Influence of Sea Surface Temperature on the Predictability of Idealized Tropical Cyclone Intensity

The role of sea surface temperature (SST) forcing in the development and predictability of tropical cyclone (TC) intensity is examined using a large set of idealized numerical experiments in the Weather Research and Forecasting (WRF) model. The results indicate that the onset time of rapid intensification of TC gradually decreases, and the peak intensity of TC gradually increases, with the increased magnitude of SST. The predictability limits of the maximum 10 m wind speed (MWS) and minimum sea level pressure (MSLP) are ~72 and ~84 hours, respectively. Comparisons of the analyses of variance for different simulation time confirm that the MWS and MSLP have strong signal-to-noise ratios (SNR) from 0-72 hours and a marked decrease beyond 72 hours. For the horizontal and vertical structures of wind speed, noticeable decreases in the magnitude of SNR can be seen as the simulation time increases, similar to that of the SLP or perturbation pressure. These results indicate that the SST as an external forcing signal plays an important role in TC intensity for up to 72 hours, and it is significantly weakened if the simulation time exceeds the predictability limits of TC intensity.     

论东亚夏季风的特征、驱动力与年代际变化

本文是以新的资料和研究结果对东亚夏季风的基本特征、驱动力和年代际变化所作的重新分析与评估。内容包括四个部分:（1）东亚夏季风的基本特征;（2）东亚夏季风的驱动力;（3）东亚夏季风的年代际变率与原因;（4）东亚夏季风与全球季风的关系。结果表明:东亚夏季风是亚洲夏季风的一个重要有机部分,主要由来源于热带的季风气流组成,并随季节由南向北呈阶段性推进,它是形成夏季东亚天气与气候的主要环流和降水系统。驱动夏季风的主要强迫有三部分:外部强迫、耦合强迫与内部变率,其中人类活动引起的外强迫（气候变暖、城市化、气溶胶增加等）是新出现的外强迫,它正不断改变着东亚夏季风的特征与演变趋势。海洋与陆面耦合强迫作为自然因子是引起东亚夏季风年际和年代际变化的主要原因,其中太平洋年代尺度振荡（PDO）与北大西洋多年代尺度振荡（AMO）的协同作用是造成东亚夏季风30~40年周期振荡的主要原因。1960年代以后,东亚夏季风经历了强—弱—强的年代际变化,相应的中国东部夏季降水型出现了“北多南少”向“南涝北旱”以及“北方渐增”的转变。最近的研究表明,上述东亚夏季风年代际变化与整个亚非夏季风系统的变化趋势是一致的。在本世纪主要受气候变暖的影响,夏季风雨带将持续北移,中国北方和西部地区出现持续性多雨的格局。最后本文指出,亚非夏季风系统相比于其他区域季风系统更适合全球季风的概念。     

The 2020/21 Extremely Cold Winter in China Influenced by the Synergistic Effect of La Niña and Warm Arctic

In the first half of winter 2020/21,China has experienced an extremely cold period across both northern and southern regions,with record-breaking low temperatures set in many stations of China.Meanwhile,a moderate La Ni?a event which exceeded both oceanic and atmospheric thresholds began in August 2020 and in a few months developed into its mature phase,just prior to the 2020/21 winter.In this report,the mid?high-latitude large-scale atmospheric circulation anomalies in the Northern Hemisphere,which were forced by the negative phase of Arctic Oscillation,a strengthened Siberian High,an intensified Ural High and a deepened East Asian Trough,are considered to be the direct reason for the frequent cold surges in winter 2020/21.At the same time,the synergistic effect of the warm Arctic and the cold tropical Pacific(La Ni?a)provided an indispensable background,at a hemispheric scale,to intensify the atmospheric circulation anomalies in middle-to-high latitudes.In the end,a most recent La Ni?a prediction is provided and the on-coming evolution of climate is discussed for the remaining part of the 2020/21 winter for the purpose of future decision-making and early warning.     

