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Developing a Hail and Wind Damage Swath Event Database from Daily MODIS True Color Imagery and Storm Reports for Impact Analysis and Applications 从每日MODIS真彩色图像和风暴报告中开发冰雹和风力损害事件数据库,用于影响分析和应用
IF 2.9 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2023-06-23 DOI: 10.1175/waf-d-22-0210.1
J. Bell, Emily F. Wisinski, A. Molthan, C. Schultz, Emma Gilligan, Kaylee G. Sharp
Hail and damaging winds are two threats associated with intense and severe thunderstorms that traverse the Midwest and Great Plains during the primary growing season. In certain severe thunderstorm events, large swaths of agricultural crops are impacted, allowing the damage to be viewed from multiple satellite remote sensing platforms. Previous studies have focused on analyzing individual hail and wind damage swaths (HWDSs) using satellite remote sensing, but these swaths have never been officially archived or documented. This lack of documentation has made it difficult to analyze the spatial extent and temporal frequency of HWDSs from year to year. This study utilizes daily true color imagery from MODIS aboard NASA’s Terra and Aqua satellites and daily local storm reports from the Storm Prediction Center to build a database of HWDSs occurring in the months of May through August, for years 2000 through 2020. This database identified 1,646 HWDSs in 12 states throughout the Midwest and Great Plains, confirmed through a combination of archived severe weather warnings, radar information, and official storm reports. For each entry in the HWDS database, a geospatial outline is provided along with the most likely date of first visible damage from MODIS imagery as well as the physical characteristics and time of occurrence estimated from available warnings. This study also provides a summary of the radar characteristics for a portion of the database. This database will further the understanding of severe weather damage by hail and wind to agriculture to help understand the frequency of these events and assist in mapping the impacted areas.
冰雹和破坏性大风是在主要生长季节横穿中西部和大平原的强烈和严重雷暴的两大威胁。在某些严重的雷暴事件中,大片农作物受到影响,从而可以从多个卫星遥感平台上观察到破坏情况。以前的研究主要集中在使用卫星遥感分析单个冰雹和风力损害区域(hwds),但这些区域从未被正式存档或记录。由于缺乏文献资料,很难分析每年hwds的空间范围和时间频率。本研究利用美国宇航局Terra和Aqua卫星上的MODIS每日真彩图像,以及风暴预测中心的每日本地风暴报告,建立了2000年至2020年5月至8月发生的hwds数据库。该数据库通过存档的恶劣天气预警、雷达信息和官方风暴报告,在中西部和大平原的12个州确定了1,646个hwds。对于HWDS数据库中的每个条目,提供地理空间轮廓,以及MODIS图像中最可能出现第一次可见损害的日期,以及根据现有警告估计的物理特征和发生时间。本研究还提供了部分数据库的雷达特性摘要。该数据库将进一步了解冰雹和风对农业造成的严重天气损害,以帮助了解这些事件的频率,并协助绘制受影响地区的地图。
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引用次数: 0
Competing Forecast Verification: Using the Power-Divergence Statistic for Testing the Frequency of “Better” 竞争预测验证:用功率发散统计量检验“更好”的频率
IF 2.9 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2023-06-21 DOI: 10.1175/waf-d-22-0201.1
E. Gilleland, D. Muñoz‐Esparza, David D. Turner
When testing hypotheses about which of two competing models is better, say A and B, the difference is often not significant. An alternative, complementary approach, is to measure how often model A is better than model B regardless of how slight or large the difference. The hypothesis concerns whether or not the percentage of time that model A is better than model B is larger than 50%. One generalized test statistic that can be used is the power-divergence test, which encompasses many familiar goodness-of-fit test statistics, such as the loglikelihood-ratio and Pearson X2 tests. Theoretical results justify using the distribution for the entire family of test statistics, where k is the number of categories. However, these results assume that the underlying data are independent and identically distributed; which is often violated. Empirical results demonstrate that the reduction to two categories (i.e., model A is better than model B v. model B is better than A) results in a test that is reasonably robust to even severe departures from temporal independence, as well as contemporaneous correlation. The test is demonstrated on two different example verification sets: 6-h forecasts of eddy dissipation rate (m2/3s−1) from two versions of the Graphical Turbulence Guidence model and for 12-hour forecasts of 2-m temperature (°C) and 10-m wind speed (ms−1) from two versions of the High-Resolution Rapid Refresh model. The novelty of this paper is in demonstrating the utility of the power-divergence statistic in the face of temporally dependent data, as well as the emphasis on testing for the “frequency-of-better” alongside more traditional measures.
