The Contribution of United States Aircraft Reconnaissance Data to the China Meteorological Administration Tropical Cyclone Intensity Data:An Evaluation of Homogeneity

This paper investigates the homogeneity of United States aircraft reconnaissance data and the impact of these data on the homogeneity of the tropical cyclone(TC)best track data for the seasons 1949-1987 generated by the China Meteorological Administration(CMA).The evaluation of the reconnaissance data shows that the minimum central sea level pressure(MCP)data are relatively homogeneous,whereas the maximum sustained wind(MSW)data show both overestimations and spurious abrupt changes.Statistical comparisons suggest that both the reconnaissance MCP and MSW were well incorporated into the CMA TC best track dataset.Although no spurious abrupt changes were evident in the reconnaissance-related best track MCP data,two spurious changepoints were identified in the remainder of the best-track MCP data.Furthermore,the influence of the reconnaissance MSWs seems to extend to the best track MSWs unrelated to reconnaissance,which might reflect the optimistic confidence in making higher estimates due to the overestimated extreme wind“observations”.In addition,the overestimation of either the reconnaissance MSWs or the best track MSWs was greater during the early decades compared to later decades,which reflects the important influence of reconnaissance data on the CMA TC best track dataset.The wind-pressure relationship(WPR)used in the CMA TC best track dataset is also evaluated and is found to overestimate the MSW,which may lead to inhomogeneity within the dataset between the aircraft reconnaissance era and the satellite era.

Western North Pacific Tropical Cyclone Database Created by the China Meteorological Administration

This paper describes the access to, and the content, characteristics, and potential applications of the tropical cyclone(TC) database that is maintained and actively developed by the China Meteorological Administration, with the aim of facilitating its use in scientific research and operational services. This database records data relating to all TCs that have passed through the western North Pacific(WNP) and South China Sea(SCS) since 1949. TC data collection has expanded over recent decades via continuous TC monitoring using remote sensing and specialized field detection techniques,allowing collation of a multi-source TC database for the WNP and SCS that covers a long period, with wide coverage and many observational elements. This database now comprises a wide variety of information related to TCs, such as historical or real-time locations(i.e., best track and landfall), intensity, dynamic and thermal structures, wind strengths, precipitation amounts, and frequency. This database will support ongoing research into the processes and patterns associated with TC climatic activity and TC forecasting.

北京市慢性病患者家庭照顾者健康素养情况调查及相关因素分析

目的了解北京市慢性病患者家庭照顾者的健康素养情况及相关因素。方法该研究为横断面调查。2018年9月10日至11月15日,通过分层随机抽样选取北京市6个区1350名慢性病患者家庭照顾者,采用自填问卷方式开展调查。问卷内容包括家庭照顾者的一般情况和健康素养情况,健康素养内容包括:(1)日常生活习惯;(2)健康素养基本知识:行为危险因素防治知识(10题)、慢性病相关知识(11题)、急救相关知识(5题);(3)慢性病照顾相关技术掌握情况。结果回收有效问卷1268份,问卷有效回收率93.9%(1268/1350)。1268名家庭照顾者中,女性占75.7%(960/1268),年龄23~86岁,中位年龄为62岁。日常生活习惯方面,吸烟和饮酒者分别占11.3%(143/1268)、21.5%(272/1268);平时进行体育锻炼者占82.7%(1049/1268),其中72.5%(761/1049)家庭照顾者每周运动次数不少于4次;能够做到饮食清淡者仅占28.9%(366/1268)。健康素养基本知识掌握方面,12.9%(163/1268)的家庭照顾者掌握了相关基本知识(得分≥总分×80%);其中掌握慢性病相关基本知识者最多,占30.9%(392/1268)。能熟练或较熟练掌握测量血压、血糖、脉搏、应对低血糖、心肺复苏和正确拨打120急救电话这6项技能的家庭照顾者分别占27.4%(347/1268)、18.1%(230/1268)、15.1%(191/1268)、15.7%(199/1268)、6.0%(76/1268)和33.8%(429/1268)。其中,家庭照顾者对“正确拨打120急救电话”熟练掌握者占比最高,为23.7%(301/1268);对心肺复苏技能熟练掌握者占比最低,为2.6%(33/1268)。不同学历的家庭照顾者对行为危险因素知识(χ^(2)=3.88,P=0.017)、慢性病相关知识(χ^(2)=7.40,P=0.025)、急救相关知识(χ^(2)=12.04,P=0.002)以及总体基本知识(χ^(2)=13.56,P=0.001)的掌握情况差异有统计学意义。不同职业的家庭照顾者慢性病相关知识掌握情况差异有统计学意义(χ^(2)=8.78,P=0.012)。结论北京市慢性病患者家庭照顾者的健康素养水平需进一步提高,不同学历、职业的家庭照顾者的健康素养存在差异。

