ASSIMILATION OF OBSERVED SURFACE WIND WITH GRAPES

With the advances of numerical weather simulation and reduced data assimilation updating cycle, surface observation data assimilation becomes more and more important in data assimilation systems. It is widely accepted that a better data assimilation system should contain the restriction of thermodynamic processes in the surface layer. Therefore, in this paper, a new surface wind observation operator is utilized in Global and Regional Assimilation PrEdiction System_3D-Variance (GRAPES_3D-Var), with the restriction of thermodynamic process in the planetary boundary layer (PBL). In order to research the ability of this new surface wind observation operator in assimilation and forecasting, a series of experiments are operated by using the GRAPES model. The main results indicate that this new method of surface wind observation operator has positive impact on the forecast with the GRAPES model.     

中国夏季降水对南印度洋偶极子的响应研究

分析了春季印度洋海表温度（SST）与中国160个站夏季降水的关系,得到:印度洋全海盆的增温趋势与我国夏季降水的气候线性变化趋势是十分一致的。另外,热带外南印度洋出现西南印度洋为正（负）、其东北部出现（负）正海温异常的分布模态时,定义为正（负）南印度洋偶极子PSIOD（NSIOD）事件。SIOD事件对中国夏季降水具有重要影响,PSIOD年,5月份中国江南和西南以及长江中下游的降水偏多;6～8月份华北、东北区域、长江中游以及华南地区降水增多,华南与华北之间的区域降水偏少,即主要为两条雨带的分布。NSIOD年,5月份中国大部降水偏少; 6～8月中国西南、江南地区以及黄淮地区降水偏多。不同时段SIOD所起的作用是不同的,5月,SIOD主要通过改变马斯克林局地环流的变化,影响印度洋低层越赤道的水汽通量输送;6～8月,通过改变海洋大陆下垫面SST热状态,改变其上空对流强度以及水汽输送方向,并间接影响西北太平洋副热带高压的强度和南北位置,进而对中国雨带的分布产生影响。     

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。     

顶管施工中顶力与顶程关系及其影响因素分析

以上海某长距离急曲线顶管工程为例，通过现场实测4节管段顶进过程中的顶力，研究了顶力随顶程的变化规律，系统分析了顶进过程中顶力的主要影响因素，得到了一些有用的结论。     

塔里木盆地中新生代海侵和海相地层研究的新进展

中新生代海侵是塔里木盆地地质发展史上的重要事件之一。通过对新近发现的古生物化石和海相地层资料研究，本文提出了早白垩世、晚白垩世、古近纪的海侵范围的新认识。同时，依据露头和钻井资料提出了中新世海水分布的新范围。这些新成果对厘定塔里木盆地中新生代地层时代，建立整个盆地中新生代地层格架和油气远景分析具有重要意义。     

克拉玛依蛇绿混杂岩带的基本特征和锆石SHRIMP年龄信息

新发现的克拉玛依蛇绿混杂岩带分布于准噶尔盆地西北缘,表现为组分齐全的蛇绿岩和增生杂岩。由盆地边缘向山区方向,大体呈依次带状分布的超镁铁质岩、镁铁质岩、枕状玄武岩和深海相硅质岩,同时发现超镁铁岩之上被一套火山磨拉石沉积不整合覆盖。在克拉玛依蛇绿岩的白碱滩段中采得蚀变辉长岩样品,锆石SHRIMP定年结果集中在(414.4 8.6)Ma和(332±14)Ma。这一发现为研究中亚洋盆形成和消亡时代提供了重要依据,也为确定准噶尔盆地基底性质提供了重要线索。     

胶东邢家山钼钨矿床辉钼矿Re-Os同位素测年及其地质意义

邢家山矿床是胶东地区一特大型矽卡岩-斑岩型钼钨矿床,构造位置上处于华北板块东南缘与扬子板块对接地带,在成因上与幸福山似斑状含角闪二长花岗岩密切相关,归属于该区与燕山早期花岗质岩浆作用有关的特大型、大型和中型铜钼多金属矿床成矿系列。本文对该矿床透辉石榴矽卡岩中的辉钼矿进行了Re-Os同位素测年,结果显示,辉钼矿Re-Os同位素模式年龄范围为156.91±1.78Ma至160.70±1.66Ma,加权平均值为158.91±1.91Ma,对应的Re-Os等时线年龄为158.70±2.06Ma;这些年龄数据与区域上的燕山早期花岗岩锆石U-Pb年龄(158.53±0.79Ma)相近,指示区域上该期铜钼多金属矿化与区内花岗岩具有密切的时间和成因关系。中、晚侏罗世华北东部广泛的地壳增厚作用和地壳重熔导致的大规模地壳重熔型花岗质岩浆活动为该区钼钨多金属矿成矿提供了主要成矿物质和流体。结合已有的研究成果,认为胶东地区中生代以来岩浆活动及相应的成矿作用可能主要存在4期,即:约165～155Ma的铜钼多金属矿化期、约137～110Ma的金矿化期、约120～110Ma的铜钼铅锌多金属矿化期、和约100～75Ma的金银铅锌多金属矿化期,分别对应于燕山早期-燕山晚期的各期次花岗质岩浆活动。     