当测试关于两个相互竞争的模型中哪一个更好的假设时,比如A和B,差异通常并不显著。另一种补充的方法是测量模型A比模型B好多少次,而不管差异有多大。这个假设关注的是模型A优于模型B的时间百分比是否大于50%。可以使用的一种广义检验统计量是功率发散检验,它包含许多熟悉的拟合优度检验统计量,如对数似然比和皮尔逊X2检验。理论结果证明对整个检验统计量族使用分布是合理的,其中k是类别的数量。然而,这些结果假设底层数据是独立且均匀分布的;这是经常被违反的。实证结果表明,减少到两个类别(即,模型A比模型B好,模型B比模型A好)导致的测试对甚至严重偏离时间独立性以及同期相关性都相当稳健。该测试在两个不同的示例验证集上进行了演示:来自两个版本的图形湍流指导模型的6小时涡流耗散率(m2/3s−1)预报,以及来自两个版本的高分辨率快速刷新模型的12小时2米温度(°C)和10米风速(ms−1)预报。本文的新颖之处在于展示了功率散度统计在面对时间相关数据时的效用,以及强调测试“更好的频率”以及更传统的测量方法。
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引用次数: 0
Intensification of Hurricane Sally (2020) over the Mississippi River plume 飓风莎莉(2020)在密西西比河羽流上空增强
IF 2.9 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2023-06-16 DOI: 10.1175/waf-d-22-0191.1
Effy B John, K. Balaguru, L. Leung, G. Foltz, R. Hetland, S. Hagos
Tropical Cyclone (TC) Sally formed on September 11, 2020, traveled through the Gulf of Mexico (GMX), and intensified rapidly before making landfall on the Alabama coast as a devastating Category 2 TC with extensive coastal and inland flooding. In this study, using a combination of observations and idealized numerical model experiments, we demonstrate that the Mississippi River plume played a key role in the intensification of Sally near the northern Gulf coast. As the storm intensified and its translation slowed before landfall, sea surface cooling was reduced along its track, coincident with a pronounced increase in SSS. Further analysis reveals that TC Sally encountered a warm Loop Current eddy in the northern GMX close to the Mississippi River plume. Besides deepening the thermocline, the eddy advected low salinity Mississippi River plume water into the storm’s path. This resulted in the development of strong upper-ocean salinity stratification, with a shallow layer of fresh water lying above a deep, warm ‘barrier layer’. Consequently, TC-induced mixing and the associated sea surface cooling were reduced, aiding Sally’s intensification. These results suggest that the Mississippi River plume and freshwater advection by the Loop Current can play an important role in TC intensification near the US Gulf coast.