Experiments with the Improved Dynamical-Statistical-Analog Ensemble Forecast Model for Landfalling Typhoon Precipitation over South China

In recent work, three physical factors of the Dynamical-Statistical-Analog Ensemble Forecast Model for Landfalling Typhoon Precipitation (DSAEF_LTP model) have been introduced, namely, tropical cyclone (TC) track, TC landfall season, and TC intensity. In the present study, we set out to test the forecasting performance of the improved model with new similarity regions and ensemble forecast schemes added. Four experiments associated with the prediction of accumulated precipitation were conducted based on 47 landfalling TCs that occurred over South China during 2004-2018. The first experiment was designed as the DSAEF_LTP model with TC track, TC landfall season, and intensity (DSAEF_LTP-1). The other three experiments were based on the first experiment, but with new ensemble forecast schemes added (DSAEF_LTP-2), new similarity regions added (DSAEF_LTP-3), and both added (DSAEF_LTP- 4), respectively. Results showed that, after new similarity regions added into the model (DSAEF_LTP-3), the forecasting performance of the DSAEF_LTP model for heavy rainfall (accumulated precipitation ≥250 mm and ≥100 mm) improved, and the sum of the threat score (TS250 + TS100) increased by 4.44%. Although the forecasting performance of DSAEF_LTP-2 was the same as that of DSAEF_LTP-1, the forecasting performance was significantly improved and better than that of DSAEF_LTP-3 when the new ensemble schemes and similarity regions were added simultaneously (DSAEF_LTP-4), with the TS increasing by 25.36%. Moreover, the forecasting performance of the four experiments was compared with four operational numerical weather prediction models, and the comparison indicated that the DSAEF_LTP model showed advantages in predicting heavy rainfall. Finally, some issues associated with the experimental results and future improvements of the DSAEF_LTP model were discussed.     

Raindrop Size Distribution Parameters Retrieved from Xinfeng C-Band Polarimetric Radar Observations

The objective of this research was to acquire a raindrop size distribution (DSDs) retrieved from C-band polarimetric radar observations scheme for the first time in south China.An observation period of the precipitation process was selected,and the shape-slope (μ-Λ) relationship of this region was statistically analyzed using the raindrop sample observations from the two-dimensional video disdrometer (2DVD) at Xinfeng Station,Guangdong Province.Simulated data of the C-band polarimetric radar reflectivity Z_(HH)and differential reflectivity Z_(DR)were obtained through scattering simulation.The simulation data were combined with DSD fitting to determine the Z_(DR)-Λand log_(10)(Z_(HH)/N_0)-Λrelationships.Using Xinfeng C-band polarimetric radar observations Z_(DR)and Z_(HH),the raindrop Gamma size distribution parametersμ,Λ,and N_0were retrieved.A scheme for using C-band polarimetric radar to retrieve the DSDs was developed.This research revealed that during precipitation process,the DSDs obtained using the C-band polarimetric radar retrieval scheme are similar to the 2DVD observations,the precipitation characteristics of rainfall intensity (R),mass-weighted mean diameter (D_m) and intercept parameter (N_w) with time obtained by radar retrieval are basically consistent with the observational results of the 2DVD.This scheme establishes the relationship between the observations of the C-band polarimetric radar and the physical quantities of the numerical model.This method not only can test the prediction of the model data assimilation system on the convective scale and determine error sources,but also can improve the microphysical precipitation processes analysis and radar quantitative precipitation estimation.The present research will facilitate radar data assimilation in the future.     

Experiments of DSAEF_LTP Model with Two Improved Parameters for Accumulated Precipitation of Landfalling Tropical Cyclones over Southeast China

The Dynamical-Statistical-Analog Ensemble Forecast model for landfalling tropical cyclones (TCs) precipitation (DSAEF_LTP) utilises an operational numerical weather prediction (NWP) model for the forecast track, while the precipitation forecast is obtained by finding analog cyclones, and making a precipitation forecast from an ensemble of the analogs. This study addresses TCs that occurred from 2004 to 2019 in Southeast China with 47 TCs as training samples and 18 TCs for independent forecast experiments. Experiments use four model versions. The control experiment DSAEF_LTP_1 includes three factors including TC track, landfall season, and TC intensity to determine analogs. Versions DSAEF_LTP_2, DSAEF_LTP_3, and DSAEF_LTP_4 respectively integrate improved similarity region, improved ensemble method, and improvements in both parameters. Results show that the DSAEF_LTP model with new values of similarity region and ensemble method (DSAEF_LTP_4) performs best in the simulation experiment, while the DSAEF_LTP model with new values only of ensemble method (DSAEF_LTP_3) performs best in the forecast experiment. The reason for the difference between simulation (training sample) and forecast (independent sample) may be that the proportion of TC with typical tracks (southeast to northwest movement or landfall over Southeast China) has changed significantly between samples. Forecast performance is compared with that of three global dynamical models (ECMWF, GRAPES, and GFS) and a regional dynamical model (SMS-WARMS). The DSAEF_LTP model performs better than the dynamical models and tends to produce more false alarms in accumulated forecast precipitation above 250 mm and 100 mm. Compared with TCs without heavy precipitation or typical tracks, TCs with these characteristics are better forecasted by the DSAEF_LTP model.     

