IMPROVEMENT OF REGIONAL PREDICTION OF SEA FOG ON GUANGDONG COASTLAND USING THE FACTOR OF TEMPERATURE DIFFERENCE IN THE NEAR-SURFACE LAYER

The relationship between the factor of temperature difference of the near-surface layer(T_(1000 hPa)-T_(2m))and sea fog is analyzed using the NCEP reanalysis with a horizontal resolution of l°xl°(2000 to 2011) and the station observations(2010 to 2011).The element is treated as the prediction variable factor in the GRAPES model and used to improve the regional prediction of sea fog on Guangdong coastland.(1) The relationship between this factor and the occurrence of sea fog is explicit:When the sea fog happens,the value of this factor is always large in some specific periods,and the negative value of this factor decreases significantly or turns positive,suggesting the enhancement of warm and moist advection of air flow near the surface,which favors the development of sea fog.(2) The transportation of warm and moist advection over Guangdong coastland is featured by some stages and the jumping among these states.It also gets stronger over time.Meanwhile,the northward propagation of warm and moist advection is quite consistent with the northward advancing of sea fog from south to north along the coastland of China.(3) The GRAPES model can well simulate and realize the factor of near-surface temperature difference.Besides,the accuracy of regional prediction of marine fog,the relevant threat score and Heidke skill score are all improved when the factor is involved.

An Evaluation of Tropical Cyclone Genesis Forecast over the Western North Pacific and the South China Sea from the CMA-TRAMS

Tropical cyclone(TC) genesis forecasting is essential for daily operational practices during the typhoon season.The updated version of the Tropical Regional Atmosphere Model for the South China Sea(CMA-TRAMS) offers forecasters reliable numerical weather prediction(NWP) products with improved configurations and fine resolution. While traditional evaluation of typhoon forecasts has focused on track and intensity, the increasing accuracy of TC genesis forecasts calls for more comprehensive evaluation methods to assess the reliability of these predictions. This study aims to evaluate the effectiveness of the CMA-TRAMS for cyclogenesis forecasts over the western North Pacific and South China Sea. Based on previous research and typhoon observation data over five years, a set of localized, objective criteria has been proposed. The analysis results indicate that the CMA-TRAMS demonstrated superiority in cyclogenesis forecasts, predicting 6 out of 22 TCs with a forecast lead time of up to 144 h. Additionally, over 80% of the total could be predicted 72 h in advance. The model also showed an average TC genesis position error of 218.3 km, comparable to the track errors of operational models according to the annual evaluation. The study also briefly investigated the forecast of Noul(2011). The forecast field of the CMA-TRAMS depicted thermal and dynamical conditions that could trigger typhoon genesis, consistent with the analysis field. The 96-hour forecast field of the CMA-TRAMS displayed a relatively organized threedimensional structure of the typhoon. These results can enhance understanding of the mechanism behind typhoon genesis,fine-tune model configurations and dynamical frameworks, and provide reliable forecasts for forecasters.

Preliminary Model Study for Forecasting a Hot Weather Process in Guangdong Province Using CMA-TRAMS

In this paper, the CMA-TRAMS tropical high-resolution system was used to forecast a typical hot weather process in Guangdong, China with different horizontal resolutions and surface coverage. The results of resolutions of 0.02° and 0.06° were presented with the same surface coverage of the GlobeLand30 V2020, companies with the results of resolution 0.02° with the USGS global surface coverage. The results showed that, on the overall assessment the 2 km model performed better in forecasting 2 m temperature, while the 6 km model was more accurate in predicting 10 m wind speed. In the evaluation of representative stations, the 2 km model performed better in forecasting 2 m temperature and 2 m relative humidity at the coastal stations, and the 2 km model was also better in forecasting 2 m pressure at the representative stations. However, the 6 km model performed better in forecasting 10 m wind speed at the representative stations. Furthermore, the 2 km model, owing to its higher horizontal resolution, presented a more detailed stratification of various meteorological field maps, allowing for a more pronounced simulation of local meteorological element variations. And the use of the surface coverage data of the GlobeLand30 V2020 improved the forecasting of 2 m temperature, and 10 m wind speed compared to the USGS surface coverage data.