热带气旋莎莉于2020年9月11日形成,穿过墨西哥湾(GMX),并在登陆阿拉巴马州海岸之前迅速增强,形成毁灭性的2级热带气旋,沿海和内陆洪水泛滥。在这项研究中,我们结合观测和理想化的数值模型实验,证明了密西西比河羽流在墨西哥湾北部海岸附近萨利的增强中发挥了关键作用。随着风暴在登陆前增强,其平移速度减慢,其路径上的海面冷却减少,同时SSS显著增加。进一步的分析表明,TC Sally在靠近密西西比河羽流的GMX北部遇到了一个温暖的环流涡。除了加深温跃层外,涡流还将低盐度的密西西比河羽流引入风暴路径。这导致了强烈的上层海洋盐度分层的发展,浅层淡水位于深层温暖的“屏障层”之上。因此,TC引起的混合和相关的海面冷却减少,有助于Sally的强化。这些结果表明,密西西比河羽流和环流的淡水平流在美国墨西哥湾沿岸TC增强中起着重要作用。
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引用次数: 1
Advancing Tropical Cyclone Precipitation Forecast Verification Methods and Tools 热带气旋降水预报验证方法和工具的进展
IF 2.9 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2023-06-15 DOI: 10.1175/waf-d-23-0001.1
Kathryn M. Newman, B. Brown, John Halley Gotway, L. Bernardet, M. Biswas, T. Jensen, L. Nance
Tropical cyclone (TC) forecast verification techniques have traditionally focused on track and intensity, as these are some of the most important characteristics of TCs and are often the principle verification concerns of operational forecast centers. However, there is a growing need to verify other aspects of TCs as process-based validation techniques may be increasingly necessary for further track and intensity forecast improvements as well as improving communication of the broad impacts of TCs including inland flooding from precipitation. Here we present a set of TC-focused verification methods available via the Model Evaluation Tools (MET) ranging from traditional approaches, to the application of storm-centric coordinates and the use of feature-based verification of spatially-defined TC objects.Storm-relative verification using observed and forecast tracks can be useful for identifying model biases in precipitation accumulation in relation to the storm center. Using a storm-centric cylindrical coordinate system based on the radius of maximum wind adds additional storm-relative capabilities to regrid precipitation fields onto cylindrical or polar coordinates. This powerful process-based model diagnostic and verification technique provides a framework for improved understanding of feedbacks between forecast tracks, intensity, and precipitation distributions. Finally, object-based verification including land masking capabilities provides even more nuanced verification options. Precipitation objects of interest, either the central core of TCs or extended areas of rainfall after landfall, can be identified, matched to observations, and quickly aggregated to build meaningful spatial and summary verification statistics.
热带气旋预报验证技术传统上侧重于轨道和强度,因为这是热带气旋的一些最重要的特征,通常是业务预报中心的主要验证问题。然而,越来越需要验证tc的其他方面,因为基于过程的验证技术可能越来越需要进一步改进跟踪和强度预报,以及改善tc的广泛影响的交流,包括降水引起的内陆洪水。在这里,我们通过模型评估工具(MET)提供了一套以TC为中心的验证方法,从传统方法到以风暴为中心的坐标的应用,以及对空间定义的TC对象使用基于特征的验证。使用观测和预报路径的风暴相关验证对于识别与风暴中心有关的降水积累的模式偏差是有用的。使用基于最大风半径的以风暴为中心的柱坐标系统增加了额外的风暴相对能力,将降水场网格化到柱坐标或极坐标上。这种强大的基于过程的模型诊断和验证技术为改进对预报轨迹、强度和降水分布之间反馈的理解提供了一个框架。最后,基于对象的验证(包括陆地屏蔽功能)提供了更细致的验证选项。感兴趣的降水对象,无论是tc的中心核心还是登陆后降雨的扩展区域,都可以被识别,与观测相匹配,并快速汇总以建立有意义的空间和汇总验证统计。
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引用次数: 0
Assimilation of AMSU-A Surface-Sensitive Channels in CMA_GFS 4D-Var System over Land CMA_GFS 4D-Var系统对AMSU-A地表敏感通道的陆地同化
IF 2.9 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2023-06-14 DOI: 10.1175/waf-d-23-0032.1
Hongyi Xiao, Juan Li, Guiqing Liu, Liwen Wang, Yihong Bai
The assimilation of two surface-sensitive channels of the AMSU-A instruments onboard the NOAA-15/-18/-19 and MetOp-A/B satellites over land was achieved in the China Meteorological Administration Global Forecast System (CMA_GFS). The land surface emissivity was calculated by (1) the window channel retrieval method and (2) the Tool to Estimate Land Surface Emissivities at Microwave frequencies (TELSEM2). Quality controls for these satellite microwave observations over land were conducted. The predictors and regression coefficients used for oceanic satellite data were retained during the bias correction over land and found to perform well. Three batch experiments were implemented in CMA_GFS with 4D-Var: (1) assimilating only the default data, and adding the above data over land with land surface emissivity obtained from (2) TELSEM2 and (3) the window channel retrieval method. The results indicated that the window channel retrieval method can better reduce the departure between the observed and simulated brightness temperature. Over most land types, the positive impacts of this method exceed those of TELSEM2. Both TELSEM2 and the window channel retrieval method improve the humidity analysis near the ground, as well as the forecast capability globally, particularly in those regions where the land coverage is greater, such as in the Northern Hemisphere. The data utilization of the two surface-sensitive channels increase by 6% and 12%, respectively, and the additional data every six hours can cover most land, where there was no surface-sensitive data assimilated before. This study marks the beginning of near-surface channel assimilation over land in CMA_GFS and represents a breakthrough in the assimilation of other surface-sensitive channels in other satellite instruments.