AN OBJECTIVE TROPICAL CYCLONE INTENSITY ESTIMATION MODEL BASED ON DIGITAL IR SATELLITE IMAGES

An objective tropical cyclone(TC) intensity estimation model is proposed based on the statistical relationship between TC intensity and its inner-core convection,plus the persistence of TC intensity.In the model,the innercore convection is described by several parameters retrieved from digital infrared(IR) satellite images,including the number of convective cores(Num),their distance to the TC center,and their blackbody temperature(TBB),among others.The persistence of TC intensity is embodied by the TC intensity six hours previous(V6h).The model was set up by the stepwise regression technique using a five-year dataset(2006-2010) and was tested using an independent dataset covering 2011-2012,with V6h from the best-track dataset.Selected factors of the model included V6h,Num,Lat(TC center latitude),Lon(TC center longitude),DISmin(minimum distance between convective cores and TC center),and TBBdif(difference between the maximum and minimum TBB value of convective cores).Results showed that,for independent samples during 2011-2012,the MAE(mean absolute error) and RMSE(root-mean-square error) of Vmax estimation were 1.8 m s-1 and 2.4 m s-1,respectively.In order to make the model totally independent from the best-track dataset,the model estimation from six hours previous was used as the V6h for a second independent test covering 2011-2012.The results showed that the model had an MAE and RMSE of 5.4 m s-1 and 7.3 m s-1,respectively.Large errors were found for strong TCs(Severe Typhoon or Super Typhoon).The error statistics of the proposed model are comparable to published statistics on the widely used Dvorak technique or its objective versions,implying its potential to be used as an alternative tool for TC intensity estimation in either real-time operation or post-season best-track analyses.

A METHODOLOGICAL STUDY ON AMH COPULA-BASED JOINT EXCEEDANCE PROBABILITIES AND APPLICATIONS FOR ASSESSING TROPICAL CYCLONE IMPACTS AND DISASTER RISKS(PART Ⅰ)

A disaster induced by a tropical cyclone(TC)is a complex non-linear process,involving interactions of multiple factors.Assuming that the resilience to TC disasters remains basically unchanged,the disaster-causing risk is usually consistent with intensities of the TC-induced rainstorms and wind.When an area is hit by a low probability TC,the rainstorm and wind intensities are higher,and the likelihood for causing a disaster is greater.Therefore,criteria for the impact of a TC and disaster risk assessments can be established based on the probable intensities of the TC-associated rainstorms and wind.In this study,an AMH Copula-based function is introduced to investigate the joint risk probabilities of TC rainstorms and wind.In line with the equivalence principle of the distribution of a stochastic atmospheric phenomenon in both time and space,and taking the impact on Shanghai of TC Haikui as an example,the Copula-based joint probability distribution model is developed to assess the impacts of TC rainstorms and wind,based on the marginal distributions of the maximum daily rainfall and extreme gust velocity.The joint exceedance probabilities of TC rainstorms and wind derived from the model can be used as criteria to measure the risk levels.As our findings show,this approach captures the TC risks well,especially in high-risk areas.The aim of the study is to provide a practically useful concept for making more accurate assessments of the risk level of an extreme weather event using observational data,and objective criteria for risk avoidance and transfer.

A new technique for automatically locating the center of tropical cyclones with multi-band cloud imagery

A spiral cloud belt matching(SCBeM)technique is proposed for automatically locating the tropical cyclone(TC)center position on the basis of multi-band geo-satellite images.The technique comprises four steps:fusion of multi-band geo-satellite images,extraction of TC cloud systems,construction of a spiral cloud belt template(CBT),and template matching to locate the TC center.In testing of the proposed SCBeM technique on 97 TCs over the western North Pacific during 2012-2015,the median error(ME)was 50 km.An independent test of another 29 TCs in 2016 resulted in a ME of 54 km.The SCBeM performs better for TCs with intensity above“typhoon”level than it does for weaker systems,and is not suitable for use on high-latitude or landfall TCs if their cloud band formations have been destroyed by westerlies or by terrain.The proposed SCBeM technique provides an additional solution for automatically and objectively locating the TC center and has the potential to be applied conveniently in an operational setting.Intercomparisons between the Automated Rotational Center Hurricane Eye Retrieval(ARCHER)and SCBeM methods using events from 2014 to 2016 reveal that ARCHER has better location accuracy.However,when IR imagery alone is used,the ME of SCBeM is 54 km,and in the case of low latitudes and low vertical wind shear the ME is 45-47 km,which approaches that of ARCHER(49 km).Thus,the SCBeM method is simple,has good time resolution,performs well and is a better choice for those TC operational agencies in the case that the microwave images,ASCAT,or other observations are unavailable.

