An Overview of Research and Forecasting on Rainfall Associated with Landfalling Tropical Cyclones

The ability to forecast heavy rainfall associated with landfalling tropical cyclones （LTCs） can be improved with a better understanding of the mechanism of rainfall rates and distributions of LTCs. Research in the area of LTCs has shown that associated heavy rainfall is related closely to mechanisms such as moisture transport, extratropical transition （ET）, interaction with monsoon surge, land surface processes or topographic effects, mesoscale convective system activities within the LTC, and boundary layer energy transfer etc.. LTCs interacting with environmental weather systems, especially the westerly trough and mei-yu front, could change the rainfall rate and distribution associated with these mid-latitude weather systems. Recently improved technologies have contributed to advancements within the areas of quantitative precipitation estimation （QPE） and quantitative precipitation forecasting （QPF）. More specifically, progress has been due primarily to remote sensing observations and mesoscale numerical models which incorporate advanced assimilation techniques. Such progress may provide the tools necessary to improve rainfall forecasting techniques associated with LTCs in the future.

A STUDY OF THE INFLUENCE OF MICROPHYSICAL PROCESSES ON TYPHOON NIDA(2016) USING A NEW DOUBLE-MOMENT MICROPHYSICS SCHEME IN THE WEATHER RESEARCH AND FORECASTING MODEL

The basic structure and cloud features of Typhoon Nida(2016) are simulated using a new microphysics scheme(Liuma) within the Weather Research and Forecasting(WRF) model. Typhoon characteristics simulated with the Liuma microphysics scheme are compared with observations and those simulated with a commonly-used microphysics scheme(WSM6). Results show that using different microphysics schemes does not significantly alter the track of the typhoon but does significantly affect the intensity and the cloud structure of the typhoon. Results also show that the vertical distribution of cloud hydrometeors and the horizontal distribution of peripheral rainband are affected by the microphysics scheme. The mixing ratios of rain water and graupel correlate highly with the vertical velocity component and equivalent potential temperature at the typhoon eye-wall region. According to the simulation with WSM 6 scheme,it is likely that the very low typhoon central pressure results from the positive feedback between hydrometeors and typhoon intensity. As the ice-phase hydrometeors are mostly graupel in the Liuma microphysics scheme, further improvement in this aspect is required.

A Methodological Study on Using Weather Research and Forecasting(WRF) Model Outputs to Drive a One-Dimensional Cloud Model

A new method for driving a One-Dimensional Stratiform Cold （1DSC） cloud model with Weather Research and Fore casting （WRF） model outputs was developed by conducting numerical experiments for a typical large-scale stratiform rainfall event that took place on 4-5 July 2004 in Changchun, China. Sensitivity test results suggested that, with hydrometeor pro files extracted from the WRF outputs as the initial input, and with continuous updating of soundings and vertical velocities （including downdraft） derived from the WRF model, the new WRF-driven 1DSC modeling system （WRF-1DSC） was able to successfully reproduce both the generation and dissipation processes of the precipitation event. The simulated rainfall intensity showed a time-lag behind that observed, which could have been caused by simulation errors of soundings, vertical velocities and hydrometeor profiles in the WRF output. Taking into consideration the simulated and observed movement path of the precipitation system, a nearby grid point was found to possess more accurate environmental fields in terms of their similarity to those observed in Changchun Station. Using profiles from this nearby grid point, WRF-1DSC was able to repro duce a realistic precipitation pattern. This study demonstrates that 1D cloud-seeding models do indeed have the potential to predict realistic precipitation patterns when properly driven by accurate atmospheric profiles derived from a regional short range forecasting system, This opens a novel and important approach to developing an ensemble-based rain enhancement prediction and operation system under a probabilistic framework concept.

