Short-term Climate Characteristics at Ny-(A)lesund over the Arctic Tundra Area

Based on the Germany Koldwey Station's 1994-2003 conventional observation hourly data, this paper conducts a statistical analysis on the short-term climate characteristics for an arctic tundra region (Ny-(A)lesund island) where our first arctic expedition station (Huanghe Station) was located. Affected by the North Atlantic warming current, this area has a humid temperate climate, and the air temperature at Ny-(A)lesund rose above 0 ℃ even during deep winter season during our research period. The wind speed in this area was low and appeared most at southeast direction. We find that the temperature at Ny-(A)lesund rose in the faster rate (0.68 ℃/10 a) than those at the whole Arctic area. Compared with the floating ices where our expedition conducted in the Arctic, Ny-(A)lesund was warmer and more humid and had lower wind speed. Comparison of the near surface air temperature derived by NCEP/NCAR reanalysis to the conventional measurements conducted at the Koldwey site in Ny-(A)lesund area shows a good agreement for winter season and a significant difference for summer season.     

热带气旋进入广西影响区强度突然加强的环流特征及物理量诊断分析

本文对1960~2002年进入广西影响区的热带气旋进行统计分析,发现平均每年有4.3个热带气旋进入广西影响区,强度突然加强的平均每年有0.3个,发生在6~10月,其区域分布主要集中在海南岛东北部近海至粤西近海区域和北部湾海域。利用《台风年鉴》和《历史天气图》以及欧洲中心NCEP再分析资料,对这类热带气旋进行环流特征诊断分析,得出了一些结论,有助于更好地做出这类热带气旋的风力和降水预报。     

利用浮标资料初步评估NCEP再分析湍通量

通过与浮标观测资料的对比分析,指出NCEP动量通量、再计算NCEP热通量更能够代表NCEP再分析数据库的数值模拟效果。当风速大于20m/s时,数值模拟的湍通量低于浮标块体湍通量,当风速在10～20m/s时,数值模拟的湍通量高于浮标块体湍通量。同时还发现数值模拟结果的延迟现象,以及不能反映大风过后快速的海气温差变化而引起的感热通量变化。     

EAR70、CLDAS和ERA Interim表层土壤温度在中国地区的评估

本文利用2010—2015年2400多国家气象站逐小时观测数据对覆盖中国的EAR70、CLDAS和ERA Interim 3种表层土壤温度进行了评估和对比。结果表明：空间上CLDAS表层土壤温度精度最高（平均误差为-0.5 ℃，均方根误差为3.0 ℃，相关系数为0.96），受益于CLDAS高精度的陆面初始场，EAR70平均误差得到了改善；时间上ERA Interim再分析表层土壤温度在6:00和夏、秋季精度会明显下降，再分析表层土壤温度在数值较高时段表现出冷偏差，原因是模拟的土壤温度数值上升速度慢，对应的参数化方案有待改进。再分析表层土壤温度在东北地区冬季存在冷偏差，可能和积雪覆盖有关，陆面参数化方案也有待提高。在地形复杂的青藏高原地区，融合地面观测的CLDAS提高了大气驱动的质量进而改进了土壤的模拟。ERA Interim分辨率较粗不适合在青藏高原或者沿海地区使用，结合了CLDAS的EAR70在青藏高原精度提高。土壤表层温度的精度随着高精度的土壤状态初始场进入模式中时间延长会显著下降。因此，CLDAS的实时同化方式，能够有效提高在分析数据的精度。     

北极苔原新奥尔松地区的地表辐射特征

利用我国北极黄河站所在地,德国Koldewey站1993-2003年的资料,对新奥尔松地区的地表辐射特征进行了初步分析。结果表明,由于云的影响,新奥尔松极昼期间的日照百分率仅为32.2%。暖季由于下垫面地表冰雪融化,地表反射率迅速减小,地面吸收辐射和地面有效辐射都迅速增大。全年累计的净辐射为正值;暖季是接受太阳辐射能的主要时段,寒季接受的太阳辐射能极少。虽近10年来新奥尔松地区的气温增加十分显著,但各辐射量的变化趋势不明显。地表辐射实测值与同期NCEP/NCAR相邻格点逐日资料的比较表明,NCEP资料对各辐射项模拟的精度不高。     

一个简单海气耦合模式预报性能评估

对改进初始强迫风场后的Zebiak-Cane海气耦合模式预报性能进行了全面评估。结果表明：1）耦合模式在20世纪90年代预报能力小于80年代；提前0～5个月的耦合模式预报能力小于同期持续预报能力，之后则相反；耦合模式对Nino3区指数预报能力最强。2）在1997／1998年El Nino事件期间，耦合模式对东太平洋SSTA场预报能力大于其对中西太平洋SSTA场的预报能力，且提前0～2个月之后的耦合模式对东太平洋SSTA场预报能力远远大于持续预报。     