在中国气象局全球预报系统(CMA_GFS)中实现了NOAA-15/-18/-19和MetOp-A/B卫星上AMSU-A仪器的两个地面敏感通道在陆地上的同化。地表发射率通过(1)窗口通道反演方法和(2)微波频率下地表发射率估算工具(TELSEM2)计算。对这些卫星在陆地上的微波观测进行了质量控制。用于海洋卫星数据的预测因子和回归系数在陆地偏差校正期间被保留,并被发现表现良好。在具有4D-Var的CMA_GFS中进行了三批实验:(1)仅同化默认数据,并将上述数据与从(2)TELSEM2和(3)窗口通道检索方法获得的陆地表面发射率相加。结果表明,窗口通道检索方法可以更好地减少观测亮度温度与模拟亮度温度之间的偏差。在大多数土地类型中,这种方法的积极影响超过了TELSEM2。TELSEM2和窗口通道检索方法都提高了地面附近的湿度分析以及全球预测能力,特别是在陆地覆盖率较高的地区,如北半球。两个地表敏感通道的数据利用率分别提高了6%和12%,每6小时的额外数据可以覆盖大部分土地,而这些土地以前没有同化的地表敏感数据。这项研究标志着CMA_GFS陆地近地表通道同化的开始,并代表着其他卫星仪器对其他地表敏感通道同化的突破。
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引用次数: 0
The quagmire of arrested development in tropical cyclones 热带气旋发展停滞的泥潭
IF 2.9 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2023-06-13 DOI: 10.1175/waf-d-22-0194.1
C. Slocum, J. Knaff
Forty-eight hour intensity forecasts for Hurricane Pamela (2021) from numerical weather prediction models, statistical–dynamical aids, and forecasters were a major forecast bust with Pamela making landfall as a minor rather than major hurricane. From the satellite presentation, Pamela exhibited a symmetric pattern referred to as central cold cover (CCC) in the subjective Dvorak intensity technique. Per the technique, the CCC pattern is accompanied by arrested development in intensity despite the seemingly favorable convective signature. To understand forecast uncertainty during occurrences, central cold cover frequency from 2011–2021 is documented. From these cases, composites of longwave infrared brightness temperatures from geostationary satellites for CCC cases are presented and the surrounding tropical cyclone large-scale environment is quantified and compared with other tropical cyclones at similar latitudes and intensities. These composites show that central cold cover has a consistent presentation, but varies in the preceding hours for storms that eventually intensify or weaken. And, the synoptic-scale environment surrounding the tropical cyclone thermodynamically supports the vigorous deep convection associated with CCC. Finally, intensity forecast errors from numerical weather prediction models and statistical–dynamical aids are examined in comparison to similar tropical cyclones. This work shows that guidance struggles during CCC cases with intensity errors from these models being in the lowest percentiles of performance, particularly for 24- and 36-h forecasts.
