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Accurate short-term forecasting of intensive rainfall has high practical value but remains difficult to achieve. Based on deep learning and spatial–temporal sequence predictions, this paper proposes a hierarchical dynamic graph network. To fully model the correlations among data, the model uses a dynamically constructed graph convolution operator to model the spatial correlation, a recurrent structure to model the time correlation, and a hierarchical architecture built with graph pooling to extract and fuse multi-level feature spaces. Experiments on two datasets, based on the measured cumulative rainfall data at a ground station in Fujian Province, China, and the corresponding numerical weather grid product, show that this method can model various correlations among data more effectively than the baseline methods, achieving further improvements owing to reversed sequence enhancement and low-rainfall sequence removal. [ABSTRACT FROM AUTHOR]

Surface ozone (O3) is influenced not only by anthropogenic emissions but also by meteorological factors, with wind direction being one of the most overlooked factors. Here, we combine the observational data of both O3 and wind flow to compare the variation in surface O3 with wind direction between coastal and inland regions of Fujian, a province in the southeast coast of China with complicated topography. We further conduct a numerical simulation using a global chemical transport model, GEOS-Chem, to interpret the observational results, explore the linkages between these O3 variations and wind flows, and identify the dominant processes for the occurrence of high O3 that varies with wind flows. The results from the observations over 2015–2021 suggest that, over coastal regions, surface O3 concentrations show a strong dependence on wind flow changes. On average, during the daytime, when southeasterly winds prevail, the mean of O3 concentrations reaches 83.5 μg/m3, which is 5.0 μg/m3 higher than its baseline values (the mean O3 concentrations), while the northwesterly winds tend to reduce surface O3 by 6.4 μg/m3. The positive O3 anomalies with southeasterly wind are higher in the autumn and summer than in the spring and winter. During the nighttime, the onshore northeasterly winds are associated with enhanced O3 levels, likely due to the airmass containing less NO2, alleviating the titration effects. Over inland regions, however, surface O3 variations are less sensitive to wind flow changes. The GEOS-Chem simulations show that the prevailing southeasterly and southwesterly winds lead to the positive anomaly of chemical reactions of O3 over coastal regions, suggesting enhanced photochemical production rates. Furthermore, southeasterly winds also aid in transporting more O3 from the outer regions into the coastal regions of Fujian, which jointly results in elevated surface O3 when southeasterly winds dominates. When affected by wind flows in different directions, the chemical reaction and transport in the inland regions do not exhibit significant differences regarding their impact on O3. This could be one of the reasons for the difference in O3 distribution between coastal and inland regions. This study could help to deepen our understanding of O3 pollution and aid in providing an effective warning of high-O3 episodes. [ABSTRACT FROM AUTHOR]

The urban climate has a critical influence on developing sustainable cities, and one important factor is the urban wind environment. Moreover, refining urban wind fields is required for the quantitative assessment of urban wind environments. Computational fluid dynamics (CFD) is a powerful tool for modeling the wind flow characteristics in urban areas. Although CFD has been widely used in various fields, its use for simulating urban wind fields has limitations because of the complexity of urban building models and the high computational workload. Accordingly, we consider the generalization parameters in the vertical and horizontal directions based on the CFD results and the building topology based on the state of the building nodes. We perform a two-dimensional generalization of building clusters, conduct spatial analysis in a geographic information system (GIS), and generate three-dimensional models. This generalization scheme is applied to Meiling Street in Jinjiang City, Fujian Province, China. The results indicate that the generalization decreases the number of buildings from 7003 to 3367 and the computation time from 11 h and 26 min to 10 h and 25 min. The computation efficiency is improved by 8.89%, with 1.85% changes in the average wind speed ratio. This scheme substantially improves the computational efficiency of urban wind field CFD simulations by reducing the geometric model's complexity without compromising the accuracy. This strategy is suitable for simulating large-scale urban wind fields. [ABSTRACT FROM AUTHOR]

The urban wind environment is an important element of urban microclimates and plays an important role in the quality of the urban environment. The computational fluid dynamics (CFD) simulation method is an important means for urban wind field research. However, CFD simulation has high requirements for computer hardware and software. In this paper, based on geographic information system (GIS) technology, a new building data generalization method was developed to solve the problems of a huge amount of data and calculations in urban-scale CFD wind field simulations. Using Fluent software and high-precision urban building geographic information data with elevation attributes, the method was applied to Jinjiang City, Fujian Province, China. A CFD simulation of the wind field of Jinjiang City was implemented, and detailed, intuitive wind field information was obtained, which were compared with the measured data. The results show that the building data generalization method could effectively improve the efficiency of the city's overall wind field CFD simulation. The simulated wind speed was significantly correlated with the measured data, but it was overestimated. The simulated wind direction was consistent with the measured data of most stations. The simulation results were reasonable and could provide reference for application and subsequent research. [ABSTRACT FROM AUTHOR]

