A Nonlinear Representation of Model Uncertainty in a Convective-Scale Ensemble Prediction System     

Zhizhen XU  Jing CHEN  Mu MU  Guokun DAI  Yanan MA 《大气科学进展》2022,39(9):1432-1450

How to accurately address model uncertainties with consideration of the rapid nonlinear error growth characteristics in a convection-allowing system is a crucial issue for performing convection-scale ensemble forecasts. In this study, a new nonlinear model perturbation technique for convective-scale ensemble forecasts is developed to consider a nonlinear representation of model errors in the Global and Regional Assimilation and Prediction Enhanced System (GRAPES) Convection-Allowing Ensemble Prediction System (CAEPS). The nonlinear forcing singular vector (NFSV) approach, that is, conditional nonlinear optimal perturbation-forcing (CNOP-F), is applied in this study, to construct a nonlinear model perturbation method for GRAPES-CAEPS. Three experiments are performed: One of them is the CTL experiment, without adding any model perturbation; the other two are NFSV-perturbed experiments, which are perturbed by NFSV with two different groups of constraint radii to test the sensitivity of the perturbation magnitude constraint. Verification results show that the NFSV-perturbed experiments achieve an overall improvement and produce more skillful forecasts compared to the CTL experiment, which indicates that the nonlinear NFSV-perturbed method can be used as an effective model perturbation method for convection-scale ensemble forecasts. Additionally, the NFSV-L experiment with large perturbation constraints generally performs better than the NFSV-S experiment with small perturbation constraints in the verification for upper-air and surface weather variables. But for precipitation verification, the NFSV-S experiment performs better in forecasts for light precipitation, and the NFSV-L experiment performs better in forecasts for heavier precipitation, indicating that for different precipitation events, the perturbation magnitude constraint must be carefully selected. All the findings above lay a foundation for the design of nonlinear model perturbation methods for future CAEPSs.  相似文献   

Change in Precipitation over the Tibetan Plateau Projected by Weighted CMIP6 Models     

Yin ZHAO  Tianjun ZHOU  Wenxia ZHANG  Jian LI 《大气科学进展》2022,39(7):1133-1150

Precipitation over the Tibetan Plateau (TP) is important to local and downstream ecosystems. Based on a weighting method considering model skill and independence, changes in the TP precipitation for near-term (2021–40), mid-term (2041–60) and long-term (2081–2100) under shared socio-economic pathways (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSSP3-7.0, SSP5-8.5) are projected with 27 models from the latest Sixth Phase of the Couple Model Intercomparison Project. The annual mean precipitation is projected to increase by 7.4%–21.6% under five SSPs with a stronger change in the northern TP by the end of the 21st century relative to the present climatology. Changes in the TP precipitation at seasonal scales show a similar moistening trend to that of annual mean precipitation, except for the drying trend in winter precipitation along the southern edges of the TP. Weighting generally suggests a slightly stronger increase in TP precipitation with reduced model uncertainty compared to equally-weighted projections. The effect of weighting exhibits spatial and seasonal differences. Seasonally, weighting leads to a prevailing enhancement of increase in spring precipitation over the TP. Spatially, the influence of weighting is more remarkable over the northwestern TP regarding the annual, summer and autumn precipitation. Differences between weighted and original MMEs can give us more confidence in a stronger increase in precipitation over the TP, especially for the season of spring and the region of the northwestern TP, which requires additional attention in decision making.  相似文献   

Impacts of New Implementing Strategies for Surface and Model Physics Perturbations in TREPS on Forecasts of Landfalling Tropical Cyclones     

Xubin ZHANG 《大气科学进展》2022,39(11):1833-1858

To improve the ensemble prediction system of the tropical regional atmosphere model for the South China Sea (TREPS) in predicting landfalling tropical cyclones (TCs), the impacts of three new implementing strategies for surface and model physics perturbations in TREPS were evaluated for 19 TCs making landfall in China during 2014–16. For sea surface temperature (SST) perturbations, spatially uncorrelated random perturbations were replaced with spatially correlated ones. The multiplier f, which is used to form perturbed tendency in the Stochastically Perturbed Parameterization Tendency (SPPT) scheme, was inflated in regions with evident convective activity (f-inflated SPPT). Lastly, the Stochastically Perturbed Parameterization (SPP) scheme with 14 perturbed parameters selected from the planetary boundary layer, surface layer, microphysics, and cumulus convection parameterizations was added. Overall, all these methods improved forecasts more significantly for non-intensifying than intensifying TCs. Compared with f-inflated SPPT, the spatially correlated SST perturbations generally showed comparable performance but were more (less) skillful for intensifying (non-intensifying) TCs. The advantages of the spatially correlated SST perturbations and f-inflated SPPT were mainly present in the deterministic guidance for both TC track and wind and in the probabilistic guidance for reliability of wind. For intensifying TCs, adding SPP led to mixed impacts with significant improvements in probability-matched mean of modest winds and in probabilistic forecasts of rainfall; while for non-intensifying TCs, adding SPP frequently led to positive impacts on the deterministic guidance for track, intensity, strong winds, and moderate rainfall and on the probabilistic guidance for wind and discrimination of rainfall.  相似文献   