Research on the short-term fishery forecasting of Spanish mackerel (Scomberomerus niphonius)

-This paper presents the use of the hydrographic factors in short-term fishery forecasting of the spawning migration stock of the Spanish mackerel and salinity describes more concretely the correlativity of water temperature, salinity and air temperature with the fishing season in spring. The data have been collected from the hydrographic environmental investigation at the fixed position on the sea and the telegraph recordings of the drift net operation in the spring fishing season during the period of April and May from 1972 to 1980. The correlation coefficients of various factors with the data of the fishing season have been calculated by using the monadic regression method.The main reference targets of the forecasting are: (1) By using the upper-layer water temperature as the forecasting factor at the beginning of the fishing season, the accuracy is high; (2) the distribution and location of the isotherm of the upper-layer water at 10°C at the beginning of April are used as an important factor for determining the location and the range of the central fishing area of the Spanish mackerel; (3) whether a low temperature area at 8°C existing at the Estuary of the Changjiang River can be used as an important factor for forecasting the migration distribution of the Spanish mackerel moving to the north.

Improvement and Evaluation of the Latest Version of WRF-Lake at a Deep Riverine Reservoir

The WRF-lake vertically one-dimensional(1D)water temperature model,as a submodule of the Weather Research and Forecasting(WRF)system,is being widely used to investigate water-atmosphere interactions.But previous applications revealed that it cannot accurately simulate the water temperature in a deep riverine reservoir during a large flow rate period,and whether it can produce sufficiently accurate heat flux through the water surface of deep riverine reservoirs remains uncertain.In this study,the WRF-lake model was improved for applications in large,deep riverine reservoirs by parametric scheme optimization,and the accuracy of heat flux calculation was evaluated compared with the results of a better physically based model,the Delft3D-Flow,which was previously applied to different kinds of reservoirs successfully.The results show:(1)The latest version of WRF-lake can describe the surface water temperature to some extent but performs poorly in the large flow period.We revised WRF-lake by modifying the vertical thermal diffusivity,and then,the water temperature simulation in the large flow period was improved significantly.(2)The latest version of WRF-lake overestimates the reservoir-atmosphere heat exchange throughout the year,mainly because of underestimating the downward energy transfer in the reservoir,resulting in more heat remaining at the surface and returning to the atmosphere.The modification of vertical thermal diffusivity can improve the surface heat flux calculation significantly.(3)The longitudinal temperature variation and the temperature difference between inflow and outflow,which cannot be considered in the 1D WRF-lake,can also affect the water surface heat flux.

城市化对北京单次极端高温过程影响的数值模拟研究

城市化对高温热浪的频次和强度具有重要影响,但目前对于城市化影响高温热浪过程的机理了解还不充分。本文利用WRF模式,对2010年7月2~6日(北京时)北京一次高温过程进行了模拟,分析了城市化对此次高温过程的影响机理。采用优化后的WRF模式,能够模拟出北京连续5日高温的特征和城市热岛强度的变化。城市下垫面的不透水性决定了城区2 m高度处相对湿度低于乡村,削弱了城区通过潜热调节城市气温的能力。日落后,城市感热通量下降缓慢,城区降温速率小于乡村,夜间边界层稳定、高度低,风速小,抑制了城乡之间能量的传输,形成了夜间强的城市热岛强度,造成夜间城市气温明显高于乡村。日出后城乡地面感热通量、潜热通量迅速上升,边界层稳定性下降。午后,城市下垫面分别为地表感热通量和潜热通量的高、低值中心,通过潜热调节气温的能力被削弱;边界层稳定性降低,有利于能量的垂直扩散;此时,城市热岛强度小于夜间。因此,北京城市下垫面形成了明显的城市热岛效应,加重了城区极端高温事件的强度。此外,在这次高温热浪期间,中国东部大部分地区受到大陆暖高压控制,晴空少云,西北气流越山后形成焚风效应,是北京地区高温热浪形成的天气背景。

Simulation of Quasi-Linear Mesoscale Convective Systems in Northern China：Lightning Activities and Storm Structure