This study analyzed the spatiotemporal variation characteristics of extreme maximum temperature events (EMTEs) in East China in the last 60 years and investigated the relationship between EMTEs and atmospheric circulation. The arithmetic mean, linear trend, and the Mann–Kendall test were applied to daily maximum temperature (DMT) data (1961–2020) from 345 meteorological observation stations with complete observation records in East China to compile four characteristic indexes of EMTEs: intensity, consecutive days, first days, and last days. The analysis of these indexes revealed the following: (1) The annual number of days with a DMT ≥ 35 °C increased at the rate of 1.45 d/decade (p ≤ 0.05); the mutation occurred in 2009 with a growth rate before and after the mutation of 0.4 and 2.8 d/10a, respectively. Most of the region showed an increasing trend, with the most significant increase to the east of the Yangtze River Delta, in coastal areas of Zhejiang and Fujian, and south of Jiangxi. (2) The EMTE intensity rose at the rate of 0.15 °C/decade (p ≤ 0.05). Most areas showed a significant upward trend, and the historical extreme values of EMTEs mostly appeared in the 21st century. (3) The annual mean growth rate of consecutive EMTE days was 0.24 d/10a, which increased significantly after 2003. In comparison with 1961–2002, consecutive EMTE days increased by 35% during 2003–2020. The rate of increase was significant (p ≤ 0.05) for most areas east of the Yangtze River Delta, coastal areas of Zhejiang and Fujian, and areas south of Jiangxi. The mean mutation time was 2003, and the growth rate before and after the mutation was 0.4 and 1.4 d/10a, respectively. (4) The mean first EMTE day advanced and the mean last EMTE day became delayed, especially in the 21st century. Over the study period, the mean first EMTE day advanced by 12 days and the mean last EMTE day became delayed by 7 days. (5) The analysis of National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis data indicated that an increasing number of EMTEs have occurred in East China. The reason is that this region experiences atmospheric subsidence resulting from the intensification and westward extension of the subtropical high coupled with the weakening and northward displacement of the mid-latitude westerly trough. [ABSTRACT FROM AUTHOR]

Stationary models are usually applied for wind characteristics analysis. However, nonstationarity has been found in the field measurements of typhoons in recent studies; therefore, using traditional models with stationary assumptions to conduct wind characteristics is inadequate. In this research, data acquisition of typhoon wind speeds and monsoon are conducted based on the wind field measurements. Wind speeds of typhoon "Maria" passing through Pintan, Fujian Province, China and the monsoon from 2017.10–2018.10 were obtained to investigate wind characteristics. The run test method is utilized to show that non-stationarity exists in both typhoon and monsoon wind speed, and the percent of non-stationary increases with the increase in time interval. Additionally, results show that stronger non-stationarity exists in typhoon wind speed compared with monsoons. Based on a self-adaptive procedure to extract time varying mean wind speed, a non-stationary model is established to compare with the non-stationary model, which has been applied in the traditional wind characteristic analysis. The fluctuating wind characteristics such as turbulence intensity, gust factor, turbulence integral scale, and wind speed spectrum are analyzed to compare the two models. Results show that the difference of such characteristics between the two models increases with the time interval, indicating the necessity of consideration of non-stationary models, especially for design specifications with larger time intervals. Influences of time intervals are investigated, and relevant recommendations are provided for wind resistance specifications. Our conclusions may provide reference for wind resistance design in engineering applications. [ABSTRACT FROM AUTHOR]

Humid subtropical China is an "oasis" relative to other dry subtropics of the world due to the prevailing of the East Asian summer monsoon (EASM). Although many long climate sensitive tree-rings have been published to understand the historical climate change over various regions in China, long tree-ring chronologies in humid subtropical China are rare due to the difficulty to find old growth trees. This study established a tree-ring chronology spanning from 1776 to 2016 from Cryptomeria fortunei Hooibrenk ex Otto et Dietr in Liancheng area of humid subtropical China, which is also currently the longest chronology in Fujian province. Similar to the climate-growth relationships in neighboring regions, our tree-ring chronology is limited by cold temperature in winter and spring and drought in summer. In addition, a drought stress before the growing season also played a role in limiting the growth of our tree rings. Our climate sensitive tree rings showed different correlations with the Pacific Decadal Oscillation (PDO) in different periods, possibly via modulation of the EASM. [ABSTRACT FROM AUTHOR]