS-2 radiance data in the Rapid-refresh Multi-scale Analysis and Prediction System—Short-term (RMAPS-ST) regional model. The results and impact of MWHS-2 radiance data assimilation were investigated and evaluated. It is found that MWHS-2 radiance data can be effectively assimilated in the RMAPS-ST after a series of quality control and variational bias correction. Benefits could be obtained in the reduction of background departures for each humidity sounding channel. Assimilation experiments over a period of one month were carried out, and the impacts of MWHS-2 radiances were quantitatively analyzed on the forecasts of RMAPS-ST system. The results showed that MWHS-2 saw a small but significant improvement for low-level humidity of short-range forecast, by 16.5% and 3.2% in terms of mean bias and root-mean-square error, respectively. The positive impact on short-range forecast also can be found for middle and low level temperature and wind. For quantitative precipitation forecast, the assimilation of MWHS-2 radiances increased the score skills of different rainfall levels in the first 12 h forecast by an average of 1.4%. There was a slight overall improvement in the 24-h precipitation forecast for over-estimation and false alarm of 3-h accumulated rainfall below 1.0 mm, with 0.75% and 0.36%, respectively. The addition of MWHS-2 radiance data gives a small positive impact on low-level humidity, temperature, and wind in the RMAPS-ST regional model, and it also improves short-range forecast of rainfall, particularly in the first 12 h of the forecast.