A CASE STUDY OF NUMERICAL SIMULATION OF SEA FOG ON THE SOUTHERN CHINA COAST

This study uses numerical simulations to examine a case of sea fog that was observed from 20 to 22 March2011 on the southern China coast. The observation dataset includes observatory data, cloud-top temperature from MODIS, GPS sonde, and data from the Integrated Observation Platform for Marine Meteorology(IOPMM). The simulations are based on the Weather Research and Forecasting(WRF) model with four distinct parameter settings.Both the observations and simulations focus on the characteristics of the fog extent, boundary layer structure, and meteorological elements near the air-sea interface. Our main results are as follows:(1) The extent of mesoscale sea fog can be well simulated when the sea surface temperature has at least 0.5 ×0.5 horizontal resolution.(2) To accurately model the vertical structure of the sea fog, particularly the surface-based inversion, vertical levels must be added in the boundary layer.(3) When these model conditions are met, the simulations faithfully reproduce the measured downward shortwave radiation, downward longwave radiation, and surface sensible heat flux during the sea fog period.

A STUDY ON THE APPLICATION OF FY-2E CLOUD DRIFT WIND HEIGHT REASSIGNMENT IN NUMERICAL FORECAST OF TYPHOON CHANTHU(1003) TRACK

In this paper, we first analyzed cloud drift wind(CDW) data distribution in the vertical direction, and then reassigned the height of every CDW in the research domain in terms of background information, and finally, conducted contrast numerical experiments of assimilating the CDW data before and after reassignment to examine the impacts on the forecast of the track of Typhoon Chanthu(1003) from 00:00(Coordinated Universal Time) 21 July to 00:00 UTC23 July, 2010. The analysis results of the CDW data indicate that the number of CDWs is mainly distributed in the midand upper-troposphere above 500 h Pa, with the maximum number at about 300 h Pa. The height reassigning method mentioned in this work may update the height effectively, and the CDW data are distributed reasonably and no obvious contradiction occurs in the horizontal direction after height reassignment. After assimilating the height-reassigned CDW data, especially the water vapor CDW data, the initial wind field around Typhoon Chanthu(1003) became more reasonable, and then the steering current leading the typhoon to move to the correct location became stronger. As a result, the numerical track predictions are improved.

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.

INFLUENCE OF DIFFERENT-SCALE ERRORS INTERACTIONS ON ANALYSIS AND FORECAST OF REGIONAL NWP MODEL

In the previous study, the influences of introducing larger- and smaller-scale errors on the background error covariances estimated at the given scales were investigated, respectively. This study used the covariances obtained in the previous study in the data assimilation and model forecast system based on three-dimensional variational method and the Weather Research and Forecasting model. In this study, analyses and forecasts from this system with different covariances for a period of one month were compared, and the causes for differing results were presented. The variations of analysis increments with different-scale errors are consistent with those of variances and correlations of background errors that were reported in the previous paper. In particular, the introduction of smaller-scale errors leads to greater amplitudes in analysis increments for medium-scale wind at the heights of both high- and low-level jets. Temperature and humidity analysis increments are greater at the corresponding scales at the middle- and upper-levels. These analysis increments could improve the intensity of the jet-convection system that includes jets at different levels and the coupling between them that is associated with latent heat release. These changes in analyses will contribute to more accurate wind and temperature forecasts in the corresponding areas. When smaller-scale errors are included, humidity analysis increments are significantly enhanced at large scales and lower levels, to moisten southern analyses. Thus, dry bias can be corrected, which will improve humidity forecasts. Moreover, the inclusion of larger-(smaller-) scale errors will be beneficial for the accuracy of forecasts of heavy(light) precipitation at large(small) scales because of the amplification(diminution) of the intensity and area in precipitation forecasts.