Vertical structures of PM10 and PM 2.5 and their dynamical character in low atmosphere in Beijing urban areas

The vertical structures and their dynamical character of PM2.5 and PM10 over Beijing urban areas are revealed using the 1 min mean continuous mass concentration data of PM2.5 and PM10 at 8, 100, and 320 m heights of the meteorological observation tower of 325 m at Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP CAS tower hereafter) on 10―26 August, 2003, as well as the daily mean mass concentration data of PM2.5 and PM10 and the continuous data of CO and NO2 at 8, 100 (low layer), 200 (middle layer), and 320 m (high layer) heights, in combination with the same period meteorological field observation data of the meteorological tower. The vertical distributions of aerosols observed on IAP CAS tower in Beijing can be roughly divided into two patterns: gradually and rapidly decreasing patterns, I.e. The vertical distribution of aerosols in calm weather or on pollution day belongs to the gradually decreasing pattern, while one on clean day or weak cold air day belongs to the rapidly decreasing pattern. The vertical distributive characters of aerosols were closely related with the dynamical/thermal structure and turbulence character of the atmosphere boundary layer. On the clean day, the low layer PM2.5 and PM10 concentrations were close to those at 8 m height, while the concentrations rapidly decreased at the high layer, and their values were only one half of those at 8 m, especially, the concentration of PM2.5 dropped even more. On the clean day, there existed stronger turbulence below 150 m, aerosols were well mixed, but blocked by the more stronger inversion layer aloft, and meanwhile, at various heights, especially in the high layer, the horizontal wind speed was larger, resulting in the rapid decrease of aerosol concentration, I.e. Resulting in the obvious vertical difference of aerosol concentrations between the low and high layers. On the pollution day, the concentrations of PM2.5 and PM10 at the low, middle, and high layers dropped successively by, on average, about 10% for each layer in comparison with those at 8 m height. On pollution days, in company with the low wind speed, there existed two shallow inversion layers in the boundary layer, but aerosols might be, to some extent, mixed below the inversion layer, therefore, on the pollution day the concentrations of PM2.5 and PM10 dropped with height slowly; and the observational results also show that the concentrations at 320 m height were obviously high under SW and SE winds, but at other heights, the concentrations were not correlated with wind directions. The computational results of footprint analysis suggest that this was due to the fact that the 320 m height was impacted by the pollutants transfer of southerly flow from the southern peripheral heavier polluted areas, such as Baoding, and Shijiazhuang of Hebei Province, Tianjin, and Shandong Province, etc., while the low layer was only affected by Beijing's local pollution source. The computational results of power spectra and periods preliminarily reveal that under the condition of calm weather, the periods of PM10 concentration at various heights of the tower were on the order of minutes, while in cases of larger wind speed, the concentrations of PM2.5 and PM10 at 320 m height not only had the short periods of minute-order, but also the longer periods of hour order. Consistent with the conclusion previously drawn by Ding et al., that air pollutants at different heights and at different sites in Beijing had the character of "in-phase" variation, was also observed for the diurnal variation and mean diurnal variation of PM2.5 and PM10 at various heights of the tower in this experiment, again confirming the "in-phase" temporal/spatial distributive character of air pollutants in the urban canopy of Beijing. The gentle double-peak character of the mean diurnal variation of PM2.5 and PM10 was closely related with the evident/similar diurnal variation of turbulent momentum fluxes, sensible heat fluxes, and turbulent kinetic energy at various heights in the urban canopy. Besides, under the condition of calm weather, the concentration of PM2.5 and PM10 declined with height slowly, it was 90% of 8 m concentration at the low layer, a little lesser than 90% at the middle layer, and 80% at the high layer, respectively. Under the condition of weak cold air weather, the concentration remarkably dropped with height, it was 70% of 8 m concentration at the low layer, and 20%―30% at the middle and high layers, especially the concentration of PM2.5 was even lower.     

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.