The 3-hour-interval prediction of ground-level temperature in South Korea using dynamic linear models

The 3-hour-interval prediction of ground-level temperature from 00 h out to 45 h in South Korea(38 stations) is performed using the DLM (dynamic linear model) in order to eliminate the systematic error of numerical model forecasts. Numerical model forecasts and observations are used as input values of the DLM. According to the comparison of the DLM forecasts to the KFM (Kalman filter model) forecasts with RMSE and bias, the DLM is useful to improve the accuracy of prediction.     

试论中国重要景观区区域地球化学异常系统评价的量化模型

在对中国5个重要景观区1:20万金、铜表生地球化学异常特征进行总结、对比,并讨论景观、表生因素对区域异常评价标志影响的基础上,进一步充实、完善了区域异常系统评价体系的思路和评价准则,提出了区域地球化学异常系统评价的量化模型。     

利用RPC模型进行IKONOS影像的精确定位

研究了IKONOS卫星影像基于RPC模型的立体定位算法与区域网平差方法.针对立体定位计算过程中RPC(Rational Polynomial Coefficients)模型存在的系统性误差,给出了物方和像方补偿方案.实验结果表明,各种补偿方案均可有效消除RPC模型的系统误差,取得优于1.3 m的定位精度;区域网平差的定位精度可达1.1 m,是最理想的定位方法.     

偏重钻铤在丁集矿冻结造孔施工中的应用

钻井技术的关键是预防及控制孔斜,通过对目前常用4种防斜钻具组合的适岩性、井深、井斜及钻效等指标对比,在冻结造孔施工中选用了适用地层广、防斜性能好并具有纠斜作用的偏重钻铤。为发挥偏重钻铤的防斜作用,宜增大转速,并使钻铤减去部分的重量应位于离轴线尽可能远的部位。在淮南丁集冻结孔施工的三十多口钻孔中,井斜一般均在0．5°以内,钻效超过2400m/台·月。     

导航卫星的单星定轨

本文对导航卫星的单星定轨进行了初步探讨，针对单星定轨时卫星钟钟差和接收机钟钟差难以处理的特点，提出了定轨的同时解算测站距离偏差和采用平均距离变化率进行定轨两种方案，采用GPS的实测数据试验计算表明，两种计算方案均能初步完成单星定轨任务。     

Importance of no‐rain measurements on the comparison of radar and rain gauge rain rate

This study evaluated four possible cases of comparing radar and rain gauge rain rate for the detection of mean‐field bias. These four cases, or detection designs, consider in this study are: (1) design 1‐uses all the data sets available, including zero radar rain rate and zero rain gauge rain rate, (2) design 2—uses the data sets of positive radar rain rate and zero or positive rain gauge rain rate, (3) design 3—uses the data sets of zero or positive radar rain rate and positive rain gauge rain rate and (4) design 4—uses the data sets of positive radar rain rate and positive rain gauge rain rate. A theoretical review of these four detection designs showed that only the design 1 causes no design bias, but designs 2, 3 and 4 can cause positive, negative and negative design biases, respectively. This theoretical result was also verified by applying these four designs to the rain rate field generated by a multi‐dimensional rain rate model, as well as to that of the Mt Gwanak radar in Korea. The results from both applications showed that especially the design 4, which is generally used for the detection of mean‐field bias of radar rain rate, causes a serious design bias; therefore, is inappropriate as a design for detecting the mean‐field bias of radar rain rate. Copyright © 2009 John Wiley & Sons, Ltd.     

Seasonal prediction of June rainfall over South China: Model assessment and statistical downscaling

The performances of various dynamical models from the Asia-Pacific Economic Cooperation(APEC) Climate Center(APCC) multi-model ensemble(MME) in predicting station-scale rainfall in South China(SC) in June were evaluated.It was found that the MME mean of model hindcasts can skillfully predict the June rainfall anomaly averaged over the SC domain.This could be related to the MME's ability in capturing the observed linkages between SC rainfall and atmospheric large-scale circulation anomalies in the Indo-Pacific region.Further assessment of station-scale June rainfall prediction based on direct model output(DMO) over 97 stations in SC revealed that the MME mean outperforms each individual model.However,poor prediction abilities in some in-land and southeastern SC stations are apparent in the MME mean and in a number of models.In order to improve the performance at those stations with poor DMO prediction skill,a station-based statistical downscaling scheme was constructed and applied to the individual and MME mean hindcast runs.For several models,this scheme can outperform DMO at more than 30 stations,because it can tap into the abilities of the models in capturing the anomalous Indo-Paciric circulation to which SC rainfall is considerably sensitive.Therefore,enhanced rainfall prediction abilities in these models should make them more useful for disaster preparedness and mitigation purposes.     