Synergistic Effect of the Planetary-scale Disturbance, Typhoon and Meso-β-scale Convective Vortex on the Extremely Intense Rainstorm on 20 July 2021 in Zhengzhou

On 20 July 2021,northern Henan Province in China experienced catastrophic flooding as a result of an extremely intense rainstorm,with a record-breaking hourly rainfall of 201.9 mm during 0800–0900 UTC and daily accumulated rainfall in Zhengzhou City exceeding 600 mm(“Zhengzhou 7.20 rainstorm”for short).The multi-scale dynamical and thermodynamical mechanisms for this rainstorm are investigated based on station-observed and ERA-5 reanalysis datasets.The backward trajectory tracking shows that the warm,moist air from the northwestern Pacific was mainly transported toward Henan Province by confluent southeasterlies on the northern side of a strong typhoon In-Fa(2021),with the convergent southerlies associated with a weaker typhoon Cempaka(2021)concurrently transporting moisture northward from South China Sea,supporting the rainstorm.In the upper troposphere,two equatorward-intruding potential vorticity(PV)streamers within the planetary-scale wave train were located over northern Henan Province,forming significant divergent flow aloft to induce stronger ascending motion locally.Moreover,the converged moist air was also blocked by the mountains in western Henan Province and forced to rise so that a deep meso-β-scale convective vortex(MβCV)was induced over the west of Zhengzhou City.The PV budget analyses demonstrate that the MβCV development was attributed to the positive feedback between the rainfall-related diabatic heating and high-PV under the strong upward PV advection during the Zhengzhou 7.20 rainstorm.Importantly,the MβCV was forced by upper-level larger-scale westerlies becoming eastward-sloping,which allowed the mixtures of abundant raindrops and hydrometeors to ascend slantwise and accumulate just over Zhengzhou City,resulting in the record-breaking hourly rainfall locally.

Properties of High-Order Finite Difference Schemes and Idealized Numerical Testing

Construction of high-order difference schemes based on Taylor series expansion has long been a hot topic in computational mathematics, while its application in comprehensive weather models is still very rare. Here, the properties of high-order finite difference schemes are studied based on idealized numerical testing, for the purpose of their application in the Global/Regional Assimilation and Prediction System(GRAPES) model. It is found that the pros and cons due to grid staggering choices diminish with higher-order schemes based on linearized analysis of the one-dimensional gravity wave equation. The improvement of higher-order difference schemes is still obvious for the mesh with smooth varied grid distance. The results of discontinuous square wave testing also exhibits the superiority of high-order schemes. For a model grid with severe non-uniformity and non-orthogonality, the advantage of high-order difference schemes is inapparent, as shown by the results of two-dimensional idealized advection tests under a terrain-following coordinate. In addition, the increase in computational expense caused by high-order schemes can be avoided by the precondition technique used in the GRAPES model. In general, a high-order finite difference scheme is a preferable choice for the tropical regional GRAPES model with a quasi-uniform and quasi-orthogonal grid mesh.

