Machine Learning-based Weather Support for the 2022 Winter Olympics

正1.A key support for the 2022 Winter Olympics The XXIV Olympic Winter Games are scheduled to take place from 4 to 22 February 2022, followed by the Paralympic Games from 4 to 13 March, in Beijing and towns in the neighboring Hebei Province, China. Weather plays an extremely important role in the outcome of the games (Chen et al., 2018). It can not only cause a difference between a medal or not, but affect the safety of athletes. Success of the Winter Olympics will greatly depend on weather conditions at the outdoor competition venues, dealing with many weather elements including the snow surface temperature, apparent tem-     

基于FY-3C微波辐射成像仪海表温度产品的偏差订正方法研究

提出一种针对FY-3C搭载的微波辐射成像仪（MWRI）海表温度产品的分段回归偏差订正方法,该方法通过引进气候态海表温度数据,建立与关联实测海表温度相匹配的回归模型,并通过对模型中关联变量的误差分析,选择最优样本进行分段回归,以实现对海表温度数据的重新估计。通过对MWRI海表温度数据的偏差订正试验表明,采用分段回归方法获得的订正结果无论在误差指标的空间分布还是时间序列上,都要明显优于采用传统概率密度函数偏差订正方法的结果。其中,采用概率密度函数方法订正后的海表温度产品误差标准差和均方根误差从订正前的0.9—1.0℃,减小到0.8℃左右,而采用分段回归方法获得相应的订正误差仅为0.6℃左右,订正效果有明显改善。      

Decreasing precipitation occurs in daily extreme precipitation intervals across China in observations and model simulations

Extreme precipitation response to increasing temperature includes not only changes of frequency and intensity, but also changes of extreme precipitation interval (EPIV) and the precipitation during the neighboring daily extreme precipitations interval (EPIP). These changes have not been fully evaluated yet in observations or climate model simulations although they are very useful to understand variations of extreme precipitation. We used daily precipitation data from 669 meteorological stations during the past five decades across China and projections of 19 general circulation models from CMIP5 under the RCP4.5 and RCP8.5 scenarios to investigate variations of EPIV and EPIP. We found the national average annual EPIV increased across China during the last five decades, while annual EPIP significantly decreased. The decreases mainly occurred in southwest China, east China, and southeast China. At national and regional scales, the average annual EPIV and EPIP showed greater decreases under the RCP8.5 scenario than those under the RCP4.5 scenario from 2006 to 2100. Annual EPIP showed a stronger correlation with extreme precipitation intensity than EPIV. The national average annual EPIP had a significant positive correlation with the Western Pacific Subtropical High Area Index. The abnormal geopotential heights over western Mongolia and the western Pacific at 500 hpa as well as the abnormal SSTs in Japan Sea and the western of Pacific in rainy seasons would result in abnormal annual EPIVs and EPIPs in China. This study may provide references for flooding prediction, water resources management, and disaster prevention and mitigation.     

合成孔径雷达森林资源监测技术研究综述

合成孔径雷达（Synthetic Aperture Radar,SAR）技术凭借其全天时、全天候的成像能力以及对森林垂直结构信息敏感的特点,在森林资源监测中具有独特的优势,已成为当前森林资源遥感调查技术的研究热点.本文首先介绍了SAR森林资源监测技术的发展背景、发展轨迹和相关知识;然后,重点阐述了极化SAR、干涉SAR、极化干涉SAR和层析SAR在林地覆盖类型分类、变化检测以及森林参数定量化估测应用中的技术方法;最后,就SAR在森林资源监测研究和应用中存在的问题与发展趋势进行了总结与展望.     

信息网络管理及安全防范

1信息网络存在的问题(1)信息网络硬件配置的安全策略不够全面。一般都能够部署边界防火墙和配备网络病毒查杀软件等基础设施,但缺乏有针对性及病毒库更新及时的防护软件。在内外网分离的工作环境中,内网也只重视边界防护,一旦突破内网,安全无法保障。部分业务和网络节点还存在缺陷,对网络技术的恶意代码检测手段及安全事件的事中分析、事后溯源能力不足,因此存在被网络攻击的风险。     

Wintertime Cyclone Activity and Its Relation to Precipitation over China

The authors examined the variability in wintertime cyclone activity and storm tracks and their relation to precipitation over China for the period 1951–2006 using the observational data.Two apparent modes of variability were assumed for the cyclone activity and storm tracks.The first mode describes the oscillation in the strength of the storm tracks in East Asia,which significantly increased since the mid-1980s,whereas the second mode describes a seesaw oscillation in the storm track strength between the Central-Southeast China and northern East Asia.The storm tracks over the Central-Southeast China have increased since the late 1960s.The possible causes for the variation of the cyclone activity and storm tracks are also explored.It is shown that wintertime precipitation,which has increased since the mid-1980s,concentrates in Central-Southeast China.The enhancement may be caused by the first mode of variability of storm tracks,whereas the interannual variability of precipitation may be linked to the second mode of the storm track variability.     

