经济特区对发展中国家工业化的作用和影响

一、引言一般来说,在适当的背景下建立经济特区或工业园区,可以成为推进工业化发展和结构转型的有效途径。从全球范围上看,经济特区也成为诸多发展中国家推进工业化进程与实现经济转型的政策工具。《2020年世界发展报告》也提到经济特区在提高全球价值链参与度方面发挥了关键作用(世界银行,2019年)。根据联合国贸发会议2019年发布的最新《世界投资报告》,经济特区模式已被全球140多个经济体所采纳,其中包括近3/4的发展中经济体和所有转型经济体。近年来,经济特区的数量迅速增长,在147个经济体中至少有5383个经济特区(仅包括主要经济特区)。其中,大多数经济特区都是多功能区。产业园区和创新园区主要集中在更发达的新兴市场。大多数发达国家的经济特区则主要侧重于物流。

Uncertainty in Tropical Cyclone Intensity Predictions due to Uncertainty in Initial Conditions

Focusing on the role of initial condition uncertainty,we use WRF initial perturbation ensemble forecasts to investigate the uncertainty in intensity forecasts of Tropical Cyclone(TC)Rammasun(1409),which is the strongest TC to have made landfall in China during the past 50 years.Forecast results indicate that initial condition uncertainty leads to TC forecast uncertainty,particularly for TC intensity.This uncertainty increases with forecast time,with a more rapid and significant increase after 24 h.The predicted TC develops slowly before 24 h,and at this stage the TC in the member forecasting the strongest final TC is not the strongest among all members.However,after 24 h,the TC in this member strengthens much more than that the TC in other members.The variations in convective instability,precipitation,surface upward heat flux,and surface upward water vapor flux show similar characteristics to the variation in TC intensity,and there is a strong correlation between TC intensity and both the surface upward heat flux and the surface upward water vapor flux.The initial condition differences that result in the maximum intensity difference are smaller than the errors in the analysis system.Differences in initial humidity,and to a lesser extent initial temperature differences,at the surface and at lower heights are the key factors leading to differences in the forecasted TC intensity.These differences in initial humidity and temperature relate to both the overall values and distribution of these parameters.

Inflammatory risk stratification individualizes anti-inflammatory pharmacotherapy for acute type A aortic dissection

The systemic benefits of anti-inflammatory pharmacotherapy vary across cardiovascular diseases in clinical practice.We aimed to evaluate the application of artificial intelligence to acute type A aortic dissection(ATAAD)patients to determine the optimal target population who would benefit from urinary trypsin inhibitor use(ulinastatin).Patient characteristics at admission in the Chinese multicenter 5A study database(2016-2022)were used to develop an inflammatory risk model to predict multiple organ dysfunction syndrome(MODS).

THE PERFORMANCE OF GLOBAL MODELS IN TC TRACK FORECASTING OVER THE WESTERN NORTH PACIFIC FROM 2010 TO 2012

Forecasts of tropical cyclone(TC)tracks from six global models during 2010 and 2012 were assessed to study the current capability of track forecast guidance over the western North Pacific.To measure the performance of the global model forecasts,a series of statistical evaluations of track forecasts up to 120 h were carried out,including the mean,median,percentile distribution,regional distribution,relative position,correlation analysis,and binned analysis.Results showed that certain improvements have been made for the six global models in their prediction accuracy and stability in the past three years.Remarkably,stepped decreases in the values of each quantile were found at all lead time levels from 2010 to 2012 for NCEP-GFS.An analysis of the regional distribution of position errors showed that a high-latitude region,low-latitude region(which covers mostly the TC genesis region)and the South China Sea are the three main areas within which large errors tend to concentrate.The majority of the models show their own respective characteristics of systematic bias at each lead time,as established through the relative position analysis results.Only the results of NCEP-GFS and CMA-T639 did not show any obvious systematic bias in the three-year study period.Binned analyses indicated that the prediction accuracy and stability of most of the models were better for strong TCs than for weak TCs at short lead time levels.It was also found that the models tend to perform better for initially large TCs,or for those with weak vertical wind shear at lead times shorter than 48 h.The results demonstrate the heavy reliance of forecast errors upon the initial characteristics of a TC or its environmental conditions.

OVERVIEW OF SEVERE TYPHOON FITOW AND ITS OPERATIONAL FORECASTS

Severe typhoon Fitow(1323)brought persistent and heavy rainfall to Zhejiang and the Shanghai area after it made landfall at Fujian Province of China in October 2013,breaking the rainfall records of several counties and districts in Zhejiang.In this paper,we provide an overview of the characteristics of Fitow’s landfall,including its track,intensity,structural evolution,heavy rainfall,and wind.We also describe some of the associated disastrous impacts.Finally,we provide verifications of operational forecasts of its track,intensity and rainfall.Though the track and intensity is well predicted,the rainfall persistence and enhancement in the second stage in Shanghai and north Zhejiang areas are not predicted out at all.The analysis presented in this paper provides forecasters and researchers with some valuable information on Fitow,which could form a useful basis for further studies.

VERIFICATION OF ENSEMBLE TRACK FORECASTS OF TROPICAL CYCLONES DURING 2014

The track forecasts of fi ve ensemble prediction systems(JMA-WEPS,CMA-GEFS,ECMWF-EPS,NCEP-GEFS and MSC-CENS,respectively)in 2014 are evaluated in this paper.First,on the assumption of bivariate normal distribution,a probability ellipse based on ensemble spread is proposed to represent forecast uncertainties,and then the ellipse and ensemble mean are used to evaluate the fi ve different systems.It is found that the probability ellipse of ECMWF-EPS is smaller,with a high hit ratio,and its mean track errors are just a little larger than those of NCEP-GEFS within 48 h,meaning overall it outperforms the other four systems.Meanwhile,the performance of CMA-GEFS is found to be the poorest.

Evaluation of forecast performance for Super Typhoon Lekima in 2019

The predictions for Super Typhoon Lekima(2019)have been evaluated from official forecasts,global models,regional models and ensemble prediction systems(EPSs)at lead times of 1–5 days.Track errors from most deterministic forecasts are smaller than their annual mean errors in 2019.Compared to the propagation speed,the propagation direction of Lekima(2019)was much easier to determine for the official agency and numerical weather prediction(NWP)models.The National Centers for Environmental Prediction Global Ensemble Forecast System(NCEP-GEFS),Japan Meteorological Agency Global Ensemble Prediction System(JMA-GEPS)and Meteorological Service of Canada Ensemble System(MSC-CENS)are underdispersed,and the Shanghai Typhoon Institute Typhoon Ensemble Data Assimilation and Prediction System(STI-TEDAPS)is overdispersed,while the ensemble prediction system from European Centre for Medium-Range Weather Forecasts(ECMWF)shows adequate dispersion at all lead times.Most deterministic forecasting methods underestimated the intensity of Lekima(2019),especially for the rapid intensification period after Lekima(2019)entered the East China Sea.All of the deterministic forecasts performed well at predicting the first landfall point at Wenling,Zhejiang Province with a lead time of 24 and 48 h.