STATISTICAL CHARACTERISTICS AND NUMERICAL SIMULATION OF SEA-LAND BREEZES IN HAINAN ISLAND

The sea-land breeze circulation(SLBC) occurs regularly at coastal locations and influences the local weather and climate significantly. In this study, based on the observed surface wind in 9 conventional meteorological stations of Hainan Island, the frequency of sea-land breeze(SLB) is studied to depict the diurnal and seasonal variations. The statistics indicated that there is a monthly average of 12.2 SLB days and an occurrence frequency of about 40%, with the maximum frequency(49%) in summer and the minimum frequency(29%) in autumn. SLB frequencies(41%) are comparable in winter and spring. A higher frequency of SLB is present in the southern and central mountains due to the enhancement effect of the mountain-valley breeze. Due to the synoptic wind the number of SLB days in the northern hilly area is less than in other areas. Moreover, the WRF model, adopted to simulate the SLBC over the island for all seasons, performs reasonably well reproducing the phenomenon, evolution and mechanism of SLBC. Chiefly affected by the difference of temperature between sea and land, the SLBC varies in coverage and intensity with the seasons and reaches the greatest intensity in summer. The typical depth is about 2.5 km for sea breeze circulation and about 1.5 km for land breeze circulation. A strong convergence zone with severe ascending motion appears on the line parallel to the major axis of the island, penetrating 60 to 100 km inland. This type of weak sea breeze convergence zone in winter is north-south oriented. The features of SLBC in spring are similar both to that in summer with southerly wind and to that in winter with easterly wind. The coverage and intensity of SLBC in autumn is the weakest and confined to the southwest edge of the central mountainous area. The land breeze is inherently very weak and easily affected by the topography and weather. The coverage and intensity of the land breeze convergence line is significantly less than those of the sea breeze. The orographic forcing of the central mountain exhibits significant impacts on low-level airflow. A windward land breeze front usually occurs along the coastline between the wee hours and the morning in summer, with an arc-shaped convergence zone about 10 to 30 km off shore. In winter the arc-shaped convergence zone is weak and appears only in the southeast coastal area. Landing on the flat regions of northern to western parts of the island and going inland from there, the sea breeze front at the leeward side meets with that at the windward side in the centre of the island when sea breeze fully develops, causing an intense convergence zone throughout the whole island. Consistent with prevailing winds in direction, the windward sea breeze and leeward land breeze develop quickly but are not distinguishable from background winds.

Key Deviation Analysis of Initial Fields on Ensemble Forecast in South China During the Rainfall Event on May 21,2020

Extreme rainfall is common from May to October in south China.This study investigates the key deviation of initial fields on ensemble forecast of a persistent heavy rainfall event from May 20 to 22,2020 in Guangdong Province,south China by comparing ensemble members with different performances.Based on the rainfall distribution and pattern,two types are selected for analysis compared with the observed precipitation.Through the comparison of the thermal and dynamic fields in the middle and lower layers,it can be found that the thermal difference between the middle and lower layers was an important factor which led to the deviation of precipitation distribution.The dynamic factors also have some effects on the precipitation area although they were not as important as the thermal factors in this case.Correlating accumulated precipitation with atmospheric state variables further corroborates the above conclusion.This study suggests that the uncertainty of the thermal and dynamic factors in the numerical model can have a strong impact on the quantitative skills of heavy rainfall forecasts.

A Time Neighborhood Method for the Verification of Landfalling Typhoon Track Forecast

Landfalling typhoons can cause disasters over large regions.The government and emergency responders need to take measures to mitigate disasters according to the forecast of landfall position,while slight timing error can be ignored.The reliability of operational model forecasts of typhoon landfall position needs to be evaluated beforehand,according to the forecasts and observation of historical cases.In the evaluation of landfalling typhoon track,the traditional method based on point-to-point matching methods could be influenced by the predicted typhoon translation speed.Consequently,the traditional track evaluation method may result in a large track error even if the predicted landfall position is close to observation.The purpose of this paper is to address the above issue using a simple evaluation method of landfalling typhoon track forecast based on the time neighborhood approach.In this new method,the timing error was lessened to highlight the importance of the position error during the landfall of typhoon.The properties of the time neighborhood method are compared with the traditional method based on numerical forecast results of 12 landfalling typhoon cases.Results demonstrated that the new method is not sensitive to the sampling frequency,and that the difference between the time neighborhood and traditional method will be more obvious when the moving speed of typhoon is moderate(between 15−30 km h^(−1)).The time neighborhood concept can be easily extended to a broader context when one attempts to examine the position error more than the timing error.

