SWCWARMS 模式对巴中地区预报能力的检验

应用巴中地区218个自动气象观测站2016年6～8月逐日的24h累积雨量,采取基于客观统计的检验方法,针对24h累积雨量,采取TS评分、BIAS评分和空报率对比分析了 SWCWARMS 模式和 EC 细网格模式在巴中地区的预报能力。研究结果表明:(1)从降水落区来看,两个模式都对雨带的移动都有较好的预报能力;(2)从降水 TS 评分看,SWCWARMS模式在各量级上的 TS 评分都优于 EC 模式;(3)从降水 BIAS 评分看,EC 模式容易漏报中雨及以上量级的降水,而 SWCWARMS 模式则对大暴雨的预报有较大的空报;(4)从逐月评估结果看,6月和7月SWCWARMS 模式较EC模式有更好的预报效果,8月两者差异不大。总体而言,SWCWARMS 模式在巴中地区的预报效果优于 EC 模式。      

基于快速更新同化数值预报的小时降水量时间滞后集合订正技术

由中小尺度对流系统造成短时强降水天气的发生发展十分迅速,对其落区和时效的预报预警一直都是预报业务中的难点。本文基于快速更新同化的中尺度数值预报系统GRAPES-RAFS 0. 1°×0. 1°分辨率逐小时降水预报,首先通过时间滞后集合预报方法构建了多个集合成员,使用平均TS评分值计算相应预报成员权重系数建立预报方程,然后采用频率匹配订正法进行降水量级订正,从而得到集合订正的逐小时降水量预报。2017年8-9月的逐日试验和典型个例预报结果评估表明效果良好。(1)GRAPES-RAFS最新时次的预报场并不完全代表最好的预报效果,通过时间滞后集合订正方法自动识别优选预报成员,显著提高了预报能力;(2)GRAPES-RAFS预报存在降水量级偏弱的系统性误差,经过频率匹配方法订正后,在量级预报上更接近实况;(3)时间滞后集合预报对我国中东部(包括黄淮、江淮、江南地区)的小时降水量订正效果最好;(4)进一步使用的频率匹配订正方法显著提升了逐时降水量的预报效果,其在降水频率更高、强度更大的江南南部、华南、西南地区效果更为显著;(5)对于中小尺度的强降水过程,经过上述方法订正后,显著提高了模式对强降水系统位置、形态及降水量级的预报水平。     

华南快速循环同化模式在湖南不同环流型下的小时降水预报性能检验

利用T-mode斜交旋转主成分分析法,对湖南2021年汛期(4—9月)逐小时850 hPa风场进行环流分型,在此基础上开展同期华南快速循环同化模式(CMA-GD-R3)小时降水预报性能检验。结果表明：影响湖南2021年汛期的主要环流型为西南涡切变型、切变型、副热带高压边缘南风型和台风外围东风型4类;模式小时降水预报的晴雨准确率和分级降水TS评分日变化特征明显,晴雨准确率夜间高于白天,分级降水TS评分峰值出现在早晨,各环流型的临近时效降水预报效果较好,短时强降水发生频次最高的西南涡切变型晴雨准确率较低,副热带高压边缘南风型在较大量级降水表现相对较差;SAL(structure amplitude and location)检验显示,西南涡切变型、切变型过程模式位置预报较接近实况,强度预报表现为前弱后强,副热带高压边缘南风型过程预报落区分散,位置预报不稳定,整体强度较实况明显偏弱,台风外围东风型过程在短时预报时效落区接近实况,强度预报显著偏弱,该方法能较客观地反映模式降水预报空间偏差。     

