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基于中国第6~9次北极科学考察观测的季节冰区边界层逆温变化特征分析 总被引:1,自引:0,他引:1
利用我国第6~9次北极科学考察期间获取的大气探空资料,分析了北极季节冰区边界层逆温的时空变化特征及其成因。分析发现:(1)边界层逆温具有较强的年际变化和空间变化,高纬度密集冰区观测到更多的强逆温现象,逆温厚度与逆温层温差呈显著的对数关系;(2)不同年份边界层逆温的主要成因有所差别:海冰分布的差异导致不同年份的边界层逆温特征不同;表面融化、辐射冷却、多层云的结构和暖平流对不同冰情年份边界层逆温的贡献程度不同;(3)开阔水域和冰区边界层逆温的成因不同。表面融化和空气平流对冰区边界层逆温的形成起着非常重要的作用,而辐射冷却是开阔水域边界层逆温的主要成因之一。 相似文献
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基于2018年8月至2019年5月布放在北极随海冰漂流的自动气象站和温度链浮标获取的观测数据,分析了北极高纬度区域的大气特征和海冰生消过程。根据海冰的漂移轨迹分为两个阶段分析,第1阶段,海冰主要向东南漂移;第2阶段,海冰主要向东北漂移。第1阶段观测的平均气温和平均相对湿度分别为–6.6℃和93%,第2阶段观测的平均气温和平均相对湿度分别为–29.3℃和76%,第2阶段平均气压高于第1阶段。海冰的漂移轨迹主要受到波弗特高压外围气流的影响。利用自动气象站漂移轨迹计算得到海冰漂移速度,与美国国家冰雪数据中心海冰漂移速度比较显示,两者纬向速度更为接近。海冰在第1阶段以融化为主,海冰厚度略有减小,8月份海冰生长率为–0.11 cm/d;海冰的生长过程主要发生在第2阶段,1–3月生长率均超过0.9 cm/d,2019年3月海冰生长最快,平均生长率为1.3 cm/d,海冰的增长一直持续至观测结束。 相似文献
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Annual observations of first-year ice(FYI) and second-year ice(SYI) near Zhongshan Station, East Antarctica,were conducted for the first time from December 2011 to December 2012. Melt ponds appeared from early December 2011. Landfast ice partly broke in late January, 2012 after a strong cyclone. Open water was refrozen to form new ice cover in mid-February, and then FYI and SYI co-existed in March with a growth rate of 0.8 cm/d for FYI and a melting rate of 2.7 cm/d for SYI. This difference was due to the oceanic heat flux and the thickness of ice,with weaker heat flux through thicker ice. From May onward, FYI and SYI showed a similar growth by 0.5 cm/d.Their maximum thickness reached 160.5 cm and 167.0 cm, respectively, in late October. Drillings showed variations of FYI thickness to be generally less than 1.0 cm, but variations were up to 33.0 cm for SYI in March,suggesting that the SYI bottom was particularly uneven. Snow distribution was strongly affected by wind and surface roughness, leading to large thickness differences in the different sites. Snow and ice thickness in Nella Fjord had a similar "east thicker, west thinner" spatial distribution. Easterly prevailing wind and local topography led to this snow pattern. Superimposed ice induced by snow cover melting in summer thickened multi-year ice,causing it to be thicker than the snow-free SYI. The estimated monthly oceanic heat flux was ~30.0 W/m2 in March–May, reducing to ~10.0 W/m2 during July–October, and increasing to ~15.0 W/m2 in November. The seasonal change and mean value of 15.6 W/m2 was similar to the findings of previous research. The results can be used to further our understanding of landfast ice for climate change study and Chinese Antarctic Expedition services. 相似文献
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本文利用ERA5再分析数据和我国北极科学考察期间获取的走航气象观测数据,分析了夏季影响船舶通航北极航道的关键近地面气象要素的时空变化特征。结果表明,7–8月的天气条件最适宜船舶在北极航道航行,9月低温、大风和大浪天气显著增多,对船舶航行影响较大,10月的天气更加恶劣,对船舶航行的挑战更大。低温天气主要出现在各航道的中段,大风和大浪天气集中在航道两端的海域。除北极中心区和10月的挪威海和巴伦支海以外,其余时间的海域出现大风和大浪天气的概率以增加趋势为主,但具有较大的年际变化。根据现有北极航道气象观测数据分析发现,东北航道能见度最差,西北航道能见度最好,中央航道居中。 相似文献
