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In the present study, the performances of the NWP models on two heavy rainfalls on 20 July and 22 August 2021 over Henan Province were investigated. The impacts of the water vapor transport to the extreme rainfall were further discussed. The results showed that the regional model system in the Guangzhou Meteorological Service generally showed high scores on the extreme rainfall over Henan. The maximum 24h accumulative rainfall by the 24h forecasts by the CMA-GD reached 556 mm over Henan Province. The 24-h and 48-h Threat Score (TS) of heavy rainfall reached 0.56 and 0.64. The comparisons of the Fraction Skill Score (FSS) verifications of the heavy rainfall by CMA-GD and CMA-TRAMS at the radium of 40km reached 0.96 and 0.87. The water vapor transport to the extreme rainfall showed that the vertically integrated water vapor transport (IVT) of the whole layer before the occurrence of the heavy rainfall exhibited a double-eyes distribution in case 7 · 20. The north eye over Henan reached the same magnitude of IVT as the typhoon eye (Cempaka) over south China. The IVT over the lower troposphere (<500 hPa) showed an overwhelming magnitude than the upper level, especially in the planetary boundary layer (<700 hPa). More practical technical needs to be developed to improve its performances on the forecasting of extreme rainfall, as well as more experiments need to be conducted to examine the effects of the specific terrain and physical schemes on the extreme rainfall. 相似文献
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This study assesses the predictive capabilities of the CMA-GD model for wind speed prediction in two wind farms located in Hubei Province, China. The observed wind speeds at the height of 70m in wind turbines of two wind farms in Suizhou serve as the actual observation data for comparison and testing. At the same time, the wind speed predicted by the EC model is also included for comparative analysis. The results indicate that the CMA-GD model performs better than the EC model in Wind Farm A. Th... 相似文献
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By deriving the discrete equation of the parameterized equation for the New Medium-Range Forecast (NMRF) boundary layer scheme in the GRAPES model, the adjusted discrete equation for temperature is obviously different from the original equation under the background of hydrostatic equilibrium and adiabatic hypothesis. In the present research, three discrete equations for temperature in the NMRF boundary layer scheme are applied, namely the original (hereafter NMRF), the adjustment (hereafter NMRF-gocp), and the one in the YSU boundary-layer scheme (hereafter NMRF-TZ). The results show that the deviations of height, temperature, U and V wind in the boundary layer in the NMRF-gocp and NMRF-TZ experiments are smaller than those in the NMRF experiment and the deviations in the NMRF-gocp experiment are the smallest. The deviations of humidity are complex for the different forecasting lead time in the three experiments. Moreover, there are obvious diurnal variations of deviations from these variables, where the diurnal variations of deviations from height and temperature are similar and those from U and V wind are also similar. However, the diurnal variation of humidity is relatively complicated. The root means square errors of 2m temperature (T2m) and 10m speed (V10m) from the three experiments show that the error of NMRF-gocp is the smallest and that of NMRF is the biggest. There is also a diurnal variation of T2m and V10m, where T2m has double peaks and V10m has only one peak. Comparison of the discrete equations between NMRF and NMRF-gocp experiments shows that the deviation of temperature is likely to be caused by the calculation of vertical eddy diffusive coefficients of heating, which also leads to the deviations of other elements. 相似文献