基于局地增长模培育法的对流可分辨尺度WRF模式对河南“21·7”特大暴雨的预报评估

基于WRF(Weather Research and Forecasting)模式,选取河南“21·7”特大暴雨事件,采用局地增长模培育法(Local Breeding Growth Mode,LBGM)生成对流尺度集合预报系统,在此基础上对24 h累积降水量进行SAL(Structure,Amplitude and Location)检验,结合预报成功指数(Threat Score,TS)、公平成功指数(Equitable Threat Score,ETS)评分等评分结果进行对比分析,综合评估集合预报成员的预报效果,表明:1)基于局地增长模培育法生成初始扰动的集合预报系统成员对于强降水预报有一定优势,在降水强度和位置的预报上与实况较接近;2)经检验,成员e003的TS和ETS评分在20日00时—21日00时(北京时,下同)和21日08时—22日08时两个强降水时段内表现最佳,并在SAL检验中对应较好的降雨强度A和雨区位置L,而成员e008暴雨TS、ETS评分最低,对应SAL检验中具有一定的位置偏差,即TS、ETS评分和SAL检验之间存在相关性,将二者有机结合,可以为业务工作中定量评估模式降水预报效果提供参考;3)通过对比整体评分表现较好的成员e003和较差的成员e008,两者预报的位势高度场与ERA5(ECMWF reanalysis v5,ERA5)再分析资料之间的差值,可以验证降水预报误差主要源于对低涡系统的预报偏差,同时预报评分较好的成员其位势高度偏差较小,综合评估效果更佳。     

基于MET系统对SWCWARMS及GRAPES模式在西南地区的站点检验分析

应用国家基本观测站资料、自动站逐时降水资料,基于客观统计检验方法,针对降水(12h、24h累积雨量)、近地面要素(2m温度、10m风)和高空要素(风场、温度场、高度场),分别评估SWCWARMS模式和GRAPES模式对2015年西南地区预报能力,得到如下几点结论:(1)SWCWARMS模式降水ETS评分高于GRAPES模式,除24h小雨外SWCWARMS模式偏差值均高于GRAPES模式,两个模式在不同预报时效内对中雨、大雨、暴雨都表现一定程度的空报;(2)12h降水分段评分上,SWCWARMS模式TS评分均高于GRAPES模式,但SWCWARMS模式预报降水范围过大,随着预报时效增长空报多于GRAPES模式;SWCWARMS模式中雨和大雨空报大于其它量级降水,GRAPES模式对大暴雨漏报较多其它量级降水表现为空报;(3)两模式对高度场和温度场预报优于风场,对对流层中层预报优于中低层,SWCWARMS模式对高度场和温度场预报优于GRAPES模式,夏半年SWCWARMS模式均方根误差小于GRAPES模式;(4)两模式都表现出2m温度均方根误差在秋季增加而春季减小这一特征,SWCWARMS模式近地面要素均方根误差均小于GRAPES模式。      

基于邻域最优概率的GRAPES快速更新循环同化预报系统逐时降水订正方法

针对高分辨率数值天气预报的时空不确定性, 利用邻域最优概率方法对华南区域GRAPES快速更新循环同化预报系统的24 h预报进行逐时降水订正和检验评估。结果表明: (1)邻域法能改善模式降水预报的空间不确定性, 最优邻域半径随降水等级增加而减小, 强降水的最优邻域半径约为60 km; (2)通过引入时间滞后因子, 可进一步改善模式不同时间起报的不确定性, 结合Brier评分确定了时间滞后窗为4 h; (3)提出基于邻域最优概率阈值的降雨进行分级订正方法, 有效提升了降水客观预报能力, 晴雨预报较模式全部为正技巧, TS评分达到0.89以上, 总体提升幅度约5.3%;强降水预报同样均为正技巧, TS评分呈先降后升趋势, 在12 h时效前后预报效果最优, 进一步提升了GRAPES快速更新循环同化预报系统的业务预报水平。      

SWCWARMS及ECMWF模式对四川盆地暖区型和斜压锋生型暴雨预报检验分析

利用2014～2016年5～10月四川盆地所有观测站资料及SWCWARMS模式、ECMWF模式同时段20时起报的24h累积降水资料,基于邻域法FSS、ETS评分指数检验了两模式对于高能暖区型暴雨及斜压锋生型暴雨预报的预报性能。主要结论为:(1)两种类型暴雨过程平均误差均是SWCWARMS模式较ECMWF模式大,且误差值为正,表明模式以湿偏差为主;(2)高能暖区型暴雨FSS评分各降水量级各空间尺度均是SWCWARMS模式高于ECMWF模式;斜压锋生型暴雨50mm以下量级降水在36km以下空间尺度ECMWF模式FSS评分高于SWCWARMS模式,54km以上空间尺度SWCWARMS模式评分较高,大暴雨量级降水各尺度下均是SWCWARMS模式评分较高;(3)高能暖区型暴雨ETS评分暴雨、大暴雨量级SWCWARMS模式评分较高,中雨、大雨ECMWF模式预报更优;斜压锋生型暴雨ETS评分,中雨、大雨及暴雨量级降水预报ECMWF优于SWCWARMS,大暴雨量级SWCWARMS模式预报更优。      

