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.     

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.     

台风大风预报研究回顾

大风是台风引发的三大灾害之一,考虑到现有的台风大风研究相对较少、预报经验也比较不足,因此对其预报方法进行回顾总结具有十分重要的意义。从经验预报、统计预报、数值模式预报及数值预报产品释用等4个方向梳理了台风大风预报技术的研究与应用现状:天气图、卫星云图和雷达图是经验预报中非常重要的工具;统计预报根据方法的不同可细分为回归预报、客观相似预报和气候持续性预报;数值模式预报方面,国内外多家机构都研发了相应的台风大风预报产品;数值预报产品的释用目前则包含了动力释用、统计释用和人工智能释用。同时总结了上述4类预报方法各自的优势和不足。最后,讨论了未来研究与实际业务中进一步提高台风大风预报能力的可能发展方向。     

海南岛热带气旋极端降水的特征及其成因

围绕海南岛热带气旋(TC)极端降水的特征及其成因,利用国家气象信息中心提供的海南岛台站日降水数据、上海台风所的TC最佳路径数据集和NCEP/NCAR再分析数据,通过气候统计、天气诊断相结合的方法,探讨了1958—2013年海南岛TC极端降水的空间分布和时间变化特征,并进一步诊断分析了极端降水产生的可能成因。结果表明,海南岛TC极端降水在西北部出现最多,东南部出现较少。从长期趋势看,无论从TC极端降水量还是从TC极端降水频数,TC极端降水的极端趋势均在增加。充足的西南水汽通量输送是产生TC极端降水的重要条件;当南亚高压和副热带高压相距较近,即南亚高压偏东偏强,副热带高压偏西偏强时,海南岛容易出现TC极端降水事件;在TC路径和低层风场结构的配合下,海南岛地形对极端降水的落区有关键影响。     

极端天气气候事件监测与预测研究进展及其应用综述

极端天气气候事件(简称"极端事件")分为单站极端事件和区域性极端事件。本文回顾了极端事件的研究进展,首先回顾了单站极端温度、极端降水和干旱事件的观测研究及相关指数,进而对近年来不断增多的区域性极端事件研究做了简要回顾,最后还回顾了极端事件气候预测研究进展。同时,对国内外在极端事件气候监测和预测业务现状进行了初步总结,并指出:在极端事件气候监测方面中国的业务产品较丰富,并率先开展了针对区域性极端事件的监测业务,但在产品表现形式上缺乏统一组织,特别是英文产品表现力严重不足;在极端事件气候预测方面,国家气候中心发展了两种方法:一个是基于物理统计的BP-CCA和OSR的干旱预测方法,另一个基于国家气候中心月动力延伸预报模式(DERF)的高温预测方法。最后,对极端事件监测和预测业务发展及相关科学问题给出展望,指出应根据极端事件的业务需求继续加强相关研究和业务能力建设。     

甘肃白银厂矿区及其外围铜矿床成矿特征与定量预测

北祁连地区是我国重要的海相火山成因铜多金属块状硫化物矿床成矿带,位于该区东段的白银矿田内产出有多个大型-特大型VMS矿床,具有较好的找矿前景.在该地区铜矿床成矿特征研究的基础上,利用GIS技术提取与成矿有关的地层、构造、岩浆岩、地球化学等多元找矿信息,构建了白银矿区及外围铜矿床的证据权重找矿模型,利用后验概率圈定出找矿远景区,按照各找矿远景区相对成矿可能性的大小和各找矿标志将远景区分为Ⅰ、Ⅱ、Ⅲ3级,各级找矿远景区各3个.     

地形对台风“海燕”暴雨增幅作用的观测与模拟

1330号台风"海燕"过程影响海南岛的强降水落区和强降水极值点(毛感乡)均位于南部地区,利用海南省区域加密自动站、三亚多普勒雷达以及0.25°×0.25°ERA-interim再分析资料对强降水成因进行观测分析,应用WRF Ver3.1.1模式对"海燕"进行模拟试验。结果表明:(1)"海燕"从海南岛南部近海北上阶段,其外围的偏东风或偏南风与五指山、吊罗山形成向南开口的"厂"字形地形正交,加密自动站和多普勒雷达在五指山区及"厂"字形地形南侧均探测到多个β中尺度风向辐合切变线或气旋性辐合涡旋,毛感乡附近存在明显的风向辐合,地面辐合中心与小时雨量大值区基本吻合。(2)"厂"字形地形迎风坡的强迫抬升导致气流垂直速度增大,毛感乡附近存在的水平的β中尺度辐合切变和垂直的β中尺度环流,有利于边界层辐合和中高层辐散增强,降水显著增幅。(3)数值模拟的强降水落区和降水极值点与实况基本一致,极值雨量较实况偏小;地形对山区及山脉迎风(背风)坡的雨量增(减)幅作用明显;有地形时,在五指山区及"厂"字形地形南侧容易产生β中尺度风向辐合区。     

伴随IOD型和独立型ENSO对山东气候年际变化的影响

使用1951年以来66 a的观测和再分析资料,通过合成分析的方法对比分析了厄尔尼诺/拉尼娜（El Niño /La Niña）伴随正/负印度洋偶极子（positive/negative Indian Ocean Dipole,pIOD/nIOD）发生年或独立发生年山东夏、秋季气温和降水的年际变化特征,结果表明,伴随IOD型和独立型El Niño/La Niña对山东夏、秋季气温和降水的影响在强度、范围、正负位相、空间型态上存在很大的差异。在气温方面,El Niño在pIOD的调制作用下对山东南部地区夏季气温年际变化的影响加强;El Niño与pIOD伴随发生时,山东秋季气温较常年偏高,而独立发生时气温则偏低,呈反位相变化;La Niña与nIOD伴随发生年夏季鲁西北气温较常年偏低,La Niña独立发生年夏季半岛东部气温较常年偏高,气温异常呈反位相变化;nIOD对La Niña的调制促进作用有利于山东秋季气温较常年异常偏高;850 hPa气温异常与山东表面气温异常有很强的正相关关系。在降水方面,El Niño在pIOD的调制作用下容易引起山东北部地区夏季降水偏少,但会削弱其对山东中部地区秋季降水负异常的影响;La Niña在nIOD的调制作用下山东境内降水都较常年偏多,但降水异常地域分布非常不均,鲁西北降水较常年显著偏多;独立型La Niña更易引起鲁西北西部、鲁中、鲁南大部分地区夏季降水偏少。850 hPa环流异常配合温度场异常对山东夏、秋季降水异常分布有一定的影响。     

影响中国的台风频数年代际变化趋势:1951-2004年

Interdecadal variations in the frequency of typhoon affecting China (TAC) during 1951-2004 were investigated in this study. The yearly frequency of TACs showed a slightly increasing trend from the 1950s to the early 1970s and a significant decreasing trend afterwards. There were more TACs during the 1960s while the most inactive period was observed in recent 10 years. A decreasing trend was observed in the monthly frequency of TACs in June, August and September throughout the 54 years. Large interannual variabilities were apparent in yearly and monthly frequencies of TACs.     

2004年全球重大气候事件概述

2004年全球气候持续偏暖。年初，暴雪席卷欧洲多国，美国受到罕见大雪袭击，南亚和墨西哥遭遇低温严寒。北半球夏秋季，西太平洋、大西洋热带风暴活动频繁。日本、菲律宾和美国受灾严重。年内，非洲、亚洲部分国家发生严重干旱；同时，南亚、南美洲及非洲多国暴雨致洪。年内，欧洲伊比利亚半岛、日本和澳大利亚遭遇高温热浪。