基于频率匹配法和最优TS评分法的降水预报订正效果对比

利用2020年1月1日—2023年1月2日ECMWF、NCEP模式降水预报资料和眉山地区降水观测资料,采用频率匹配法（Frequency Matching Method,FM）、最优TS评分法（Optimal Threat Score,OTS）对ECMWF和NCEP的模式降水预报进行订正,对比检验评分和预报个例,并验证两种方法的适用性。结果表明：FM、OTS订正明显改善了小雨空报和暴雨漏报,提高了晴雨预报准确率、小雨ETS评分、暴雨TS评分,且OTS优于FM;FM可能出现参考数据与实况数据有较大偏差的情况,从而影响订正效果,OTS则不受参考数据的影响;数值模式降水的预报偏度明显大于1或小于1时,FM、OTS订正效果越好;FM、OTS难以订正小雨漏报、暴雨空报,也难以对降水差值较大的空漏报或降水落区偏差进行订正。     

基于GF-1的坑塘信息精确提取方法研究

以国产高分一号2 m全色、8 m多光谱遥感影像作为数据源,选择廊坊市文安县作为研究区域,针对坑塘信息精确提取问题,采用单波段阈值法、监督分类法、面向对象方法等进行实验研究,重点研究了面向对象方法,结合运用遥感影像光谱、纹理、形状等特征,分析坑塘与其他地物之间的差异,最终实现坑塘信息的精确提取。     

南水北调东线工程通水后东平湖水质评价

为了解南水北调东线工程全线通水后东平湖水质状况,于2015年6月（枯水期）采集了东平湖4个地表水样品和7个地下水样品,测定了其中As、Cd、Cr、Cu、F、Hg、Mn和Pb等8种元素的含量,采用综合污染指数法、综合水质评分法和健康风险评价模型评价了其水环境质量和健康风险,结果表明：地表水中重金属浓度多数满足地表水环境质量标准I类,其中Hg污染相对较重,地下水中重金属浓度多数满足地下水质量标准III类及以上,其中F和Mn污染相对较重;4个地表水采样点综合污染指数均小于1,表明其水质优良,地下水中3个采样点的综合水质评分小于2.5,水质良好,4个采样点的综合水质评分大于4.25,水质较差;地表水的平均健康风险为9.18×10-5a-1,地下水的平均健康风险为8.16×10-5a-1,均为III级中风险。     

蒙特卡罗方法在降水评估中的应用研究

预报检验重点关注预报与观测间的综合统计特征用以探讨模式预报性能,而统计显著性检验方法是衡量评估结论的重要指标,是判断预报效果改进与否的有效手段.当前诸多重要检验指标如降水技巧评分等由于不满足正态分布特征均难以采用简单的计算方式获得置信区间以衡量检验指标的误差特征,因此难以正确判断通过统计检验所获得的评估差异是真实反映模式预报效果差异或是由检验样本的不确定性所造成.蒙特卡罗方法可通过样本重构获取正态分布的统计样本从而有效地解决这一问题.采用2015年8月的T639模式及GRAPES全球预报模式24 h降水预报产品,使用中国区域2400站日降水资料作为实况,重点研究蒙特卡罗方法在统计显著性检验中的应用特征,分析不同蒙特卡罗重构次数对检验结果的收敛性.结果表明10 000次蒙特卡罗重构后统计指标可满足正态分布,而通过显著性检验分析后可明显区分预报系统间降水评分差异的统计特征.     

MODES系统对贵州月气温、降水预测初步评估

通过对2013年1月—2015年6月(MODES)发布的最优月预测产品在贵州省月平均气温距平和降水距平百分率的预测检验评估,发现MODES对全省平均气温有较好的预报,分析时段内预测与实况的相关系数为0.24,距平同号率为65.5%,且对气温偏高预测的可参考性高于其对气温偏低的预测。相比于气温,MODES对降水预测能力较弱,参考性也相对较低,其中对贵州全省平均降水偏多趋势的预测技巧要优于对全省平均偏少趋势的预报技巧。逐站分析显示,MODES对贵州气温预测效果较好的地区在西部、北部和东部,对降水偏多的预测效果较好的地区位于除西北部和北部边缘地区外的其余大部地区。通过对MODES与预报员综合预报的结果评估发现,MODES月预测总体效果较预报员好,且稳定性高于预报员,可为预报员提供参考信息。     

Contrasting the Skills and Biases of Deterministic Predictions for the Two Types of El Nio