Two intense quasi-linear mesoscale convective systems（QLMCSs） in northern China were simulated using the WRF（Weather Research and Forecasting） model and the 3D-Var（three-dimensional variational） analysis system of the ARPS（Advanced Regional Prediction System） model.A new method in which the lightning density is calculated using both the precipitation and non-precipitation ice mass was developed to reveal the relationship between the lightning activities and QLMCS structures.Results indicate that,compared with calculating the results using two previous methods,the lightning density calculated using the new method presented in this study is in better accordance with observations.Based on the calculated lightning densities using the new method,it was found that most lightning activity was initiated on the right side and at the front of the QLMCSs,where the surface wind field converged intensely.The CAPE was much stronger ahead of the southeastward progressing QLMCS than to the back it,and their lightning events mainly occurred in regions with a large gradient of CAPE.Comparisons between lightning and non-lightning regions indicated that lightning regions featured more intense ascending motion than non-lightning regions;the vertical ranges of maximum reflectivity between lightning and non-lightning regions were very different;and the ice mixing ratio featured no significant differences between the lightning and non-lightning regions.

Simulation of a torrential rainstorm in Xinjiang and gravity wave analysis

We used a weather research and forecasting model to simulate a torrential rainstorm that occurred in Xinjiang, China during June 16–17, 2016. The model successfully simulated the rainfall area, precipitation intensity, and changes in precipitation. We identified a clear wave signal using the two-dimensional fast Fourier transform method; the waves propagated westwards, with wavelengths of 45–20 km, periods of 50–120 min, and phase velocities mainly concentrated in the-25 m/s to-10 m/s range. The results of wavelet cross-spectral analysis further confirmed that the waves were gravity waves, peaking at 11：00 UTC, June 17, 2016. The gravity wave signal was identified along 79.17–79.93°E, 81.35–81.45°E and 81.5–81.83°E. The gravity waves detected along 81.5–81.83°E corresponded well with precipitation that accumulated in 1 h, indicating that gravity waves could be considered a rainstorm precursor in future precipitation forecasts.

Validation of WRF model on simulating forcing data for Heihe River Basin

The research of coupling WRF （Weather Research and Forecasting Model） with a land surface model is enhanced to explore the interaction of the atmosphere and land surface; however, regional applicability of WRF model is questioned. In order to do the validation of WRF model on simulating forcing data for the Heihe River Basin, daily meteorological observation data from 15 stations of CMA （China Meteorological Administration） and hourly meteorological observation data from seven sites of WATER （Watershed Airborne Telemetry Experimental Research） are used to compare with WRF simulations, with a time range of a whole year for 2008. Results show that the average MBE （Mean Bias Error） of daily 2-m surface temperature, surface pressure, 2-m relative humidity and 10-m wind speed were -0.19 ℃, -4.49 hPa, 4.08% and 0.92 m/s, the average RMSE （Root Mean Square Error） of them were 2.11 ℃, 5.37 hPa, 9.55% and 1.73 m/s, and the average R （correlation coefficient） of them were 0.99, 0.98, 0.80 and 0.55, respectively. The average MBE of hourly 2-m surface temperature, surface pressure, 2-m relative humidity, 10-m wind speed, downward shortwave radiation and downward longwave were-0.16 ℃,-6.62 hPa,-5.14%, 0.26 m/s, 33.0 W/m^2 and-6.44 W/m^2, the average RMSE of them were 2.62 ℃, 17.10 hPa, 20.71%, 2.46 m/s, 152.9 W/m^2 and 53.5 W/m^2, and the average R of them were 0.96, 0.97, 0.70, 0.26, 0.91 and 0.60, respectively. Thus, the following conclusions were obtained： （1） regardless of daily or hourly validation, WRF model simulations of 2-m surface temperature, surface pressure and relative humidity are more reliable, especially for 2-m surface air temperature and surface pressure, the values of MBE were small and R were more than 0.96; （2） the WRF simulating downward shortwave radiation was relatively good, the average R between WRF simulation and hourly observation data was above 0.9, and the average R of downward longwave radiation was 0.6; （3） both wind speed and rainfall simulated from WRF model did not agree well with observation data.