数值天气预测模型、统计-动力辅助工具和预报员对飓风帕梅拉(2021)48小时强度的预测是一个主要的预测失误,帕梅拉以小飓风而非大飓风的形式登陆。从卫星展示来看,帕梅拉在主观德沃夏克强度技术中表现出一种被称为中心冷覆盖(CCC)的对称模式。根据该技术,CCC模式伴随着强度的停滞发展,尽管有看似有利的对流特征。为了了解发生期间的预测不确定性,记录了2011-2021年的中心冷覆盖频率。根据这些情况,给出了CCC情况下地球静止卫星长波红外亮度温度的组合,并对周围热带气旋的大尺度环境进行了量化,并与类似纬度和强度的其他热带气旋进行了比较。这些复合物表明,中心冷覆盖具有一致的表现,但在风暴最终增强或减弱的前几个小时有所不同。热带气旋周围的天气尺度环境在热力学上支持了CCC产生的强烈深层对流。最后,将数值天气预测模型和统计动力辅助工具的强度预测误差与类似热带气旋进行了比较。这项工作表明,在CCC情况下,这些模型的强度误差处于最低的性能百分位数,特别是对于24小时和36小时的预测,指导很困难。
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引用次数: 0
The roles of chaos seeding and multiple perturbations in convection–permitting ensemble forecasting over southern China 混沌播种和多重扰动在华南对流集合预报中的作用
IF 2.9 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2023-06-06 DOI: 10.1175/waf-d-22-0177.1
Jingzhuo Wang, Jing Chen, Hongqi Li, Haile Xue, Zhizhen Xu
The roles of chaos seeding and multiple perturbations, including model perturbations and topographic perturbations, in convection-permitting ensemble forecasting, are assessed. Six comparison experiments were conducted for fourteen heavy rainfall events over southern China. Chaos seeding was run as a benchmark experiment to compare their effects to the intended perturbations. The results first reveal the chaos seeding phenomenon. That is, the tiny and local perturbations of the skin soil moisture propagate into the whole analysis domain within an hour and expand to every prognostic variables, and the perturbations derived from chaos seeding develop when moist convection is active. Secondly, the chaos seeding has the statistically significant differences from our intended perturbations for the ensemble spread magnitudes of precipitation and the spread-skill relationships and probabilistic forecast skills of dynamical variables. Additionally, for the probabilistic forecasts of precipitation, initial and lateral boundary perturbations and model perturbations can yield statistically larger FSS and AROC scores than chaos seeding; topographic perturbations can only improve FSS and AROC scores a little. The different performances may be related to the different degrees of the real dynamical influence of our intended perturbations. Finally, model perturbations can increase the ensemble spreads of precipitation, and improve FSS and AROC scores of precipitation and the consistency of middle- and low-level dynamical variables. However, the effects of topographic perturbations are small.
评估了混沌播种和多重扰动(包括模式扰动和地形扰动)在允许对流的集合预报中的作用。对中国南方14次强降雨事件进行了6次对比试验。混沌播种作为基准实验,将其效果与预期扰动进行比较。结果首次揭示了混沌播种现象。即表层土壤湿度的微小局部扰动在1小时内传播到整个分析域并扩展到每一个预测变量,混沌播种引起的扰动在湿对流活跃时产生。其次,混沌播种对降水的总体扩散强度、动力变量的扩散技能关系和概率预测技能与预期扰动具有统计学上的显著差异。此外,对于降水的概率预报,初始和横向边界扰动和模式扰动比混沌播种产生更大的FSS和AROC分数;地形扰动只能略微提高FSS和AROC分数。不同的性能可能与我们预期扰动的实际动态影响的不同程度有关。最后,模式扰动增加了降水的集合扩展,提高了降水的FSS和AROC分数以及中低层动力变量的一致性。然而,地形扰动的影响很小。
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引用次数: 2
Evaluating the precipitation biases over the western periphery of the Sichuan Basin by ECMWF operational forecast model ECMWF运行预报模型对四川盆地西缘降水偏误的评价
IF 2.9 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2023-06-05 DOI: 10.1175/waf-d-22-0218.1
Juan Li, Haoming Chen, Puxi Li, Xingwen Jiang