The tropical Pacific has begun to experience a new type of El Nio, which has occurred particularly frequently during the last decade, referred to as the central Pacific(CP) El Nio. Various coupled models with different degrees of complexity have been used to make real-time El Nio predictions, but high uncertainty still exists in their forecasts. It remains unknown as to how much of this uncertainty is specifically related to the new CP-type El Nio and how much is common to both this type and the conventional Eastern Pacific(EP)-type El Nio. In this study, the deterministic performance of an El Nio–Southern Oscillation(ENSO) ensemble prediction system is examined for the two types of El Nio. Ensemble hindcasts are run for the nine EP El Nio events and twelve CP El Nio events that have occurred since 1950. The results show that(1) the skill scores for the EP events are significantly better than those for the CP events, at all lead times;(2) the systematic forecast biases come mostly from the prediction of the CP events; and(3) the systematic error is characterized by an overly warm eastern Pacific during the spring season, indicating a stronger spring prediction barrier for the CP El Nio. Further improvements to coupled atmosphere–ocean models in terms of CP El Nio prediction should be recognized as a key and high-priority task for the climate prediction community.     

Flood forecasting in Niger-Benue basin using satellite and quantitative precipitation forecast data

Availability of reliable, timely and accurate rainfall data is constraining the establishment of flood forecasting and early warning systems in many parts of Africa. We evaluated the potential of satellite and weather forecast data as input to a parsimonious flood forecasting model to provide information for flood early warning in the central part of Nigeria. We calibrated the HEC-HMS rainfall-runoff model using rainfall data from post real time Tropical Rainfall Measuring Mission (TRMM) Multi satellite Precipitation Analysis product (TMPA). Real time TMPA satellite rainfall estimates and European Centre for Medium-Range Weather Forecasts (ECMWF) rainfall products were tested for flood forecasting. The implication of removing the systematic errors of the satellite rainfall estimates (SREs) was explored. Performance of the rainfall-runoff model was assessed using visual inspection of simulated and observed hydrographs and a set of performance indicators. The forecast skill was assessed for 1–6 days lead time using categorical verification statistics such as Probability Of Detection (POD), Frequency Of Hit (FOH) and Frequency Of Miss (FOM). The model performance satisfactorily reproduced the pattern and volume of the observed stream flow hydrograph of Benue River. Overall, our results show that SREs and rainfall forecasts from weather models have great potential to serve as model inputs for real-time flood forecasting in data scarce areas. For these data to receive application in African transboundary basins, we suggest (i) removing their systematic error to further improve flood forecast skill; (ii) improving rainfall forecasts; and (iii) improving data sharing between riparian countries.     

Factors Limiting the Forecast Skill of the Boreal Summer Intraseasonal Oscillation in a Subseasonal-to-Seasonal Model

In this study,we evaluate the forecast skill of the subseasonal-to-seasonal(S2S)prediction model of the Beijing Climate Center(BCC)for the boreal summer intraseasonal oscillation(BSISO).We also discuss the key factors that inhibit the BSISO forecast skill in this model.Based on the bivariate anomaly correlation coefficient(ACC)of the BSISO index,defined by the first two EOF modes of outgoing longwave radiation and 850-hPa zonal wind anomalies over the Asian monsoon region,we found that the hindcast skill degraded as the lead time increased.The ACC dropped to below 0.5for lead times of 11 days and longer when the predicted BSISO showed weakened strength and insignificant northward propagation.To identify what causes the weakened forecast skill of BSISO at the forecast lead time of 11 days,we diagnosed the main mechanisms responsible for the BSISO northward propagation.The same analysis was also carried out using the observations and the outputs of the four-day forecast lead that successfully predicted the observed northward-propagating BSISO.We found that the lack of northward propagation at the 11-day forecast lead was due to insufficient increases in low-level cyclonic vorticity,moistening and warm temperature anomalies to the north of the convection,which were induced by the interaction between background mean flows and BSISO-related anomalous fields.The BCC S2S model can predict the background monsoon circulations,such as the low-level southerly and the northerly and easterly vertical shears,but has limited capability in forecasting the distributions of circulation and moisture anomalies.     

Transportation Part II

Abstract

This article presents research on evaluating problem-based learning using GIS technology in a Singapore secondary school. A quasi-experimental research design was carried to test the PBL pedagogy (PBL-GIS) with an experimental group of students and compare their learning outcomes with a control group who were exposed to PBL but not GIS. The results show significant differences in the learning outcomes between the two groups. Specifically, students in the control group show more memorization skill while students in the experimental group demonstrate more analytical and evaluation skills. The conclusion is that learning with PBL-GIS pedagogy can result in higher-order learning outcomes.     

对比加权评分法在边坡治理方案优选中的应用

通过对量化指标和定性指标的评分,用对比法确定各因素权值,用加权评分法对各方案进行优选,得出最优方案。以实例分析了该方法的应用,计算结果表明：该方法简易可行,减少了目标的客观权重与实际情况之间的误差。