Simulations of Microphysics and Precipitation in a Stratiform Cloud Case over Northern China:Comparison of Two Microphysics Schemes

Using the Weather Research and Forecasting(WRF)model with two different microphysics schemes,the Predicted Particle Properties(P3)and the Morrison double-moment parameterizations,we simulated a stratiform rainfall event on 20–21 April 2010.The simulation output was compared with precipitation and aircraft observations.The aircraft-observed moderate-rimed dendrites and plates indicated that riming contributed significantly to ice particle growth at the mature precipitation stage.Observations of dendrite aggregation and capped columns suggested that aggregation coexisted with deposition or riming and played an important role in producing many large particles.The domain-averaged values of the 24-h surface precipitation accumulation from the two schemes were quite close to each other.However,differences existed in the temporal and spatial evolutions of the precipitation distribution.An analysis of the surface precipitation temporal evolution indicated faster precipitation in Morrison,while P3 indicated slower rainfall by shifting the precipitation pattern eastward toward what was observed.The differences in precipitation values between the two schemes were related to the cloud water content distribution and fall speeds of rimed particles.P3 simulated the stratiform precipitation event better as it captured the gradual transition in the mass-weighted fall speeds and densities from unrimed to rimed particles.

Increases in Anthropogenic Heat Release from Energy Consumption Lead to More Frequent Extreme Heat Events in Urban Cities

With economic development and rapid urbanization,increases in Gross Domestic Product and population in fastgrowing cities since the turn of the 21st Century have led to increases in energy consumption.Anthropogenic heat flux released to the near-surface atmosphere has led to changes in urban thermal environments and severe extreme temperature events.To investigate the effects of energy consumption on urban extreme temperature events,including extreme heat and cold events,a dynamic representation scheme of anthropogenic heat release(AHR)was implemented in the Advanced Research version of the Weather Research and Forecasting(WRF)model,and AHR data were developed based on energy consumption and population density in a case study of Beijing,China.Two simulations during 1999−2017 were then conducted using the developed WRF model with 3-km resolution with and without the AHR scheme.It was shown that the mean temperature increased with the increase in AHR,and more frequent extreme heat events were produced,with an annual increase of 0.02−0.19 days,as well as less frequent extreme cold events,with an annual decrease of 0.26−0.56 days,based on seven extreme temperature indices in the city center.AHR increased the sensible heat flux and led to surface energy budget changes,strengthening the dynamic processes in the atmospheric boundary layer that reduce AHR heating efficiency more in summer than in winter.In addition,it was concluded that suitable energy management might help to mitigate the impact of extreme temperature events in different seasons.

A numerical simulation of latent heating within Typhoon Molave

The weather research and forecasting（WRF） model is a new generation mesoscale numerical model with a fine grid resolution（2 km）, making it ideal to simulate the macro-and micro-physical processes and latent heating within Typhoon Molave（2009）. Simulations based on a single-moment, six-class microphysical scheme are shown to be reasonable, following verification of results for the typhoon track, wind intensity, precipitation pattern, as well as inner-core thermodynamic and dynamic structures. After calculating latent heating rate, it is concluded that the total latent heat is mainly derived from condensation below the zero degree isotherm, and from deposition above this isotherm. It is revealed that cloud microphysical processes related to graupel are the most important contributors to the total latent heat. Other important latent heat contributors in the simulated Typhoon Molave are condensation of cloud water, deposition of cloud ice, deposition of snow, initiation of cloud ice crystals, deposition of graupel, accretion of cloud water by graupel, evaporation of cloud water and rainwater,sublimation of snow, sublimation of graupel, melting of graupel, and sublimation of cloud ice. In essence, the simulated latent heat profile is similar to ones recorded by the Tropical Rainfall Measuring Mission, although specific values differ slightly.