Precipitation Microphysical Characteristics of Typhoon Ewiniar(2018) before and after Its Final Landfall over Southern China

In this paper, the evolution of the microphysical characteristics in different regions(eyewall, inner core, and outer rainbands) and different quadrants [downshear left(DL), downshear right(DR), upshear left(UL), and upshear right(UR)]during the final landfall of Typhoon Ewiniar(2018) is analyzed using two-dimensional video disdrometer and S-band polarimetric radar data collected in Guangdong, China. Due to the different types of underlying surfaces, the periods before landfall(mainly dominated by underlying sea surface) and after landfall(mainly dominated by underlying land surface) are also analyzed. Both before landfall and after landfall, the downshear quadrants had the dominate typhoon precipitation. The outer rainbands had more graupel than the inner core, resulting in a larger radar reflectivity, differential reflectivity, specific differential phase shift, and mass-weighted mean diameter below the melting layer. Compared with other regions, the eyewall region had the smallest mean logarithmic normalized intercept parameter before landfall and the smallest mean mass-weighted mean diameter and the largest mean logarithmic normalized intercept parameter after landfall. The hydrometeor size sorting was obvious in the eyewall and inner core(especially in the eyewall) after landfall. A high concentration of large raindrops fell in the DL quadrant, and more small raindrops fell in the UR quadrant. Although the icephase process and warm rain process were both important in the formation of tropical cyclone precipitation, the warm rain process(ice-phase process) contributed more liquid water before landfall(after landfall). This investigation provides a reference for improving the microphysical parameterization scheme in numerical models.

Impacts of Sea Surface Temperature on the Interannual Variability of Winter Haze Days in Guangdong Province

The impact of sea surface temperature(SST)on winter haze in Guangdong province(WHDGD)was analyzed on the interannual scale.It was pointed out that the northern Indian Ocean and the northwest Pacific SST play a leading role in the variation of WHDGD.Cold(warm)SST anomalies over the northern Indian Ocean and the Northwest Pacific stimulate the eastward propagation of cold(warm)Kelvin waves through the Gill forced response,causing Ekman convergence(divergence)in the western Pacific,inducing abnormal cyclonic(anticyclonic)circulation.It excites the positive(negative)Western Pacific teleconnection pattern(WP),which results in the temperature and the precipitation decrease(increase)in Guangdong and forms the meteorological variables conditions that are conducive(not conducive)to the formation of haze.ENSO has an asymmetric influence on WHDGD.In El Niño(La Niña)winters,there are strong(weak)coordinated variations between the northern Indian Ocean,the northwest Pacific,and the eastern Pacific,which stimulate the negative(positive)phase of WP teleconnection.In El Niño winters,the enhanced moisture is attributed to the joint effects of the horizontal advection from the surrounding ocean,vertical advection from the moisture convergence,and the increased atmospheric apparent moisture sink(Q2)from soil evaporation.The weakening of the atmospheric apparent heat source(Q1)in the upper layer is not conducive to the formation of inversion stratification.In contrast,in La Niña winters,the reduced moisture is attributed to the reduced upward water vapor transport and Q2 loss.Due to the Q1 increase in the upper layer,the temperature inversion forms and suppresses the diffusion of haze.

Forecast Performance of the Pre-operational CMA-TRAMS(EPS)in South China During April-September 2020

The mesoscale ensemble prediction system based on the Tropical Regional Atmosphere Model for the South China Sea(CMA-TRAMS(EPS))has been pre-operational since April 2020 at South China Regional Meteorological Center(SCRMC),which was developed by the Guangzhou Institute of Tropical and Marine Meteorology(GITMM).To better understand the performance of the CMA-TRAMS(EPS)and provide guidance to forecasters,we assess the performance of this system on both deterministic and probabilistic forecasts from April to September 2020 in this study through objective verification.Compared with the control(deterministic)forecasts,the ensemble mean of the CMATRAMS(EPS)shows advantages in most non-precipitation variables.In addition,the threat score indicates that the CMA-TRAMS(EPS)obviously improves light and heavy rainfall forecasts in terms of the probability-matched mean.Compared with the European Center for Medium-range Weather Forecasts operational ensemble prediction system(ECMWF-EPS),the CMA-TRAMS(EPS)improves the probabilistic forecasts of light rainfall in terms of accuracy,reliability and discrimination,and this system also improves the heavy rainfall forecasts in terms of discrimination.Moreover,two typical heavy rainfall cases in south China during the pre-summer rainy season are investigated to visually demonstrate the deterministic and probabilistic forecasts,and the results of these two cases indicate the differences and advantages(deficiencies)of the two ensemble systems.