Identification of Convective and Stratiform Clouds Based on the Improved DBSCAN Clustering Algorithm     

Yuanyuan ZUO  Zhiqun HU  Shujie YUAN  Jiafeng ZHENG  Xiaoyan YIN  Boyong LI 《大气科学进展》2022,39(12):2203-2212

A convective and stratiform cloud classification method for weather radar is proposed based on the density-based spatial clustering of applications with noise (DBSCAN) algorithm. To identify convective and stratiform clouds in different developmental phases, two-dimensional (2D) and three-dimensional (3D) models are proposed by applying reflectivity factors at 0.5° and at 0.5°, 1.5°, and 2.4° elevation angles, respectively. According to the thresholds of the algorithm, which include echo intensity, the echo top height of 35 dBZ (ET), density threshold, and ε neighborhood, cloud clusters can be marked into four types: deep-convective cloud (DCC), shallow-convective cloud (SCC), hybrid convective-stratiform cloud (HCS), and stratiform cloud (SFC) types. Each cloud cluster type is further identified as a core area and boundary area, which can provide more abundant cloud structure information. The algorithm is verified using the volume scan data observed with new-generation S-band weather radars in Nanjing, Xuzhou, and Qingdao. The results show that cloud clusters can be intuitively identified as core and boundary points, which change in area continuously during the process of convective evolution, by the improved DBSCAN algorithm. Therefore, the occurrence and disappearance of convective weather can be estimated in advance by observing the changes of the classification. Because density thresholds are different and multiple elevations are utilized in the 3D model, the identified echo types and areas are dissimilar between the 2D and 3D models. The 3D model identifies larger convective and stratiform clouds than the 2D model. However, the developing convective clouds of small areas at lower heights cannot be identified with the 3D model because they are covered by thick stratiform clouds. In addition, the 3D model can avoid the influence of the melting layer and better suggest convective clouds in the developmental stage.  相似文献   

盛夏苏北地区一次飑线过程的数值模拟研究     

朱娟  张立凤  张铭 《湖北气象》2022,41(1):15-23

对一次盛夏苏北飑线过程采用区域三重嵌套WRF模式进行了数值模拟和结果分析,给出了飑线径向剖面的概念模型图。结果表明:模拟的飑线与实际飑线非常接近,两者具有相同的性质和特点,利用模拟的线状强降水带及其降水强度来确定模拟飑线的位置和强度是可行的。飑线成熟期,飑线处存在强辐合区、强垂直上升运动区以及假相当位温的高值区,三者均呈柱状向上伸展;飑线前方(飑线移动的方向),低层有位温高值的入流,为飑线带入大量水汽和能量,后方低层有浅薄入流;飑线过境时地面风向发生急剧变化;飑线中层位温值大致不变呈中性层结,这与对流凝结潜热释放有关。该飑线过程可大体看成是假绝热过程,并具有重力波的非平衡性质,其生成演变中存在多尺度的相互作用。  相似文献   

华南复杂地形下GRAPES_Meso3km对流尺度模式前汛期精细化降水预报评估          下载免费PDF全文

陈静  庞波  吴政秋  陈法敬  陈雨潇  刘昕  马雅楠 《大气科学学报》2022,45(1):99-111

为深入认识GRAPES_Meso(Global/Regional Assimilation and Prediction System)3 km对流尺度区域模式对华南前汛期精细化降水的预报性能,为模式改进及业务应用提供参考依据,利用广东省86个站点逐小时观测降水资料和国家气象信息中心多源融合降水资料,针对广东省复杂地形特点,结合距海岸线的远近及站点地形特点,将86个站划分为沿海东部、沿海西部和内陆地区三个子区域,采用二分类降水预报检验方法,定量评估了2020年5月18日—6月18日华南前汛期降水预报效果。结果显示,GRAPES_Meso 3 km模式精细化降水预报技巧受广东复杂地形影响较大,广东沿海东部和内陆地区24 h时累积降水的小雨、中雨、大雨量级预报成功指数(Threat Score,TS)、公平成功指数(Equitable Threat Score,ETS)评分高于沿海西部地区,尽管暴雨预报评分具有此相同特征,但三个子区域的暴雨预报评分总体较低;从3 h累积降水预报评分看,沿海东部、沿海西部及内陆地区等三个子区域存在明显的日变化特征,但是沿海东部及西部与内陆地区表现有所不同,沿海东部和西部降水预报评分夜间较低(预报偏差偏高),白天相对较高(预报偏差偏低),而内陆地区则是夜间较高(预报偏差偏低),白天相对较低(预报偏差偏高)。沿海西部预报评分相对较低的原因是由于检验时段内广东地区存在一个弱的风切变,而沿海西部大部分地区正好处于切变线南侧的温度高值区控制,但模式模拟该区域的日平均温度较实况偏低,导致沿海西部模式预报降水空报较多,降低其降水预报技巧。  相似文献   