“频率匹配法”在集合降水预报中的应用研究

基于“频率匹配法”的思路,采用两种方法进行了集合降水预报的订正研究,一种方法是利用集合成员降水频率订正简单集合平均平滑效应的“概率匹配平均”法,另一种方法是利用实况降水频率订正集合成员降水预报系统偏差的“预报偏差订正”法,通过个例和批量试验,结果表明:(1)概率匹配平均法可以矫正简单集合平均的平滑作用所造成的小量级降水分布范围增大而强降水被削弱的负作用,这种改进对强降水区更显著,并且集合系统离散度越大这种改进也越大;但该方法对预报区域内总降水量的预报没有改进作用,不能改善预报的系统性偏差.(2)虽然预报偏差订正法对降水落区预报的改进有限,但可以订正模式降水预报的系统性误差,改进雨量预报以及集合预报系统的离散度特征和概率预报技巧;直接对集合平均预报进行偏差订正的效果优于单个成员偏差订正后的简单算术平均.(3)在对每个集合成员的降水预报进行偏差订正后,概率匹配平均仍可改善其简单平均的效果,因此在实际业务中,应该综合采用上述两种方法,以获得在消除系统性偏差的同时各量级降水分布又合理的集合平均降水预报.     

GRAPES_RAFS系统2 m温度偏差订正方法研究

本文通过对2013年6月20日至7月20日GRAPES(Global and Regional Assimilation and Prediction System)_RAFS(Rapid Analysis and Forecast System)系统每天8个时次每3h的2 m温度预报进行分析,发现各时次的预报均能较好地表征2 m温度日变化特征,但预报与实况存在一定的偏差,其中西藏东部川西高原、云贵高原、江南武夷山脉偏低于实况可达3℃,而华北地区偏高于实况3℃以上.为了减小GRAPES_RAFS系统偏差对2m温度预报的影响,本文采用平均法、双权重平均法、滑动平均法和滑动双权重平均法分别对GRAPES_RAFS系统2 m温度预报产品进行偏差订正,并对订正前后的结果进行检验分析和对比.结果表明:2 m温度订正后的平均误差大部地区减小到(一1～1℃),而均方根误差大部地区降低到2.5℃内.对于偏差较大地区,订正效果更为明显,如西藏东部川西高原,经过订正,平均误差绝对值由订正前3℃以上降低到1℃内,而RMSE由订正前4℃以上控制到3℃内.对比四种订正方法,双权重订正方法与平均法订正整体效果接近,但对个别站点,双权重订正法要优于平均法,经过滑动的订正方法比无滑动的订正方法订正效果更好,订正效果最好的是滑动双权重平均法,全国平均误差大部分在(-0.5～0.5℃)内,不超过(-1～1℃)的范围.     

一种改进的数值预报降水偏差订正方法及应用

对传统的消除偏差法进行改进,形成分等级消除偏差法,并使用混合训练期和60 d滑动训练期方案分别对2012年6—8月ECMWF (European Centre for Medium-Range Weather Forecasting) 模式夏季1~5 d的降水预报进行订正试验。为了尽可能符合中国东部夏季降水具有移动性及多种时间尺度变化的特点,混合训练期以预报期前30 d与预报期前一年同日的前后各15 d组成。结果表明:在使用分等级消除偏差法的基础上,相比ECMWF模式降水预报,两种训练期方案的订正结果几乎对各个阈值的ETS评分均有一定提高,特别是对25 mm以上降水预报评分的提高幅度,混合训练期方案的订正结果明显高于60 d滑动训练期方案;在区域性强降水预报的订正中,混合训练期方案优势更为明显。另外,通过分析两种训练期方案的预报偏差发现,分等级订正是此次消除偏差订正试验中提高强降水预报评分的关键,选择合适的训练期可以增加评分提高的幅度。由于上述试验使用的ECMWF模式预报和站点实况均是业务上常用数据,因此,该方法具有一定的业务应用价值。