Comparison of Microphysical Characteristics Between Warm-sector and Frontal Heavy Rainfall in the South of China

During the April-June raining season,warm-sector heavy rainfall(WR) and frontal heavy rainfall(FR) often occur in the south of China,causing natural disasters.In this study,the microphysical characteristics of WR and FR events from 2016 to 2022 are analyzed by using 2-dimensional video disdrometer(2DVD) data in the south of China.The microphysical characteristics of WR and FR events are quite different.Compared with FR events,WR events have higher concentration of D<5.3 mm(especially D <1 mm),leading to higher rain rates.The mean values of Dmand lgNwof WR events are higher than that of FR events.The microphysical characteristics in different rain rate classes(C1:R~5-20 mm h-1,C2:R~20-50 mm h-1,C3:R~50-100 mm h^(-1),and C4:R> 100 mm h^(-1)) for WR and FR events are also different.Raindrops from C3 contribute the most to the precipitation of WR events,and raindrops from C2 contribute the most to the precipitation of FR events.For C2 and C3,compared with FR events,WR events have higher concentration of D <1 mm and D~3-4.5 mm.Moreover,the shape and slope(μ-A) relationships and the radar reflectivity and rain rate(Z-R) relationships of WR and FR events are quite different in each rain rate class.The investigation of the difference in microphysical characteristics between WR and FR events provide useful information for radar-based quantitative precipitation estimation and numerical prediction.

Performance of the CMA-GD Model in Predicting Wind Speed at Wind Farms in Hubei, China

This study assesses the predictive capabilities of the CMA-GD model for wind speed prediction in two wind farms located in Hubei Province,China.The observed wind speeds at the height of 70m in wind turbines of two wind farms in Suizhou serve as the actual observation data for comparison and testing.At the same time,the wind speed predicted by the EC model is also included for comparative analysis.The results indicate that the CMA-GD model performs better than the EC model in Wind Farm A.The CMA-GD model exhibits a monthly average correlation coefficient of 0.56,root mean square error of 2.72 m s^(-1),and average absolute error of 2.11 m s^(-1).In contrast,the EC model shows a monthly average correlation coefficient of 0.51,root mean square error of 2.83 m s^(-1),and average absolute error of 2.21 m s^(-1).Conversely,in Wind Farm B,the EC model outperforms the CMA-GD model.The CMA-GD model achieves a monthly average correlation coefficient of 0.55,root mean square error of 2.61 m s^(-1),and average absolute error of 2.13 m s^(-1).By contrast,the EC model displays a monthly average correlation coefficient of 0.63,root mean square error of 2.04 m s^(-1),and average absolute error of 1.67 m s^(-1).

Adaptive Wind Gust and Associated Gust-factor Model for the Gust-producing Weather over the Northern South China Sea