T213降水预报产品在新疆区域的检验分析——晴雨检验

利用2006年新疆地面气象观测站的实况降水资料和T213模式的降水预报值,根据中短期天气预报质量检验办法中客观降水检验方法,对T213降水预报产品的24h晴雨预报能力进行了检验分析.结果表明:新疆地区T213降水的晴雨TS评分和空、漏报率均存在明显的时空分布差异;伊犁河谷、阿勒泰地区东部和西部沿天山地区TS值较高,而地形条件复杂的区域和降水少的沙漠腹地TS值较低;晴雨TS评分空间分布情况在少雨的春季与多雨的夏季大体一致,这与新疆三山夹两盆的特殊地形有关;晴雨TS评分存在明显的季节变化,与季节雨量多寡存在一定的对应关系.     

WRF模式对吉林省2009年东北冷涡降水的预报能力检验

本文以08-08时的降水为例,应用自动站逐时观测数据和相应的模式预报资料,从降水区域预报、24小时降水量级预报、过程降水预报等几个方面检验XVRF模式对2009年6月份的冷涡天气的降水预报效果。结果表明,WRF模式对东北冷涡降水的预报无论在降水区域预报、不同时段降水、不同量级降水的预报上都表现出了较好的预报能力,特别是24小时降水晴雨确率;此外,对于冷涡天气的降水过程预报也较好,突出表现在逐时预报的晴雨确率、降水过程的起始时间等方面。这些结果都体现了WRF模式具有很好的使用价值和应用前景。     

2021年攀西地区精细化预报与数值模式小时降水检验

基于精细化预报（GDDZ）和CMA-MESO、西南区域模式（SWC）两家高分辨率模式的小时降水预报,从TS（Threat Score）评分、小时降水频次、小时降水强度、峰值时间等方面,对2021年汛期攀西地区16次降水过程进行小时尺度的检验。结果表明:（1）从逐时降水来看,在晴雨（0.1 mm）TS评分中,GDDZ在00~11时表现较优,CMA-MESO模式在12~23时表现较优;在大雨（7 mm）和暴雨（15 mm）TS评分中,CMA-MESO模式表现较优。（2）从小时降水频次来看,SWC模式预报的降水发生频次空间分布与实况更为接近;从小时降水强度来看,GDDZ预报的降水强度与实况更为接近。（3）从降水量峰值时间来看,GDDZ与实况更为接近;从小时降水强度峰值和降雨频率峰值时间来看,CMA-MESO模式预报与实况更为接近。      

VARIABILITY OF INTER-ANNUAL RELATIONSHIP BETWEEN INDIAN OCEAN DIPOLE AND HUAXI REGION’S AUTUMN PRECIPITATION

The moving-window correlation analysis was applied to investigate the relationship between autumn Indian Ocean Dipole (IOD) events and the synchronous autumn precipitation in Huaxi region, based on the daily precipitation, sea surface temperature (SST) and atmospheric circulation data from 1960 to 2012. The correlation curves of IOD and the early modulation of Huaxi region’s autumn precipitation indicated a mutational site appeared in the 1970s. During 1960 to 1979, when the IOD was in positive phase in autumn, the circulations changed from a “W” shape to an ”M” shape at 500 hPa in Asia middle-high latitude region. Cold flux got into the Sichuan province with Northwest flow, the positive anomaly of the water vapor flux transported from Western Pacific to Huaxi region strengthened, caused precipitation increase in east Huaxi region. During 1980 to 1999, when the IOD in autumn was positive phase, the atmospheric circulation presented a “W” shape at 500 hPa, the positive anomaly of the water vapor flux transported from Bay of Bengal to Huaxi region strengthened, caused precipitation ascend in west Huaxi region. In summary, the Indian Ocean changed from cold phase to warm phase since the 1970s, caused the instability of the inter-annual relationship between the IOD and the autumn rainfall in Huaxi region.     