Based on the hourly merged precipitation product, the performance of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) in simulating the diurnal variations of precipitation during warm season over the western periphery of the SCB has been evaluated, and the underlying physical causes associated with the wet biases have also been investigated. The results show that the IFS well reproduces the spatial distributions of precipitation amount, frequency, intensity over the SCB, as well as their diurnal variations, but the simulated precipitation peaks earlier than the observation with notable wet biases over the western periphery of the SCB. In addition, the strong wet biases exhibit notable regional difference over the western periphery of the SCB. The simulated wet biases over the southwestern periphery of the SCB expanding westward to higher altitudes along the windward slope, with the maximum wet biases occurring at night. The westward expansion of the simulated stronger upward motions results in a westward shift of precipitation. However, the simulated precipitation over the northwestern periphery of the SCB have small difference in terms of the location, the overestimated precipitation is associated with the stronger atmospheric instability, resulting from the higher potential temperature and the larger specific humidity near the surface. The findings revealed in this study indicate that the ECMWF forecast shows distinct uncertainties over the different complex terrain, and thus offer a promising way forward for improvements of model physical processes.
基于逐时合并降水产品,对欧洲中期天气预报中心(ECMWF)综合预报系统(IFS)模拟南海西缘暖季降水日变化的性能进行了评价,并探讨了与湿偏相关的潜在物理原因。结果表明:IFS较好地模拟了南海地区降水数量、频率、强度的空间分布及其日变化特征,但模拟的降水峰值早于观测值,且南海西缘有明显的湿偏。此外,强湿偏在南海西缘表现出显著的区域差异。模拟的南海西南外围湿偏沿上风坡向西扩展至更高高度,最大湿偏发生在夜间。模拟的较强上升运动向西扩展导致降水向西移动。然而,南海西北外围的模拟降水在位置上差异不大,高估降水与大气不稳定性较强有关,这是由于近地面的位温较高和比湿较大造成的。研究结果表明,ECMWF对不同复杂地形的预报具有明显的不确定性,为改进模式物理过程提供了一条有希望的途径。
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引用次数: 0
Seasonal forecasting of precipitation, temperature, and snow mass over the western U.S. by combining ensemble post-processing with empirical ocean-atmosphere teleconnections 结合集合后处理和经验海洋-大气遥相关对美国西部降水、温度和雪量的季节预报
IF 2.9 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2023-06-02 DOI: 10.1175/waf-d-22-0099.1
W. Scheftic, X. Zeng, M. Brunke
Accurate and reliable seasonal forecasts are important for water and energy supply management. Recognizing the important role of snow water equivalent (SWE) for water management, here we include the seasonal forecast of SWE in addition to precipitation (P) and 2-m temperature (T2m) over hydrologically defined regions of the western U.S. A two-stage process is applied to seasonal predictions from two models (NCEP CFSv2 and ECMWF SEAS5) through 1) post-processing to remove biases in the mean, variance, and ensemble spread, and 2) further reducing the residual errors by linear regression using climate indices. The adjusted forecasts from the two models are combined to form a super-ensemble using weights based on their prior skill. The adjusted forecasts are consistently improved over raw model forecasts probabilistically for all variables and deterministically for SWE forecasts. Overall skill of the super-ensemble usually improves upon the skill of forecasts from individual models, however the percentage of seasons and regions with increased skill was approximately the same as those with decreased skill relative to the top performing post-processed individual model. Seasonal SWE has the highest prediction skill, followed by T2m, with P showing lower prediction skill. Persistence contributes strongly to the skill of SWE and moderately to the skill of T2m. Furthermore, a distinct seasonality in the skill is seen in SWE, with a higher skill from late spring through early summer.
