A radar-based verification of precipitation forecast for local convective storms

Local flash flood storms with a rapid hydrological response are a real challenge for quantitative precipitation forecasting (QPF). It is relevant to assess space domains, to which the QPF approaches are applicable. In this paper an attempt is made to evaluate the forecasting capability of a high-resolution numerical weather prediction (NWP) model by means of area-related QPF verification. The results presented concern two local convective events, which occurred in the Czech Republic (CR) on 13 and 15 July 2002 and caused local flash floods. We used the LM COSMO model (Lokall Model of the COSMO consortium) adapted to the horizontal resolution of 2.8 km over a model domain covering the CR. The 18 h forecast of convective precipitation was verified by using radar rainfall totals adjusted to the measured rain gauge data. The grid point-related root mean square error (RMSE) value was calculated over a square around the grid point under the assumption that rainfall values were randomly distributed within the square. The forecast accuracy was characterized by the mean RMSE over the whole verification domain. We attempt to show a dependence of both the RMSE field and the mean RMSE on the square size. The importance of a suitable merger between the radar and rain gauge datasets is demonstrated by a comparison between the verification results obtained with and without the gauge adjustment. The application of verification procedure demonstrates uncertainties in the precipitation forecasts. The model was integrated with initial conditions shifted by 0.5° distances. The four verifications, corresponding to the shifts in the four directions, show differences in the resulting QPF, which depend on the size of verification area and on the direction of the shift.     

GRAPES模式对长江流域天气预报的检验分析

GRAPES是中国新一代数值天气预报模式。使用GRAPES中尺度模式产品和常规观测资料,分析检验了2005、2006年汛期发生在长江流域的11次主要降水天气过程,得到:GRAPES模式对于长江流域的预报,无论是降水、天气形势还是物理量都有比较强的预报能力;GRAPES模式对级别较大的降水预报容易出现漏报,而不易出现空报,对于10mm以下的雨区预报比较准确,而对于大于50mm的雨区预报,尤其是大于100mm的降水中心存在较大的偏差;对于西太平洋副热带高压的预报比实际情况偏南、偏东;对于水汽通量散度的预报与实际情况比较吻合。     

Intercomparisons of land-surface parameterizations coupled to a limited area forecast model

The goal of the Project for Intercomparison of Land-surface Parameterization Schemes (PILPS) is to improve the understanding of the interactions between the atmosphere and the continental surface in climate and weather forecast models. In PILPS Phase 4(b), selected schemes are coupled to the Limited Area Prediction System (LAPS) developed by the Australian Bureau of Meteorology. To facilitate the comparison of PILPS schemes' behavior within LAPS, a single mode of coupling is selected: explicit coupling. This type of coupling is more flexible and avoids most of the problems raised when interchanging the surface schemes. Exploratory tests are conducted. Initially, experiments are run in which the land-surface schemes use the same parameters as in their original host models. Then, in other runs, the most important surface parameters are set constant in an attempt to reduce the scatter amongst the schemes' results. In order to understand the impact of initialisation of soil moisture on the schemes' results some extreme cases (wet and dry) are performed. The partitioning between surface fluxes is studied as well as the soil moisture budget. Both regional and local results are analysed. Sensitivity between LSS is found in the precipitation field with rainfall over the Australian continent altering by about 20%, but no significant change is found in the net radiation. The scatter in the surface energy fluxes amongst the schemes is large (up to 300 W m⁻² locally, during the daytime peak) but is seldom affected by the choice of surface parameters. The dynamical range of flux partitioning between extremely dry and wet initialisation varies strongly amongst the schemes. Some major shortcoming with the BUCKET approach are seen in the re-evaporation of convective precipitation over dry land, in the very large evaporation from wet surfaces and the diurnal cycle of surface temperature.     