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利用2020年6月1日—2022年5月31日CMA GD模式2 m气温预报产品（预报时效为13—36 h）和同期江西省智能网格预报区域内地面站气温观测资料,计算气温预报准确率、平均误差和均方根误差,并统计分析其时空分布特征。结果表明： 1）模式预报准确率在不同月份、起报时次存在差异,暖季总体较高,冷季总体较低;暖季08时起报产品的月准确率总体高于20时,冷季反之;秋、冬季旬准确率分布更离散。模式预报产品其准确率明显低于中央气象台和江西省气象台订正产品,需订正后使用。08时起报产品对寒潮的预报效果优于20时。2）气温预报年误差分布存在日变化,最大值出现在08时,最小值出现在15时;年均方根误差峰值出现在15时和06时,白天大于夜间。3）冬季平均误差多为正值,夏季为负值,春、秋季平均误差大小界于冬、夏季之间;白天时段夏季均方根误差最大,夜间时段冬季最大。4）气温预报年误差地理分布特征明显,平原地区预报值偏低,年均方根误差最小;丘陵和山区22 h时效预报值偏高,31 h时效偏低;高山站预报值偏高,年均方根误差最大。丘陵地区负误差最大,平原地区最小;山区正误差最大。 相似文献
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地形对暖区暴雨的发生发展有着重要影响。以粤北一次暖区暴雨为例,从大尺度背景、中尺度特征及预报难点等方面分析了地形的作用,并利用CMA-GD模式进行了地形敏感性试验。结果表明:此次暴雨在副高与西风槽之间的双低空急流下发生,南岭地形对低空急流的动力作用、对θse舌和水汽的阻滞拦截作用,为暴雨出现在粤北创造有利条件;地形热力作用下产生的中尺度辐合线是对流触发的机制。敏感性试验显示南岭地形对暖区暴雨的落区影响显著,降水落区随南岭地形升高(降低)而往南(北)偏移。西南急流在经过南岭时,低层风速、散度、温度以及垂直速度都会随地形改变而发生明显变化。当南岭地形高度降低时,正面阻挡和摩擦作用减弱,急流、辐合及上升运动区向北推进到西风槽附近,导致雨区往北偏移;南岭地形高度升高时,地形阻挡和摩擦作用增强,辐合及上升运动区被阻隔在南岭南侧,暖区对流提前触发,雨区发生在粤北。可见,此次暴雨过程主要来自大尺度环流背景的影响,但其落区与南岭地形密切相关。 相似文献
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基于CMA-GD模式预报数据,利用多神经网络的动态权重集成方法,开展了贵州省温度预报订正研究,最终获得本地化温度预报订正产品。结果表明：(1) 在对历史数据检验评估的基础上,利用多种神经网络方法可有效降低模式系统误差,通过BP、BP_GA、WAVENN、GRNN、LSTM等神经网络订正,2020年贵州省0～72 h预报时效的温度平均绝对误差较模式降低0.01～0.17 ℃;(2) 考虑到不同神经网络订正结果的差异性,采用动态权重方案对订正结果进行优势集成可显著提升预报可靠性。经集成后的温度预报效果优于模式直接输出和各神经网络订正结果,2020年贵州省0～72 h预报时效的温度平均绝对误差较模式降低14.93%,预报准确率提升8.24%。此外,动态权重集成后的订正结果还表现出较好的稳定性。基于该方法形成的本地化客观预报订正产品可为提升贵州复杂地形下温度预报质量以及精细化预报服务水平提供参考依据。 相似文献
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使用CMA-GD模式及云分析系统,引入云南C波段多普勒雷达反射率因子资料,对2019年7月9日过程进行模拟试验,分析引入反射率资料对模式初始场和降水过程预报的影响。（1）引入反射率后,云中和底部的云量有所增加。水汽在900~200 hPa有大范围增加,能有效地调整降水区域的水汽分布。对模式顶层温度的调整较大,而对风场的影响较小。（2）引入反射率后,对3 h内降水强度及落区有较大改善,4~6 h的预报有所改善,7 h以后改善不明显。（3）引入反射率资料后,1~4 h大气可降水量增量较明显,5~9 h增量较前4 h明显减小。（4）在河口上空云水和水汽在950~400 hPa增加,霰、云冰和云雪在600~400 hPa增加,雨滴在1 000~500 hPa增加。水凝物增加,有利于河口站降水的发生。 相似文献
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基于2019年8月至2020年7月华南区域模式（CMA-GD）预报和湖南97个国家站2m温度实况,开展了模式温度预报检验和逐步回归订正技术研究。结果表明,华南区域模式2m温度预报与实况变化趋势基本一致,预报偏差具有明显日变化,白天准确率下降、夜间升高,随着预报时效的延长,偏差增大;夏半年预报偏差大于冬半年;湘西预报效果优于湘东;00时起报的2m温度预报优于12时起报。基于华南区域模式预报产品,区分起报时次和季节的2m温度预报逐步回归订正预报效果较好,订正后预报相对于模式预报误差下降、准确率提高,有明显正技巧,对12时起报的模式预报效果改善更大,不同站点订正效果略有差异,对预报误差较大站点,订正效果明显。 相似文献
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FSS-based Evaluation on Monsoon Precipitation Forecasts in South China from Regional Models with Different Resolution 
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下载免费PDF全文 This study evaluated the forecast skill of CMA-GD 3 km and CMA-GD 1 km with hourly Rapid Update Cycle (RUC) for five monsoon precipitation events in South China from 2018 to 2020, using the fraction skill score (FSS) of the neighborhood spatial verification method. The results revealed that, among the 24-lead-hour forecasts in CMA-GD 3 km, the FSS for the 0.1 mm precipitation threshold increased linearly with the lead time from 3 to 1 hour, while there was no significant improvement in other lead times. For the 5 mm precipitation threshold, the forecast skill was highest for the latest 1-hour lead time, while the FSS showed slight variation between lead times of 24 hours and 8 hours. The FSS for 10 mm and 20 mm precipitation thresholds were similar to that of 5 mm, with the difference that the best score occurred at the 2-hour lead time. Among the 6-lead-hour forecasts in CMA-GD 1 km, the forecasts of the latest 1-hour lead time were the best choices for four precipitation thresholds. When comparing CMA-GD 3 km and CMA-GD 1 km, it was found that CMA-GD 3 km had better skill for forecasts of 0.1 mm and 5 mm precipitation at 2-hour and 1-hour lead times, while CMA-GD 1 km had better skill for all other forecasts, including the forecast of 20 mm precipitation nearly all lead hours (including 3- to 6-hour, and 1-hour lead times). The results suggest that the increased resolution of the model may be beneficial for precipitation forecasts in South China, especially for short-duration heavy precipitation over a longer lead hours. However, the limited sample size of this study calls for further evaluation using more cases to validate the results′ generality. 相似文献
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