基于智能物联网技术的天津城市积水监测预警系统     

侯天宇  梁好  霍凯  赵敏  陈子煊  张春莉  苑超 《气象研究与应用》2021,(1):85-89

通过智能物联网技术实时获取积水监测实况数据,利用天津市气象精细化格点预报产品和城市自动雨量观测站实况数据,以机器学习、神经网络模型和天津市城市内涝风险等级划分原理为基础,研究基于用户实时位置的城市内涝预报预警技术,研发天津市城市自动化积水监测预警系统。结果表明,该系统具备一定的城市内涝风险监测预警预报能力,并在2018—2020年多次重大天气过程中应用,积水深度预报结果与监测结果基本一致,应用数据表明验证结果良好,系统可以为政府防灾减灾决策、指挥调度提供精准、及时的气象数据支撑。  相似文献   

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

马蕴琦  任福民  贾莉  丁晨晨 《热带气象学报(英文版)》2022,28(2):139-153

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.  相似文献   

天山南坡暖季暴雨过程的水汽来源及输送特征     

庄晓翠  李博渊  赵江伟  李建刚  张林梅 《干旱气象》2022,(1)

利用1981—2020年5—9月天山南坡16个气象站逐日降水资料和NCEP/NCAR GDAS再分析资料,分析天山南坡暖季暴雨过程的环流形势,并采用HYSPLIT模式,模拟追踪水汽源地及输送特征。结果表明:天山南坡暖季暴雨主要发生在南亚高压双体型、500 hPa以上西南急流(气流)、700 hPa切变辐合以及天山地形辐合抬升的重叠区域。水汽主要源自中亚、大西洋及其沿岸、地中海和黑海及其附近,经TKAP(塔吉克斯坦、吉尔吉斯坦、阿富汗东北部、巴基斯坦北部和印度西北部)、南疆、北疆关键区,分别从偏西、偏南、偏北通道输入暴雨区,700 hPa以上偏西通道、以下偏北通道占主导地位,且贡献最大的是南疆关键区。源自中亚的水汽主要输送至暴雨区700 hPa及以下,对暴雨的贡献较大,且沿途损失较大;源自大西洋及其沿岸、地中海和黑海及其附近的水汽主要输送至暴雨区700 hPa以上,对暴雨的贡献较小。另外,中低层还存在源自北疆、南疆、北美洲东部、蒙古的水汽。基于上述特征,建立了天山南坡暖季暴雨过程水汽三维精细化结构模型。  相似文献   

天山南坡暖季暴雨过程的水汽来源及输送特征     

庄晓翠  李博渊  赵江伟  李建刚  张林梅 《干旱气象》2022,(1)

利用1981—2020年5—9月天山南坡16个气象站逐日降水资料和NCEP/NCAR GDAS再分析资料,分析天山南坡暖季暴雨过程的环流形势,并采用HYSPLIT模式,模拟追踪水汽源地及输送特征。结果表明:天山南坡暖季暴雨主要发生在南亚高压双体型、500 hPa以上西南急流(气流)、700 hPa切变辐合以及天山地形辐合抬升的重叠区域。水汽主要源自中亚、大西洋及其沿岸、地中海和黑海及其附近,经TKAP(塔吉克斯坦、吉尔吉斯坦、阿富汗东北部、巴基斯坦北部和印度西北部)、南疆、北疆关键区,分别从偏西、偏南、偏北通道输入暴雨区,700 hPa以上偏西通道、以下偏北通道占主导地位,且贡献最大的是南疆关键区。源自中亚的水汽主要输送至暴雨区700 hPa及以下,对暴雨的贡献较大,且沿途损失较大;源自大西洋及其沿岸、地中海和黑海及其附近的水汽主要输送至暴雨区700 hPa以上,对暴雨的贡献较小。另外,中低层还存在源自北疆、南疆、北美洲东部、蒙古的水汽。基于上述特征,建立了天山南坡暖季暴雨过程水汽三维精细化结构模型。  相似文献