MODIS与NCEP大气可降水量资料的比较分析

利用中国大陆地区2001年4个季节(1、4、7、10月)中8d和4m的NCEP资料，对整层大气的比湿进行积分得到大气可降水量。选用了同时同地的MODIS大气可降水量资料，然后对两者进行了对比分析。结果发现：在中国西北、内蒙地区MODIS大气可降水量资料要比NCEP资料普遍偏大，而在东南和华南部分地区则普遍偏小。如果对上述两个地区的MODIS资料分别乘以修正系数0．933983和1．07686，则两者的差别可控制在0．2cm以内。因此，MODIS大气可降水量资料经过修正后，可以为卫星反演模式提供同化性较好的输入资料。     

基于高分辨率风场的海洋近惯性能通量计算——时空特征及其影响因素

基于高分辨率CFSR(climate forecast system reanalysis)风场资料、气候态海洋混合层厚度资料和卫星高度计海面高度异常资料,本文估计了大气风场向全球海洋混合层的近惯性能通量和近惯性能量输入功率,并探究了混合层厚度、风场时间分辨率、经验衰减系数和中尺度涡旋涡度对近惯性能通量和能量输入功率的影响。浮标实测风场和流速表明,本文所用的风场和阻尼平板模型可用于估计风场向全球海洋的近惯性能通量。本文计算得到的大气向全球海洋输入近惯性能量的功率为0.56TW(1TW=10~(12)W),其中北半球贡献0.22TW,南半球贡献0.34TW。在时间上,风场的近惯性能通量呈现各个半球冬季最强、夏季最弱的特征,这和西风带风场的季节变化有关。在空间上,近惯性能通量的高值海域为南、北半球西风带海洋,尤其是南大洋。混合层厚度和风场空间不均匀性使得西风带近惯性能通量呈现纬向变化,即海盆西部强于海盆东部。风场时间分辨率对近惯性能通量的估计至关重要,低时间分辨率风场对近惯性能通量的低估达到13%—30%。阻尼平板模型中的经验衰减系数对近惯性能通量估计的影响不超过5%。中尺度涡旋涡度仅改变近惯性能通量的空间分布,而对全球近惯性能量输入功率的影响可以忽略。     

Estimation of mean and extreme waves in the East China Seas

Accurately estimating the mean and extreme wave statistics and better understanding their directional and seasonal variations are of great importance in the planning and designing of ocean and coastal engineering works. Due to the lack of long-term wave measurement data, the analysis of extreme waves is often based on the numerical wave hind-casting results. In this study, the wave climate in the East China Seas (including the Bohai Sea, the Yellow Sea and the East China Sea) for the past 35 years (1979–2013) is hind-casted using a third generation wave model – WAMC4 (Cycle 4 version of WAM model). Two sets of reanalysis wind data from NCEP (National Centers for Environmental Prediction, USA) and ECMWF (European Centre for Medium-range Weather Forecasts) are used to drive the wave model to generate the long-term wave climate. The hind-casted waves are then analysed to study the mean and extreme wave statistics in the study area. The results show that the mean wave heights decrease from south to north and from sea to land in general. The extreme wave heights with return periods of 50 and 100 years in the summer and autumn seasons are significantly higher than those in the other two seasons, mainly due to the effect of typhoon events. The mean wave heights in the winter season have the highest values, mainly due to the effect of winter monsoon winds. The comparison of extreme wave statistics from both wind fields with the field measurements at several nearshore wave observation stations shows that the extreme waves generated by the ECMWF winds are better than those generated by the NCEP winds. The comparison also shows the extreme waves in deep waters are better reproduced than those in shallow waters, which is partly attributed to the limitations of the wave model used. The results presented in this paper provide useful insight into the wave climate in the area of the East China Seas, as well as the effect of wind data resolution on the simulation of long-term waves.     

中国近海以及邻近海域海洋再分析产品(CORA)中季节内变化的评估

A regional reanalysis product—China Ocean Reanalysis(CORA)—has been developed for the China's seas and the adjacent areas. In this study, the intraseasonal variabilities(ISVs) in CORA are assessed by comparing with observations and two other reanalysis products(ECCO2 and SODA). CORA shows a better performance in capturing the intraseasonal sea surface temperatures(SSTs) and the intraseasonal sea surface heights(SSHs) than ECCO2 and SODA do, probably due to its high resolution, stronger response to the intraseasonal forcing in the atmosphere(especially the Madden-Julian Oscillation), and more available regional data for assimilation. But at the subsurface, the ISVs in CORA are likely to be weaker than reality, which is probably attributed to rare observational data for assimilation and weak diapycnal eddy diffusivity in the CORA model. According to the comparison results, CORA is a good choice for the study related to variabilities at the surface, but cares have to be taken for the study focusing on the subsurface processes.