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在 2013—2014年南半球夏季时对南极普里兹湾海区的反照率进行了走航观测。利用安装于破冰船船头的高光谱辐照度计测量入射和反射的350—920 nm的太阳短波辐射, 基于此观测数据, 经计算得到了反照率。分析比较不同下垫面的反照率, 通过比较不同航段的观测结果, 得到了反照率的空间变化以及从海冰融化期至冻结初期的变化。不同下垫面的反照率差异较大, 有积雪覆盖的固定冰反照率最大, 有积雪覆盖的浮冰其次, 而积雪融化的浮冰则反照率有所降低。新冰的反照率较低, 有积雪覆盖的新冰反照率迅速增加。比较不同波段的反照率, 发现融化期由于积雪含水量较大, 增加了对近红外辐射的吸收, 降低了该波段的反照率。结合卫星遥感(AMSR-2)和人工观测的海冰密集度, 发现区域平均的反照率主要取决于海冰密集度, 然而也受下垫面物理特征影响, 例如2月底至3月初形成的新冰, 反照率只有老冰的1/3— 1/2。新冰形成, 会直接增加海冰密集度, 但由于其反照率较低, 对空间平均反照率的贡献较小。因此, 若要建立合理的冰水混合区的反照率参数化方案, 必须充分考虑海冰类型和冰面积雪的物理状态, 并考虑反照率的波长依赖性。 相似文献
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近年北极东北和西北航道开通状况分析 总被引:7,自引:3,他引:4
利用微波卫星遥感数据对北极东北航道和西北航道近年来的冰情变化,以及影响航道开通的关键区域和每年的开通状况进行了分析和总结,并对航道未来的可能冰情状况进行了展望,期望对航道利用者有所帮助。东北航道全线开通期主要集中在8月下旬至10月上旬,开通总天数多在40~50d;西北航道南线开通期主要集中在8月上中旬至10月上旬,开通总天数多在50~60d;西北航道北线开通时间主要集中在9月。东北航道冰情最为复杂的是连接拉普捷夫海和喀拉海的北地群岛区域海冰,也是影响航道开通的关键区。影响西北航道南线开通的关键主要是威廉王岛附近维多利亚海峡、威尔士王子岛东侧的皮尔海峡和北侧巴罗海峡区域的海冰状况;影响北线开通的关键区域是班克斯岛西北部的麦克卢尔海峡和梅尔维尔子爵海峡;东北航道可通航性优于西北航道。虽然气候变化大背景下北极海冰总量减少,但由于海冰流动性增强,局部海冰变化愈发复杂,海冰分布年际差异较大,需要加强北极海冰监测和预报能力,为未来航道利用提供保障。 相似文献
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2014年初雪龙船为救援俄罗斯"绍卡利斯基院士"号船,在南极联邦湾被海冰围困,及时掌握雪龙船周边的冰情变化,以及给出准确的天气形势判断和预报,是此次雪龙船顺利脱困的关键。通过对雪龙船被困期间的海冰、气象和海洋环境状况综合分析发现,造成雪龙船被困的主要因素,一是由于雪龙船被困区域靠近大陆架,冰山较多,多年冰和当年冰夹杂在一起,海冰类型较为复杂;二是由于受连续多个气旋影响,在雪龙船受困海域,偏东大风持续时间长,风力大,导致海冰自东向西堆积,致使雪龙船被困。 相似文献
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基于中国北极考察布放浮标观测和数值模拟的海冰和积雪厚度变化分析 总被引:1,自引:0,他引:1
Sea ice and the snow pack on top of it were investigated using Chinese National Arctic Research Expedition(CHINARE) buoy data.Two polar hydrometeorological drifters,known as Zeno? ice stations,were deployed during CHINARE 2003.A new type of high-resolution Snow and Ice Mass Balance Arrays,known as SIMBA buoys,were deployed during CHINARE 2014.Data from those buoys were applied to investigate the thickness of sea ice and snow in the CHINARE domain.A simple approach was applied to estimate the average snow thickness on the basis of Zeno~ temperature data.Snow and ice thicknesses were also derived from vertical temperature profile data based on the SIMBA buoys.A one-dimensional snow and ice thermodynamic model(HIGHTSI) was applied to calculate the snow and ice thickness along the buoy drift trajectories.The model forcing was based on forecasts and analyses of the European Centre for Medium-Range Weather Forecasts(ECMWF).The Zeno~ buoys drifted in a confined area during 2003–2004.The snow thickness modelled applying HIGHTSI was consistent with results based on Zeno~ buoy data.The SIMBA buoys drifted from 81.1°N,157.4°W to 73.5°N,134.9°W in 15 months during2014–2015.The total ice thickness increased from an initial August 2014 value of 1.97 m to a maximum value of2.45 m before the onset of snow melt in May 2015;the last observation was approximately 1 m in late November2015.The ice thickness based on HIGHTSI agreed with SIMBA measurements,in particular when the seasonal variation of oceanic heat flux was taken into account,but the modelled snow thickness differed from the observed one.Sea ice thickness derived from SIMBA data was reasonably good in cold conditions,but challenges remain in both snow and ice thickness in summer. 相似文献
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