全球贸易隐含碳变化及其影响分析

基于最新的GTAP8 (Global Trade Analysis Project）数据库,使用投入产出法,分析了2004年到2007年全球贸易变化下南北集团贸易隐含碳变化及对全球碳排放的影响。结果显示,随着发展中国家进出口规模扩张,全球贸易隐含碳流向的重心逐渐向发展中国家转移。2004年到2007年,发达国家高端设备制造业和服务业出口以及发展中国家资源、能源密集型行业及中低端制造业出口的趋势加强,该过程的生产转移导致全球碳排放增长4.15亿t,占研究时段全球贸易隐含碳增量的63%。未来发展中国家的出口隐含碳比重还将进一步提高。贸易变化带来的南北集团隐含碳流动变化对全球应对气候变化行动的影响日益突出,发达国家对此负有重要责任。     

Retrieval of outgoing longwave radiation from COMS narrowband infrared imagery

Hourly outgoing longwave radiation(OLR) from the geostationary satellite Communication Oceanography Meteorological Satellite(COMS) has been retrieved since June 2010. The COMS OLR retrieval algorithms are based on regression analyses of radiative transfer simulations for spectral functions of COMS infrared channels. This study documents the accuracies of OLRs for future climate applications by making an intercomparison of four OLRs from one single-channel algorithm(OLR12.0using the 12.0 μm channel) and three multiple-channel algorithms(OLR10.8+12.0using the 10.8 and 12.0 μm channels; OLR6.7+10.8using the 6.7 and 10.8 μm channels; and OLR All using the 6.7, 10.8, and 12.0 μm channels). The COMS OLRs from these algorithms were validated with direct measurements of OLR from a broadband radiometer of the Clouds and Earth's Radiant Energy System(CERES) over the full COMS field of view [roughly(50°S–50°N, 70°–170°E)] during April 2011.Validation results show that the root-mean-square errors of COMS OLRs are 5–7 W m-2, which indicates good agreement with CERES OLR over the vast domain. OLR6.7+10.8and OLR All have much smaller errors(～ 6 W m-2) than OLR12.0and OLR10.8+12.0(～ 8 W m-2). Moreover, the small errors of OLR6.7+10.8and OLR All are systematic and can be readily reduced through additional mean bias correction and/or radiance calibration. These results indicate a noteworthy role of the6.7 μm water vapor absorption channel in improving the accuracy of the OLRs. The dependence of the accuracy of COMS OLRs on various surface, atmospheric, and observational conditions is also discussed.     

COMPARATIVE ANALYSIS OF VARIOUS DATA OF AIR–SEA TEMPERATURE DIFFERENCE AND ITS VARIATION ACROSS SOUTH CHINA SEA IN THE PAST 35 YEARS

Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.     

Information for Authors

AIMS AND SCOPE
Atmospheric and Oceanic Science Letters （AOSL） publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography. Contributions from all over the world are welcome.     

Our Warmest Thanks to AAS Reviewers 2014

正The editorial office of Advances in Atmospheric Sciences(AAS),on behalf of all AAS editors,would like to publicly acknowledge the people listed below who served as reviewers for the journal daring 1 September 2013 to 24 August 2014.We recognize that the time and work of the reviewers is the most important resource in academic publishing.The quality of our journal depends in a crucial way upon the reviewing process and therefore all reviewers'time and efforts taken to sustain the quality of the journal are greatly appreciated.     

