东中国海黑潮海洋锋的季节变化特征及其成因

利用高分辨率海洋和大气再分析资料研究了东中国海黑潮海洋锋的季节变化特征及其成因。研究表明,东海黑潮海洋锋存在明显的季节变化,从冬季到次年春季逐渐增强,并在春季达到最强,初夏以后强度逐渐减弱,9—10月达到全年最弱。通过诊断混合层热流量方程发现,东海黑潮区一年四季均表现为暖的温度平流,有利于海洋锋的形成和维持,该暖平流也存在季节变化并在春季达到最大,对海洋锋在春季达到最强起了重要作用。海气界面净热通量在秋冬季对海洋锋的形成有促进作用,有利于海洋锋增强,而在春夏季则起抑制作用,促进海洋锋消亡。温度垂直输送全年对海洋锋起一定程度的抑制作用。总之,在海温水平平流和海表净热通量的共同作用下导致海洋锋春季达到最强,而夏秋季海表净热通量和温度垂直输送作用的共同作用致使海洋锋减弱并最后消失。因此,海洋的动力和热力共同作用导致了东海黑潮海洋锋的季节变化,其中海温水平平流和海表净热通量对海洋锋的季节变化起主要作用,而温度垂直输送项对海洋锋的发展起抑制作用,但影响相对较小。     

省级气象广域网网络优化的设计与应用

目前湖北省气象地面宽带网省—地—县3级结构中,省局与各市(州)局间采用单条专线连接,手动VPN(Virtual Private Network)拨号线路备份的传输方式,这种传输方式不足以保证数据传输的可靠性。现设计新增一条专线,实现省到地的双线路备份。同时,增加一台省端网络互联交换机,升级地市端的网络互联路由器硬件,将数据划分为业务数据和视频会商两类,定义不同的传输方式。业务数据采用OSPF(Open Shortest Path First)动态路由方式进行传输,视频会商通过配置静态路由BFD(Bidirectional Forwarding Detection)联动的路由方式进行传输,并通过QoS(Quality of Service)保证其4 Mb/s的带宽,从而实现省到地数据业务更合理可靠地传输。     

Changes of precipitation extremes over South Korea projected by the 5 RCMs under RCP scenarios

The change of extreme precipitation is assessed with the HadGEM2-AO - 5 Regional Climate Models (RCMs) chain, which is a national downscaling project undertaken cooperatively by several South Korean institutes aimed at producing regional climate change projection with fine resolution (12.5 km) around the Korean Peninsula. The downscaling domain, resolution and lateral boundary conditions are held the same among the 5 RCMs to minimize the uncertainties from model configuration. Climatological changes reveal a statistically significant increase in the mid-21st century (2046- 2070; Fut1) and the late-21st century (2076-2100; Fut2) precipitation properties related to extreme precipitation, such as precipitation intensity and average of upper 5 percentile daily precipitation, with respect to the reference period (1981-2005). Changes depending on the intensity categories also present a clear trend of decreasing light rain and increasing heavy rain. In accordance with these results, the change of 1-in-50 year maximum precipitation intensity over South Korea is estimated by the GEV method. The result suggests that the 50-year return value (RV50) will change from -32.69% to 72.7% and from -31.6% to 96.32% in Fut1 and from -31.97% to 86.25% and from -19.45% to 134.88% in Fut2 under representative concentration pathway (RCP) 4.5 and 8.5 scenarios, respectively, at the 90% confidence level. This study suggests that multi-RCMs can be used to reduce uncertainties and assess the future change of extreme precipitation more reliably. Moreover, future projection of the regional climate change contains uncertainties evoked from not only driving GCM but also RCM. Therefore, multi-GCM and multi-RCM studies are expected to provide more robust projection.     

Projections of high resolution climate changes for South Korea using multiple-regional climate models based on four RCP scenarios. Part 1: surface air temperature

We projected surface air temperature changes over South Korea during the mid (2026-2050) and late (2076-2100) 21st century against the current climate (1981-2005) using the simulation results from five regional climate models (RCMs) driven by Hadley Centre Global Environmental Model, version 2, coupled with the Atmosphere- Ocean (HadGEM2-AO), and two ensemble methods (equal weighted averaging, weighted averaging based on Taylor’s skill score) under four Representative Concentration Pathways (RCP) scenarios. In general, the five RCM ensembles captured the spatial and seasonal variations, and probability distribution of temperature over South Korea reasonably compared to observation. They particularly showed a good performance in simulating annual temperature range compared to HadGEM2-AO. In future simulation, the temperature over South Korea will increase significantly for all scenarios and seasons. Stronger warming trends are projected in the late 21st century than in the mid-21st century, in particular under RCP8.5. The five RCM ensembles projected that temperature changes for the mid/late 21st century relative to the current climate are +1.54°C/+1.92°C for RCP2.6, +1.68°C/+2.91°C for RCP4.5, +1.17°C/+3.11°C for RCP6.0, and +1.75°C/+4.73°C for RCP8.5. Compared to the temperature projection of HadGEM2-AO, the five RCM ensembles projected smaller increases in temperature for all RCP scenarios and seasons. The inter-RCM spread is proportional to the simulation period (i.e., larger in the late-21st than mid-21st century) and significantly greater (about four times) in winter than summer for all RCP scenarios. Therefore, the modeled predictions of temperature increases during the late 21st century, particularly for winter temperatures, should be used with caution.     