Evaluation of Precipitation Datasets from TRMM Satellite and Down-scaled Reanalysis Products with Bias-correction in Middle Qilian Mountain,China

Accurate estimates of precipitation are fundamental for hydrometeorological and ecohydrological studies,but are more difficult in high mountainous areas because of the high elevation and complex terrain.This study compares and evaluates two kinds of precipitation datasets,the reanalysis product downscaled by the Weather Research and Forecasting(WRF)output,and the satellite product,the Tropical Rainfall Measuring Mission(TRMM)Multisatellite Precipitation Analysis(TMPA)product,as well as their bias-corrected datasets in the Middle Qilian Mountain in Northwest China.Results show that the WRF output with finer resolution perfonns well in both estimating precipitation and hydrological simulation,while the TMPA product is unreliable in high mountainous areas.Moreover,bias-corrected WRF output also performs better than bias-corrected TMPA product.Combined with the previous studies,atmospheric reanalysis datasets are more suitable than the satellite products in high mountainous areas.Climate is more important than altitude for the\falseAlarms'events of the TRMM product.Designed to focus on the tropical areas,the TMPA product mistakes certain meteorological situations for precipitation in subhumid and semiarid areas,thus causing significant"falseAlarms"events and leading to significant overestimations and unreliable performance.Simple linear bias correction method,only removing systematical errors,can significantly improves the accuracy of both the WRF output and the TMPA product in arid high mountainous areas with data scarcity.Evaluated by hydrological simulations,the bias-corrected WRF output is more reliable than the gauge dataset.Thus,data merging of the WRF output and gauge observations would provide more reliable precipitation estimations in arid high mountainous areas.

Improving the Forecasts of Coastal Wind Speeds in Tianjin,China Based on the WRF Model with Machine Learning Algorithms

Characterized by sudden changes in strength,complex influencing factors,and significant impacts,the wind speed in the circum-Bohai Sea area is relatively challenging to forecast.On the western side of Bohai Bay,as the economic center of the circum-Bohai Sea,Tianjin exhibits a high demand for accurate wind forecasting.In this study,three machine learning algorithms were employed and compared as post-processing methods to correct wind speed forecasts by the Weather Research and Forecast(WRF)model for Tianjin.The results showed that the random forest(RF)achieved better performance in improving the forecasts because it substantially reduced the model bias at a lower computing cost,while the support vector machine(SVM)performed slightly worse(especially for stronger winds),but it required an approximately 15 times longer computing time.The back propagation(BP)neural network produced an average forecast significantly closer to the observed forecast but insufficiently reduced the RMSE.In regard to wind speed frequency forecasting,the RF method commendably corrected the forecasts of the frequency of moderate(force 3)wind speeds,while the BP method showed a desirable capability for correcting the forecasts of stronger(force>6)winds.In addition,the 10-m u and v components of wind(u_(10)and v_(10)),2-m relative humidity(RH_(2))and temperature(T_(2)),925-hPa u(u925),sea level pressure(SLP),and 500-hPa temperature(T_(500))were identified as the main factors leading to bias in wind speed forecasting by the WRF model in Tianjin,indicating the importance of local dynamical/thermodynamic processes in regulating the wind speed.This study demonstrates that the combination of numerical models and machine learning techniques has important implications for refined local wind forecasting.

The Effect of Moisture in Different Altitude Layers on the Eastward Propagation of MJO

In this study,driven by ERA5 reanalysis data,the Weather Research and Forecasting(WRF)version 4.0 was used to investigate the eastward propagation of the Madden-Julian oscillation(MJO)in the tropical atmosphere during December-February(DJF)of 2007/2008.The experiment with 11 cumulus parameterization schemes respectively shows that the Grell 3D scheme is one of several worse ones in describing MJO activities.In addition,still by use of the Grell 3D scheme,four nudging assimilation experiments for water vapor in all model vertical layers(Ndg_all),lower layers(Ndg_low),middle layers(Ndg_mid),and upper layers(Ndg_upp)were conducted.It is found that when the water vapor in the model approaches to the observed value,the model performance for MJO activities is improved greatly.Among the four nudging simulations,Ndg_all certainly performs best.Although Ndg_mid is important for the MJO-filtered profiles related to moisture,Ndg_low and Ndg_upp exhibit superiority to Ndg_mid in simulating MJO eastward propagation.Ndg_low has advantages when MJO features are represented by zonal wind at 850 hPa and precipitation because the lower-level MJO-filtered moisture is conducive to the existence of lower-level condensational heating to the east of the MJO convective center.Ndg_upp performs better when describing the MJO eastward propagation features by outgoing longwave radiation(OLR)since it can capture the moisture and cloud top temperature of deep convection associated with MJO,as well as front Walker cell.These results suggest that the lower-level moisture is more important in regulating the MJO eastward propagation,and the observed maximum MJO-filtered moisture in the middle troposphere might be a phenomenon accompanying the MJO deep convection,but not a factor controlling its eastward propagation.