Consistency correction of echo intensity data for multiple radar systems and its application in quantitative estimation of typhoon precipitation

Calibration error is one of the primary sources of bias in echo intensity measurements by ground-based radar systems.Calibration errors cause data discontinuity between adjacent radars and reduce the effectiveness of the radar system.The Global Precipitation Measurement Kuband Precipitation Radar(GPM KuPR)has been shown to provide stable long-term observations.In this study,GPM KuPR observations were converted to S-band approximations,which were then matched spatially and temporally with ground-based radar observations.The measurements of stratiform precipitation below the melting layer collected by the KuPR during Typhoon Ampil were compared with those of multiple radar systems in the Yangtze River Delta to determine the deviations in the echo intensity between the KuPR and the ground-based radar systems.The echo intensity data collected by the ground-based radar systems was corrected using the KuPR observations as reference,and the correction results were verified by comparing them with rain gauge observations.It was found that after the correction,the consistency of the echo intensity measurements of the multiple radar systems improved significantly,and the precipitation estimates based on the revised ground-based radar observations were closer to the rain gauge measurements.

APPLICATION OF SATELLITE CLOUD IMAGERY IN TRACK ANALYSIS OF TROPICAL CYCLONES

China is frequently affected by tropical cyclones in summer and autumn because its southern and eastern parts border low-latitude oceans.The track forecasting of tropical cyclones is a key issue in weather forecasting.In daily operations,forecasters usually focus on the effects of environmental flow fields on tropical cyclones,such as the subtropical high pressure belt,the basic flow,the troughs and ridges in westerlies,the cross-equatorial flow,the equatorial convergence belt,and the polar front.However,these factors become less significant when the environmental fields are so weak that the steering flow does not play a vital role or we cannot accurately determine the evolution of the environment flow field.Meteorological satellite cloud imagery can fill the data gap of conventional observations and provide important clues for forecasting the status and development of tropical cyclones when they are included in day-to-day weather forecasting operations.In this study,using 'Muifa', 'Haikui' and other typhoons as examples,the effects of the cloud pattern and the large-scale environmental vapor fields,on the moving tracks of typhoons were analyzed based on satellite data.The results showed that the change of structures of typhoon spiral cloud bands and the turning of the typhoon path were taking on greater relevance,and at the same time the satellite water vapor images had obvious advantages in terms of indicating the large-scale environmental fields.A combination of satellite cloud imagery,observational data,and weather event analysis remains the most effective approach in the operational forecasting of typhoon moving tracks.

Verification of tropical cyclones(TC)wind structure forecasts from global NWP models and ensemble prediction systems(EPSs)

Forecasting wind structure of tropical cyclone(TC)is vital in assessment of impact due to high winds using Numerical Weather Prediction(NWP)model.The usual verification technique on TC wind structure forecasts are based on grid-to-grid comparisons between forecast field and the actual field.However,precision of traditional verification measures is easily affected by small scale errors and thus cannot well discriminate the accuracy or effectiveness of NWP model forecast.In this study,the Method for Object-Based Diagnostic Evaluation(MODE),which has been widely adopted in verifying precipitation fields,is utilized in TC’s wind field verification for the first time.The TC wind field forecast of deterministic NWP model and Ensemble Prediction System(EPS)of the European Centre for Medium-Range Weather Forecasts(ECMWF)over the western North Pacific and the South China Sea in 2020 were evaluated.A MODE score of 0.5 is used as a threshold value to represent a skillful(or good)forecast.It is found that the R34(radius of 34 knots)wind field structure forecasts within 72 h are good regardless of DET or EPS.The performance of R50 and R64 is slightly worse but the R50 forecasts within 48 h remain good,with MODE exceeded 0.5.The R64forecast within 48 h are worth for reference as well with MODE of around 0.5.This study states that the TC wind field structure forecast by ECMWF is skillful for TCs over the western North Pacific and the South China Sea.