Data selection using support vector regression

Geophysical data sets are growing at an ever-increasing rate, requiring computationally efficient data selection(thinning)methods to preserve essential information. Satellites, such as Wind Sat, provide large data sets for assessing the accuracy and computational efficiency of data selection techniques. A new data thinning technique, based on support vector regression(SVR), is developed and tested. To manage large on-line satellite data streams, observations from Wind Sat are formed into subsets by Voronoi tessellation and then each is thinned by SVR(TSVR). Three experiments are performed. The first confirms the viability of TSVR for a relatively small sample, comparing it to several commonly used data thinning methods(random selection, averaging and Barnes filtering), producing a 10% thinning rate(90% data reduction), low mean absolute errors(MAE) and large correlations with the original data. A second experiment, using a larger dataset, shows TSVR retrievals with MAE < 1 m s-1and correlations 0.98. TSVR was an order of magnitude faster than the commonly used thinning methods. A third experiment applies a two-stage pipeline to TSVR, to accommodate online data. The pipeline subsets reconstruct the wind field with the same accuracy as the second experiment, is an order of magnitude faster than the nonpipeline TSVR. Therefore, pipeline TSVR is two orders of magnitude faster than commonly used thinning methods that ingest the entire data set. This study demonstrates that TSVR pipeline thinning is an accurate and computationally efficient alternative to commonly used data selection techniques.     

Temporal vulnerability in hazardscapes: Flood memory-networks and referentiality along the North Carolina Neuse River (USA)

Social models of population vulnerability to disasters increasingly include the notion that vulnerability has a strong temporal component. While this temporality is typically conceptualized as objective (making vulnerability “dynamic,” “multiscalar,” and/or “historical”), it consistently fails to acknowledge that among stakeholders managing hazardscapes temporality is also a social process in which subjective experience of time may play a role in creating situations of population vulnerability. This paper proposes that the temporal situatedness of a population relative to past hazard events and the quality with which stakeholders engage hazard memory-chains combine to significantly influences its vulnerability to natural hazards. It is proposed that this temporal vulnerability is characterized by shared, population level potential for surprise and can be evaluated by exploration of time-series depth and temporal reference points in historical ecological narratives and documents. Based on ethnohistoric research conducted from 2002 to 2006 in flood-prone eastern North Carolina (USA), it is illustrated how temporal vulnerability was relatively higher in the Neuse River watershed located at the City of Kinston than surrounding watersheds. Due to the combination of factors including the damming of the Neuse River in the 1980s, outdated official floodplain maps, relatively unmonitored floodplain development, the stochastic timing of flood events (placing the last major flood more than a generation away), technological optimism, and turnover of floodplain officials and residents, local stakeholders were seriously misinformed about the space-time risks involved both before and after the disaster of Hurricane Floyd (1999) happened. To deal with this inconsistency, the temporal rarity of Hurricane Floyd as a “500-year event” has been motivated and embraced by many in an effort to continue life-as-is. The paper proposes that the concept of temporal vulnerability is further explored and used as key dimension in the vulnerability sciences.     

An assessment of the predictability of the East Asian Subtropical Westerly Jet based on TIGGE data

The predictability of the position, spatial coverage and intensity of the East Asian subtropical westerly jet(EASWJ) in the summers of 2010 to 2012 was examined for ensemble prediction systems(EPSs) from four representative TIGGE centers,including the ECMWF, the NCEP, the CMA, and the JMA. Results showed that each EPS predicted all EASWJ properties well, while the levels of skill of all EPSs declined as the lead time extended. Overall, improvements from the control to the ensemble mean forecasts for predicting the EASWJ were apparent. For the deterministic forecasts of all EPSs, the prediction of the average axis was better than the prediction of the spatial coverage and intensity of the EASWJ. ECMWF performed best, with a lead of approximately 0.5–1 day in predictability over the second-best EPS for all EASWJ properties throughout the forecast range. For probabilistic forecasts, differences in skills among the different EPSs were more evident in the earlier part of the forecast for the EASWJ axis and spatial coverage, while they departed obviously throughout the forecast range for the intensity. ECMWF led JMA by about 0.5–1 day for the EASWJ axis, and by about 1–2 days for the spatial coverage and intensity at almost all lead times. The largest lead of ECMWF over the relatively worse EPSs, such as NCEP and CMA, was approximately 3–4 days for all EASWJ properties. In summary, ECMWF showed the highest level of skill for predicting the EASWJ, followed by JMA.