Impacts of Roof/Ground Mitigation Strategies on Improving the Urban Thermal Environment and Human Comfort over the Yangtze River Delta, China

The combined effects of global warming and the urban heat islands exacerbate the risk of urban heat stress. It is crucial to implement effective cooling measures in urban areas to improve the comfort of the thermal environment. In this study, the Weather Research and Forecasting Model(WRF), coupled with a single-layer Urban Canopy Model(UCM), was used to study the impact of heat mitigation strategies. In addition, a 5-km resolution land-cover dataset for China(ChinaLC), which is based on satellite remote sensing data, was adjusted and used, and 18 groups of numerical experiments were designed, to increase the albedo and vegetation fraction of roof/ground parameters. The experiments were conducted for four heatwave events that occurred in the summer of 2013 in the Yangtze River Delta urban agglomeration of China. The simulated results demonstrated that, for the single roof/ground schemes, the mitigation effects were directly proportional to the albedo and greening. Among all the experimental schemes, the superposed schemes presented better cooling effects. For the ground greening scheme, with similar net radiation flux and latent heat flux, its storage heat was lower than that of the roof greening scheme, resulting in more energy flux into the atmosphere, and its daytime cooling effect was not as good as that of the roof greening scheme. In terms of human thermal comfort(HTC), the improvement achieved by the ground greening scheme was better than any other single roof/ground schemes, because the increase in the relative humidity was small. The comprehensive evaluation of the mitigation effects of different schemes on the thermal environment presented in this paper provides a theoretical basis for improving the urban environment through rational urban planning and construction.

复杂气象条件下考虑结冰风险的无人机飞行策略

为解决无人机在复杂气象条件下易受结冰影响而威胁其飞行安全的问题,提出了一种考虑结冰风险的无人机航迹规划方法。首先,构建基于中尺度WRF(Weather Research and Forecasting)模式的结冰气象预测模型,通过最佳参数化方案组合的结冰气象模拟获得模拟时段内海南乐东地区的温度、压力、液态水含量(LWC)空间分布及时序变化。其次,构建基于代理模型的水滴收集质量快速预测方法。在获取美国联邦航空条例(FAR)25部附录C中连续最大结冰条件下40个采样点处水滴收集质量分布的基础上,利用本征正交分解(POD)降阶模型和Kriging插值算法,建立温度、压力、LWC、平均有效水滴直径(MVD)等结冰气象参数与水滴收集质量之间的代理模型,可快速预测出目标区域内水滴收集质量的空间分布与时序变化。最后,根据飞机结冰强度划分等级,以不同结冰强度下水滴收集质量阈值为结冰安全约束,利用基于粒子群优化(PSO)的结冰容限航迹规划方法进行考虑结冰风险的无人机飞行策略研究。研究结果表明:利用WRF模式可获得温度、压力、LWC等结冰气象参数,预测值与观测值匹配良好;基于POD降阶模型和Kriging插值算法,构建的气象参数与水滴收集质量间代理模型可快速准确地获取目标区域内水滴收集质量的空间分布与时序变化;基于PSO的结冰容限航迹规划方法可在不同结冰安全约束条件下,规划出无人机最优航迹。