起伏地形下河南省太阳散射辐射的分布式模拟

利用河南省及周边145个气象站1961－2000年常规气象观测资料和河南省1:25万DEM数据,充分考虑起伏地形下太阳散射辐射的天空因素与地面因素后,基于分布式开阔度模型和天文辐射模型,实现了起伏地形下河南省太阳散射辐射的分布式模拟.计算了100m×100 m分辨率下河南省1－12月气候平均太阳散射辐射及多年平均年散射辐射总量的空间分布.结果表明:在充分考虑经验系数的时空分布特征后,模拟精度有了进一步提高.与郑州站的观测资料对比验证表明,模拟精度较高,年平均绝对误差为3.06 MJ·m-2,年平均相对误差为1.67％;局地地形对太阳散射辐射的影响比较明显;通过个例年验证对模型性能和模拟结果进行考察,年平均相对误差不足11％.综上表明模型的时空模拟性能良好.     

华北“7.20”特大暴雨多尺度特征分析

利用华北地区248个加密气象观测站资料、FY-2G黑体亮温TBB、邢台站探空资料、华北地区多普勒雷达资料、欧洲中心（ECMWF）0.25°×0.25°和NCEP/NCAR（1°×1°）再分析资料,对2016年7月19—21日一场特大暴雨进行多尺度特征分析。结果表明：200 hPa南亚高压系统呈东西带状分布,500 hPa为“东高西低”环流背景,鄂霍茨克海附近闭合高压下游阻挡效应使上游系统移速缓慢,华北长时间处于深槽之中,环流形势利于产生稳定经向型暴雨;通过高低层流场对比发现,高空急流入口区右侧与低空急流出口区左侧重叠区为最强降水区域,降水大值区均位于太行山及燕山山脉迎风坡;垂直方向上,垂直上升运动中心介于散度辐合中心与辐散中心之间,剧烈的抽吸效应将水汽输送至高层,冷暖气流交汇及水汽上升过程凝结潜热释放导致对流系统迅速发展。河北地区稳定的深厚气旋是本次暴雨的关键系统,19日石家庄地区强对流单体（>45 dBz）存在时间超过20 h。MCS影响范围广、特殊山脉地形作用、系统停留时间较长等原因造成累积降水量增大,是本次暴雨与“7.21”北京特大暴雨相比的突出特点之一。     

2017年11月7—8日南昌市一次重度污染天气过程分析

利用地面常规观测资料、探空资料和大气污染物监测数据等资料,对2017年11月7—8日南昌市一次重度污染天气过程的大气污染物特征、天气形势及气象要素特点等进行了分析,并运用拉格朗日混合单粒子轨道模型（HYSPLIT）分析了大气污染物的后向轨迹。结果表明：1） 此次过程的首要污染物为PM2.5,空气质量呈东部劣于西部,市内劣于市郊的特点。AQI有明显的日变化特征,凌晨和上午10时各有一个AQI高峰,傍晚有一个AQI低谷,中午前后为AQI明显下降时段。2） 地面气压梯度小、风速小,不利于污染物的扩散。对流层中层有低槽东移,低层有弱切变线位于江西省北部,低层弱辐合导致周边污染物向中心辐合堆积。地面能见度与相对湿度变化呈反相关,在重度污染天气发生时多为雾和霾的混合物。南昌上空表现为“中层湿、低层干”的特点,在较干的低层有等温层和弱的逆温层,能抑制大气污染物的垂直扩散。3） 此次重度污染天气过程的大气污染物来源主要有三个,即南昌市周边环境污染、本地污染源的排放和大气污染物的外来输入,外来输入源主要为广东、广西及湖南上空的大气污染物。     

2017年3月江苏北部一次雷雨大风天气过程分析

利用多种常规观测资料和NCEP／NCAR再分析资料,分析了2017年3月1日江苏北部出现的一次罕见冷空气雷雨大风天气过程的发生背景、地面要素和云团演变特征,同时从大气动力、热力和水汽条件出发分析了午后对流的成因。结果表明：此次过程发生前,江苏地区位于高空槽前,对流层中低层有冷式切变线伴随两股冷空气南下,受江苏省北部地面气旋阻挡,冷空气在上游堆积,当气旋东移入海冷空气爆发式南下时,造成严重的大风灾害。此次过程中,对流层中高层大气降温而低层回温使大气温度直减率增大,为对流发生提供不稳定条件,但水汽输送主要集中在低层,且高层大气无明显抽吸作用,导致此次过程未发生强对流性降水,主要以大风灾害性天气为主。