Influence of coastal wind on surface ozone and nitrogen oxides in suburban Shanghai

Surface ozone, NO, NO₂, and NO _x were measured at a coastal site (Shihua) and a nearby inland site (Zhujing) in suburban Shanghai for the whole year of 2009. More days with ozone pollution in a longer time range were observed at the coastal site than the inland site. The diurnal variations of NO _x concentrations were obviously higher at Zhujing station, while those of ozone concentrations were higher at Shihua station, indicating their different air pollution conditions. Coastal wind has significant influence on the levels and characteristics of the air pollutants. The ozone concentrations during maritime winds (MW) were much higher than those during continental winds (CW) at each of the site, while the NO and NO₂ concentrations were both opposite. The ozone concentrations at Shihua station were much higher than those at Zhujing station, while the NO and NO₂ concentrations were both opposite. The ozone concentrations at both of the two sites showed a distinct “weekend effects” and “weekdays effects” patterns during CW and MW, respectively. Correlation analysis of the pollutants showed that, the compounds during MW were more age than those during CW, and the compounds at Shihua were more age than those at Zhujing. The air pollutions at both of the two sites are mainly associated with the pollutants emitted in this region instead of long range transport.     

Erratum to: Climate change projections over India by a downscaling approach using PRECIS

The author “Bhaski Bhaskaran” and his affiliation “Fujitsu Laboratory of Europe, Middlesex, UK” should be replaced by “Balakrishnan Bhaskaran”, “Fujitsu Laboratories of Europe Limited, Hayes Park, Middlesex, UK”, respectively.The corrected name and affiliation are shown in this erratum.     

Comparison of prediction performance using statistical postprocessing methods

As the 2018 Winter Olympics are to be held in Pyeongchang, both general weather information on Pyeongchang and specific weather information on this region, which can affect game operation and athletic performance, are required. An ensemble prediction system has been applied to provide more accurate weather information, but it has bias and dispersion due to the limitations and uncertainty of its model. In this study, homogeneous and nonhomogeneous regression models as well as Bayesian model averaging (BMA) were used to reduce the bias and dispersion existing in ensemble prediction and to provide probabilistic forecast. Prior to applying the prediction methods, reliability of the ensemble forecasts was tested by using a rank histogram and a residualquantile-quantile plot to identify the ensemble forecasts and the corresponding verifications. The ensemble forecasts had a consistent positive bias, indicating over-forecasting, and were under-dispersed. To correct such biases, statistical post-processing methods were applied using fixed and sliding windows. The prediction skills of methods were compared by using the mean absolute error, root mean square error, continuous ranked probability score, and continuous ranked probability skill score. Under the fixed window, BMA exhibited better prediction skill than the other methods in most observation station. Under the sliding window, on the other hand, homogeneous and non-homogeneous regression models with positive regression coefficients exhibited better prediction skill than BMA. In particular, the homogeneous regression model with positive regression coefficients exhibited the best prediction skill.     

Development of statistical seasonal prediction models of Arctic Sea Ice concentration using CERES absorbed solar radiation

Statistical seasonal prediction models for the Arctic sea ice concentration (SIC) were developed for the late summer (August-October) when the downward trend is dramatic. The absorbed solar radiation (ASR) at the top of the atmosphere in June has a significant seasonal leading role on the SIC. Based on the lagged ASR-SIC relationship, two simple statistical models were established: the Markovian stochastic and the linear regression models. Crossvalidated hindcasts of SIC from 1979 to 2014 by the two models were compared with each other and observation. The hindcasts showed general agreement between the models as they share a common predictor, ASR in June and the observed SIC was well reproduced, especially over the relatively thin-ice regions (of one- or multi-year sea ice). The robust predictability confirms the functional role of ASR in the prediction of SIC. In particular, the SIC prediction in October was quite promising probably due to the pronounced icealbedo feedback. The temporal correlation coefficients between the predicted SIC and the observed SIC were 0.79 and 0.82 by the Markovian and regression models, respectively. Small differences were observed between the two models; the regression model performed slightly better in August and September in terms of temporal correlation coefficients. Meanwhile, the prediction skills of the Markovian model in October were higher in the north of Chukchi, the East Siberian, and the Laptev Seas. A strong non-linear relationship between ASR in June and SIC in October in these areas would have increased the predictability of the Markovian model.     

湖北省冻雨天气特征及其判定方法研究

利用常规地面气象站多时次气象要素和天气现象观测资料,以及武汉、宜昌和恩施的探空资料,对1998—2014年湖北地区冻雨天气的主要环流背景进行了分析,归纳了冻雨发生发展过程的气象要素和大气层结特征,给出了基于正负能量面积的冻雨发生定量化判断方法。结果表明:乌山阻高型和贝湖阻高型是导致湖北省出现冻雨天气的两种主要天气形势;2005年和2月是冻雨主要发生的年份和月份;共存在3种典型的气温层结演变特征,其中"暖雨-冻雨-固态"的气温层结演变最易导致持续时间长、影响范围大的冻雨天气;基于正负能量面积的冻雨判定方法为:3层层结时,正能量面积(A_(SP))小于80℃·hPa,负能量面积(A_(SN))小于400℃·hPa,且正负能量关系为(5.71A_(SP)-257.14)≤A_(SN)≤(6.25A_(SP)+200);2层层结时,ASP为350~650℃·hPa,A_(SN)为200~400℃·hPa,且正负能量关系为(A_(SP)-350)≤A_(SN)≤(ASP-100)。