一种基于水滴收集量代理模型的结冰试飞空域确定方法

针对自然结冰试飞空域确定时使用的结冰指数只能给出结冰概率和结冰等级的问题,提出一种新的方法。通过对美国联邦航空条例(FAR)25部附录C连续最大结冰条件采样,对采样点进行空气流场和水滴撞击特性求解,获得不同工况的水滴收集量;基于POD(Proper Orthogonal Decomposition)和Kriging构建水滴收集量代理模型;使用WRF(Weather Research and Forecasting)对目标区域进行气象模拟,获得温度以及液态水含量分布;使用代理模型对目标区域内水滴收集量进行预测,以中度结冰强度对目标区域进行划分;最后,针对2种飞行速度对试飞空域的影响进行研究。结果表明:代理模型能够很好地预测温度、液态水含量、水滴中值体积直径、高度以及速度对水滴收集量的影响;WRF获得的目标区域的温度、液态水含量与观测值符合良好;基于代理模型可快速获得目标区域水滴收集量分布及随时间的变化,还可获得适合自然结冰试飞的目标区域及结冰速度;飞行速度的增加使得水滴收集量增加,进而引起试飞空域的变化。本文对结冰试飞空域确定具有一定参考意义。

The world meteorological organization Tenth International Workshop on tropical cyclones(IWTC-10):A summary

The Tenth International Workshop on Tropical Cyclones(IWTC-10)occurred from 5 to 9 December 2022 in Bali,Indonesia.This workshop continued the goal of the original IWTC,held in 1985 in Bangkok,Thailand,to bring together forecasters and researchers from countries around the world that are impacted by tropical cyclones(TCs)to discuss the latest research and forecast advances and share best practices to improve TC forecasts globally.The workshops have continued as a regular feature of WMO efforts to encourage the advancement of TC forecasting and improve ways of communicating TC hazards to the general public.Global TC forecasting efforts in the past 10–15 years have emphasized hazards and impacts of landfalling TCs beyond just track and intensity.Additionally,there has been a growing interest in improving the communication of these hazards and impacts,using concepts from social and behavioral sciences,in ways that can lead to effective decision-making from stakeholders(e.g.,government officials,emergency managers,media,general public).As such,the theme for IWTC-10 was“Improved TC science and services for better decision-making.”More about this theme,how the workshop was structured around it,and key outcomes from the workshop are discussed in this summary article.©2023 The Shanghai Typhoon Institute of China Meteorological Administration.Publishing services by Elsevier B.V.on behalf of KeAi Communication Co.Ltd.This is an open access article under the CC BY license(http://creativecommons.org/licenses/by/4.0/).

Effects of Land Use Changes Across Different Urbanization Periods on Summer Rainfall in the Pearl River Delta Core Area

The Pearl River Delta(PRD)is one of the three urban agglomerations in China that have experienced rapid development.For this study,a core area of the PRD was identified,comprising the highly urbanized areas of Guangzhou,Foshan,Zhongshan,Zhuhai,Shenzhen,and Dongguan Cities.The expansion of these urban areas was tracked across three time periods—the year population urbanization rate exceeded 70%(2000),18 years before(1982),and 18 years after(2018).This study used the Weather Research and Forecasting(WRF)model to explore summer rainfall changes across different urbanization periods in the PRD core area.The results show that urban land expansion mainly occurred in the post urbanization period.Rainfall changes acros s different urbanization periods were roughly consistent with previously observed spatial and temporal changes accompanying urban expansion in the PRD core area.Extreme rainfall mainly increased in the post urbanization period,shifting rainstorm center towards the PRD core area.Further causal analysis revealed that land use changes affected rainfall by altering thermodynamics and water vapor transfer.The urban expansion changed the surface energy balance,resulting in increased surface heating and heat island effects.The heat island effects thickened the planetary boundary layer and increased vertical wind speeds,which initiated dry island effects,thereby causing more water vapor transportation to the atmosphere.Consequently,rainstorms and extreme rainfall events have become concentrated in urban areas.