准确可靠的季节性预测对水和能源供应管理非常重要。认识到雪水当量(SWE)在水资源管理中的重要作用,除了降水量(P)和2米温度(T2m)外,我们还包括了美国西部水文定义区域的SWE季节性预测。将两阶段过程应用于两个模型(NCEP CFSv2和ECMWF SEAS5)的季节性预测,通过1)后处理消除平均值偏差,方差和集合扩散,以及2)通过使用气候指数的线性回归进一步减少残差。将来自两个模型的调整后的预测组合起来,使用基于其先前技能的权重形成超级集合。调整后的预测在所有变量的概率和SWE预测的确定性方面都比原始模型预测持续改进。超级集合的总体技能通常会提高单个模型的预测技能,然而,相对于表现最好的后处理单个模型,技能提高的季节和地区的百分比与技能降低的季节和区域的百分比大致相同。季节SWE的预测能力最高,其次是T2m,P的预测能力较低。坚持对SWE的技能有很大的贡献,对T2m的技能有一定的贡献。此外,SWE的技能具有明显的季节性,从春末到夏初技能更高。
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引用次数: 0
Challenges in Numerical Weather Prediction of the 10 August 2020 Midwestern Derecho: Examples from the FV3-LAM 2020年8月10日中西部Derecho数值天气预报的挑战:来自FV3-LAM的例子
IF 2.9 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2023-06-01 DOI: 10.1175/waf-d-23-0019.1
W. Gallus, M. Harrold
A severe derecho impacted the Midwestern United States on 10 August 2020, causing over 12 billion dollars in damage, and producing peak winds estimated at 63 m s−1, with the worst impacts in Iowa. The event was not forecast well by operational forecasters, nor even by operational and quasi-operational convection-allowing models.In the present study, nine simulations are performed using the Limited Area Model version of the Finite-Volume-Cubed-Sphere model (FV3-LAM) with three horizontal grid spacings and two physics suites. In addition, when a prototype of the Rapid Refresh Forecast System (RRFS) physics is used, sensitivity tests are performed to examine the impact of using the Grell-Freitas (GF) convective scheme.Several unusual results are obtained. With both the RRFS (not using GF) and Global Forecast System (GFS) physics suites, simulations using relatively coarse 13 and 25 km horizontal grid spacing do a much better job of showing an organized convective system in Iowa during the daylight hours of 10 August than the 3-km grid spacing runs. In addition, the RRFS run with 25-km grid spacing becomes much worse when the GF convective scheme is used. The 3-km RRFS run that does not use the GF scheme develops spurious nocturnal convection the night before the derecho, removing instability and preventing the derecho from being simulated at all. When GF is used, the spurious storms are removed and an excellent forecast is obtained with an intense bowing echo, exceptionally strong cold pool, and roughly 50 m s−1 surface wind gusts.
2020年8月10日,一场严重的飓风袭击了美国中西部,造成超过120亿美元的损失,峰值风速估计为每小时63米,其中爱荷华州受影响最严重。可操作的预报员甚至可操作的和准可操作的对流模式都不能很好地预测这次事件。在本研究中,使用有限体积立方球模型(FV3-LAM)的有限区域模型版本进行了九次模拟,其中有三个水平网格间隔和两个物理套件。此外,当使用快速刷新预报系统(RRFS)物理原型时,进行了灵敏度测试,以检查使用Grell-Freitas (GF)对流方案的影响。得到了几个不同寻常的结果。使用RRFS(不使用GF)和全球预报系统(GFS)物理套件,使用相对粗糙的13公里和25公里水平网格间距的模拟比3公里网格间距的模拟更能显示8月10日白天爱荷华州有组织的对流系统。此外,在格网间距为25km时,采用GF对流方案时,RRFS的运行变得更差。不使用GF方案的3公里RRFS运行在derecho前一晚产生了虚假的夜间对流,消除了不稳定性,从而完全阻止了对derecho的模拟。当使用GF时,去除了虚假的风暴,并获得了强烈的弯曲回波,异常强烈的冷池和大约50 ms - 1的地面阵风的良好预报。
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引用次数: 1
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Weather and Forecasting
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