2019年汛期气候预测效果评述及降水预测先兆信号分析

2019年汛期降水呈南多北少分布,主要多雨区位于东北和江南等地。3月发布的预报对江南、西南东部、东北东部、西北中部地区降水偏多和内蒙古中部及东北部的偏少均做了较好预测;5月发布的滚动预测将南方主要多雨中心南移,订正结果与实况更为一致。6月发布的盛夏预报及时加强了对东北地区降水趋势的订正,准确预测了东北地区降水明显偏多的特征。对南海夏季风、西南雨季、梅雨及华北雨季的季节进程预测也和实况一致。但2019年汛期降水预测也存在明显的不足之处：对长江中下游沿江降水异常偏少预测错误;对东北地区多雨的范围和异常程度估计不足。初步分析了2018—2019年冬季青藏高原积雪面积异常偏多、2018—2019年厄尔尼诺事件以及热带印度洋海温持续偏暖对长江中下游降水预测指示意义的失败,并与2018年外强迫信号及大气环流做了简单对比,指出汛期降水和传统影响因子不匹配、非对称的复杂性研究还需要深入开展。     

中国气候与环境演变评估(I):中国气候与环境变化及未来趋势

近百年来,全球气候正经历着一次以变暖为主要特征的显著变化,全球气候与环境的重大变化对中国的气候与环境演变也产生了重大影响。来自气候、环境、海洋和经济社会科学等领域的百余位专家和学者对中国气候与环境的演变及其对自然生态系统和社会经济部门的影响进行了评估,在此基础上,提出了适应和减缓气候变化的对策。本文主要阐述在全球气候变化背景下中国气候与环境的演变,并对未来气候变化的趋势做出了预测。     

东北夏季降水的年代际特征及环流变化

利用1961-2012年中国东北地区91个气象站逐月降水资料、NCEP/NCAR再分析资料和海温资料,以及经验正交函数分解EOF、显著性检验等方法,分析了东北地区夏季降水的时空分布特征、年代际变化特征及相应的环流分布型变化,探讨了不同年代际背景下东北夏季降水年际变化的环流差异。结果表明,东北夏季降水存在明显的年代际变化特征,在1961 1983年(P1)期间降水偏少,19841998年(P2)期间降水偏多,1999年之后(P3)又进入偏少时段。P2与P1时段相比,东北气旋式环流和蒙古反气旋式环流异常增强,而西北太平洋副热带地区为气旋式环流异常,来自西北太平洋偏东水汽输送贡献明显。P3与P2时段相比,东北冷涡活动偏弱,东北地区东部在850 h Pa为偏北风异常,偏南水汽输送有所减弱。进一步分析证实,北太平洋年代际振荡(PDO)对于东北地区夏季降水及相关环流型的年代际变化有重要的调制作用。P1与P3同为降水偏少时段,PDO都处于负位相,东北地区反气旋式环流都偏强;然而P1时段的多雨年,水汽输送主要来自较强的夏季风偏南气流;P3时段的多雨年,水汽输送可能主要来自西北太平洋地区。     

THE RELATIONSHIP BETWEEN HORIZONTAL VORTICITY INDUCED BY VERTICAL SHEAR AND VERTICAL MOTION DURING A SQUALL LINE PROCESS

The horizontal vorticity equation used in this study was obtained using the equations of motion in the pressure coordinate system without considering friction, to reveal its relationship with vertical shear. By diagnostically analyzing each term in the horizontal vorticity equation during a squall line process that occurred on 19 June 2010, we found that the non-thermal wind term had a negative contribution to the local change of upward movement in the low-level atmosphere, and that its impact changed gradually from negative to positive with altitude, which could influence upward movement in the mid- and upper-level atmosphere greatly. The contribution of upward vertical transport to vertical movement was the largest in the low-level atmosphere, but had negative contribution to the upper-level atmosphere. These features were most evident in the development stage of the squall line. Based on analysis of convection cells along a squall line, we found that in the process of cell development diabatic heating caused the subsidence of constant potential temperature surface and non- geostrophic motion, which then triggered strong convergence of horizontal acceleration in the mid-level atmosphere and divergence of horizontal acceleration in the upper-level atmosphere. These changes of horizontal wind field could cause a counterclockwise increment of the horizontal vorticity around the warm cell, which then generated an increase of upward movement. This was the main reason why the non-thermal wind term had the largest contribution to the strengthening of upward movement in the mid- and upper-level atmosphere. The vertical transport of large value of horizontal vorticity was the key to trigger convection in this squall line process.