Wind gusts are common environmental hazards that can damage buildings,bridges,aircraft,and cruise ships and interrupt electric power distribution,air traffic,waterway transport and port operations.Accurately predicting peak wind gusts in numerical models is essential for saving lives and preventing economic losses.This study investigates the climatology of peak wind gusts and their associated gust factors(GFs)using observations in the coastal and open ocean of the northern South China Sea(NSCS),where severe gust-producing weather occurs throughout the year.The stratified climatology demonstrates that the peak wind gust and GF vary with seasons and particularly with weather types.Based on the inversely proportional relationship between the GF and mean wind speed(MWS),a variety of GF models are constructed through least squares regression analysis.Peak gust speed(PGS)forecasts are obtained through the GF models by multiplying the GFs by observed wind speeds rather than forecasted wind speeds.The errors are thus entirely due to the representation of the GF models.The GF models are improved with weather-adaptive GFs,as evaluated by the stratified MWS.Nevertheless,these weather-adaptive GF models show negative bias for predicting stronger PGSs due to insufficient data representation of the extreme wind gusts.The evaluation of the above models provides insight into maximizing the performance of GF models.This study further proposes a stratified process for forecasting peak wind gusts for routine operations.

FSS-based Evaluation on Monsoon Precipitation Forecasts in South China from Regional Models with Different Resolution

This study evaluated the forecast skill of CMA-GD 3 km and CMA-GD 1 km with hourly Rapid Update Cycle(RUC)for five monsoon precipitation events in South China from 2018 to 2020,using the fraction skill score(FSS)of the neighborhood spatial verification method.The results revealed that,among the 24-lead-hour forecasts in CMA-GD 3 km,the FSS for the 0.1 mm precipitation threshold increased linearly with the lead time from 3 to 1 hour,while there was no significant improvement in other lead times.For the 5 mm precipitation threshold,the forecast skill was highest for the latest 1-hour lead time,while the FSS showed slight variation between lead times of 24 hours and 8 hours.The FSS for 10 mm and 20 mm precipitation thresholds were similar to that of 5 mm,with the difference that the best score occurred at the 2-hour lead time.Among the 6-lead-hour forecasts in CMA-GD 1 km,the forecasts of the latest 1-hour lead time were the best choices for four precipitation thresholds.When comparing CMA-GD 3 km and CMA-GD 1 km,it was found that CMA-GD 3 km had better skill for forecasts of 0.1 mm and 5 mm precipitation at 2-hour and 1-hour lead times,while CMA-GD 1 km had better skill for all other forecasts,including the forecast of 20 mm precipitation nearly all lead hours(including 3-to 6-hour,and 1-hour lead times).The results suggest that the increased resolution of the model may be beneficial for precipitation forecasts in South China,especially for short-duration heavy precipitation over a longer lead hours.However,the limited sample size of this study calls for further evaluation using more cases to validate the results′generality.

Impacts of Increasing Model Resolutions and Shortening Forecast Lead Times on QPFs in South China During the Rainy Season

This study investigated the impacts of increasing model resolutions and shortening forecast lead times on the quantitative precipitation forecast(QPF)for heavy-rainfall events over south China during the rainy seasons in 2013-2020.The control experiment,where the analysis-forecast cycles run with model resolutions of about 3 km,was compared to a lower-resolution experiment with model resolutions of about 9 km,and a longer-term experiment activated 12 hours earlier.Rainfall forecasting in the presummer rainy season was significantly improved by improving model resolutions,with more improvements in cases with stronger synoptic-scale forcings.This is partially attributed to the improved initial conditions(ICs)and subsequent forecasts for low-level jets(LLJs).Forecasts of heavy rainfall induced by landfalling tropical cyclones(TCs)benefited from increasing model resolutions in the first 6 hours.Forecast improvements in rainfall due to shortening forecast lead times were more significant at earlier(1-6 h)and later(7-12 h)lead times for cases with stronger and weaker synoptic-scale forcings,respectively,due to the area-and case-dependent improvements in ICs for nonprecipitation variables.Specifically,significant improvements mainly presented over the northern South China Sea for low-level onshore wind of weak-forcing cases but over south China for LLJs of strong-forcing cases during the presummer rainy season,and over south China for all the nonprecipitation variables above the surface during the TC season.However,some disadvantages of higher-resolution and shorter-term forecasts in QPFs highlight the importance of developing ensemble forecasting with proper IC perturbations,which include the complementary advantages of lower-resolution and longer-term forecasts.