人工智能在飞机颠簸预报中的应用进展及未来趋势展望

飞机颠簸对飞机运行安全及旅客舒适度具有很大危害,提高飞机颠簸的预报准确率对于减轻人员伤害和财产损失具有重要意义,且一直是航空气象研究的重点领域。随着观测手段的丰富和科学技术的进步,飞机颠簸预报也取得了长足发展。本文首先从定性预报和定量预报的角度对国内外飞机颠簸预报的主要方法,特别是人工智能(AI)方法在其中的最新应用进行了综述。在此基础上,归纳总结出AI用于飞机湍流预报存在的主要问题和未来的重点研究方向：1)飞机实况数据的开放共享以及多源湍流数据的融合构建问题;2)基于人工智能构建飞机颠簸预报模型的可解释性及物理机制问题;3)基于人工智能构建飞机颠簸的集合预报问题。最后,提出了气象领域未来第三代人工智能的发展思路。     

业务模式晴雨预报能力分析及其改进方法研究

以欧洲中心全球预报模式和中国华南区域中尺度模式(GZ 3 km)为例分析了2019年中国南方逐日晴雨预报的情况,并讨论模式晴雨预报的性能。借助TS检验评估方法,在与简单外推预报等的比较中,发现模式雨量预报特点及模式晴雨预报的统计规律,如两个模式同时预报晴天,或者模式预报有雨且降水量大于某阈值等情况,其预报准确率非常高;而对于两个模式预报不一致,或模式预报有雨且雨量较小等情况,则存在较大不确定性。基于上述研究,提出利用模式预报改进观测外推和利用观测与模式的频率匹配改进模式预报等方法。     

秦皇岛地区雾天气气候特征及预报

随着交通线路的快速发展,雾对交通运输的影响越来越大,浓雾天气常常引发交通事故,给人民的生命财产造成严重损失,危害性极大.应用秦皇岛1957-2006年"气表-1"资料,统计分析秦皇岛内陆、沿海地区雾天气时空分布特征,返查1981-2000年历史天气图,得出本地区出现雾的主要天气类型,筛选出影响雾的主要天气要素,建立MOS预报方程,为雾预报及临近预警信号的发布、解除提供有利依据,达到监测、预报之目的.     

水库汛期限制水位控制理论与观念的更新探讨

传统的水库汛限水位的控制,只利用了洪水的统计信息,使水库在汛期要时刻预防设计与校核洪水事件的发生,致使一些水库在汛期不敢蓄水而汛后又无水可蓄,造成洪水资源的浪费。提出水库汛限水位动态控制的新理念及其综合推理模式,适应当前预报技术的发展水平,考虑降雨径流洪水预报与一定时间内的短期降雨预报,排除不可能发生的洪水事件,预报可能发生的洪水,实施水库汛限水位的动态控制。但预报不可避免地存在误差,当小概率预报误差事件发生时,仍可采取弥补措施以确保大坝的防洪安全。     

2002年6月13日重庆区域大暴雨分析

通过对重庆西部“6 1 3”区域大暴雨的分析 ,发现此次天气过程是一次典型的高原涡与西南涡耦合 ,结合地面弱冷空气条件下产生的 ,同时对ECMWF和T2 1 3数值预报产品进行了简要的分析 ,发现ECMWF和T2 1 3的形势预报能力都比较好 ,但T2 1 3的部分物理量要素和降水量预报能力还有待提高。     

长江中下游旱涝中期预报方法及其业务应用

介绍了双层多因子综合相似的长江中下游旱涝中期预报模型。该模型引入了具有明确动力学和热力学意义的地转西风动量经向输送和经向温度梯度诊断量，同时强调了西太平洋副热带高压对长江中下游夏季降水的关键作用，并考虑了对流层中、低层500hPa高度和850hPa温度的大尺度环流背景场。与过去业务应用的单层相似预报模型相比较，不仅物理意义和天气学含义明确，而且更符合对具有复杂动力和热力机制的降水预报的考虑。5年的预报试验和业务应用结果表明，该方法对长江中下游地区旱涝的中期趋势预报有较好的预报能力。     

煤矿水害多源信息预测方法研究

基于MAPGIS平台,用Visual C++对其进行二次开发,研制了煤矿水害多源信息预测系统.通过对地震、电法、水文地质等多源数据进行处理后,在MAPGIS系统下进行成图、配准和空间定量分析,建立了预测模型.用该系统对煤矿实际资料进行了处理,结果表明其预测结果较传统方法更为准确.