1208号台风“韦森特”异常路径及其对珠三角南部暴雨影响成因分析

利用1°×1°NCEP再分析资料、全省遥测站资料、卫星云图、香港雷达图等资料,分析台风“韦森特”的环流背景场、物理量场特征,找出“韦森特”在南海中北部原地摆动和对珠三角南部强降水过程的物理成因：“韦森特”的原地摆动,与副热带高压、南海中部海温、还有台风内在的云系和风场结构的不对称有关;珠三角地区两侧附近存在弱的水汽通量辐合,在降水中心附近存在明显的上升运动,低层辐合、高层辐散,另外垂直螺旋场与降水中心的第一段降水期具有很好的对应关系.     

地温异常数据原因分析及处理方法

针对地温异常数据种类,结合天气学原理、气象要素的时间、空间变化规律和各要素间相互联系的规律进行分析,找出导致异常数据原因,提出相应的处理方法,尽可能使缺测的要素及缺测时次减小到最小值,最大限度地保证资料的完整.     

1957—2011年牙克石市低温气候特征分析

文章主要通过利用牙克石市1957—2011年(历年1—3、11—12月)的低温气候资料进行分析,找出牙克石市近55a来的低温气候变化特点。得出了低温天数的年、月变化以及与极端最低气温的对应关系,牙克石55a来共计出现低温天气673d,低温日数年际变化大,最长为47d,最少为1d,低温出现的高峰期在历年的1月份,低温强度最大值也在1月份。55a中≤-37℃低温最长连续日数长达17d,其次是13d。文章还利用Mann-kendall检验方法对低温年际变化进行了突变分析,分析发现在1984年发生了明显的突变,突变呈减少的趋势。     

ANNUAL VARIATIONS OF TEMPERATURE ON FOUR URBAN UNDERLYING SURFACES AND FITTING ANALYSIS

Based on the observed 2-year temperature data for four kinds of typical urban underlying surfaces, including asphalt, cement, bare land and grass land, the annual variations and influencing factors of land surface temperature are analyzed. Then fitting equations for surface temperature are established. It is shown that the annual variation of daily average, maximum and minimum temperature and daily temperature range on the four urban underlying surfaces is consistent with the change in air temperature. The difference of temperature on different underlying surfaces in the summer half year (May to October) is much more evident than that in the winter half year (December to the following April). The daily average and maximum temperatures of asphalt, cement, bare land and grass land are higher than air temperature due to the atmospheric heating in the daytime, with that of asphalt being the highest, followed in turn by cement, bare land and grass land. Moreover, the daily average, maximum and minimum temperature on the four urban underlying surfaces are strongly impacted by total cloud amount, daily average relative humidity and sunshine hours. The land surface can be cooled (warmed) by increased total cloud amount (relative humidity). The changes in temperature on bare land and grass land are influenced by both the total cloud amount and the daily average relative humidity. The temperature parameters of the four land surfaces are significantly correlated with daily average, maximum and minimum temperature, sunshine hours, daily average relative humidity and total cloud amount, respectively. The analysis also indicates that the range of fitting parameter of a linear regression equation between the surface temperature of the four kinds of typical land surface and the air temperature is from 0.809 to 0.971, passing the F-test with a confidence level of 0.99.     

Intraseasonal Oscillation in Global Ocean Temperature Inferred from Argo

The intraseasonal oscillation(ISO;14-97-day periods) of temperature in the upper 2000 m of the global ocean was studied based on Argo observations from 2003-2008.It is shown that near the surface the ISO existed mainly in a band east of 60 E,between 10 S and 10 N,and the region around the Antarctic Circumpolar Current(ACC).At other levels analyzed,the ISOs also existed in the regions of the Kuroshio,the Gulf Stream,the Indonesian throughflow,the Somalia current,and the subtropical countercurrent(STCC) of the North Pacific.The intraseasonal signals can be seen even at depths of about 2000 m in some regions of the global ocean.The largest amplitude of ISO appeared at the thermocline of the equatorial Pacific,Atlantic and Indian Ocean,with maximum standard deviation(STD) exceeding 1.2 C.The ACC,the Kuroshio,and the Gulf Stream regions all exhibited large STD for all levels analyzed.Especially at 1000 m,the largest STD appeared in the south and southeast of South Africa-a part of the ACC,with a maximum value that reached 0.5 C.The ratios of the intraseasonal temperature variance to the total variance at 1000 m and at the equator indicated that,in a considerable part of the global deep ocean,the ISO was dominant in the variations of temperature,since such a ratio exceeded even 50% there.A case study also confirmed the existence of the ISO in the deep ocean.These results provide useful information for the design of field observations in the global ocean.Analysis and discussion are also given for the mechanism of the ISO.     

Statistical downscaling of summer temperature extremes in northern China

Two approaches of statistical downscaling were applied to indices of temperature extremes based on percentiles of daily maximum and minimum temperature observations at Beijing station in summer during 1960-2008. One was to downscale daily maximum and minimum temperatures by using EOF analysis and stepwise linear regression at first, then to calculate the indices of extremes; the other was to directly downscale the percentile-based indices by using seasonal large-scale temperature and geo-potential height records. The cross-validation results showed that the latter approach has a better performance than the former. Then, the latter approach was applied to 48 meteorological stations in northern China. The cross-validation results for all 48 stations showed close correlation between the percentile-based indices and the seasonal large-scale variables. Finally, future scenarios of indices of temperature extremes in northern China were projected by applying the statistical downscaling to Hadley Centre Coupled Model Version 3 (HadCM3) simulations under the Representative Concentration Pathways 4.5 (RCP 4.5) scenario of the Fifth Coupled Model Inter-comparison Project (CMIP5). The results showed that the 90th percentile of daily maximum temperatures will increase by about 1.5℃, and the 10th of daily minimum temperatures will increase by about 2℃ during the period 2011-35 relative to 1980-99.     

Oceanic climatology in the coupled model FGOALS-g2: Improvements and biases

The present study examines simulated oceanic climatology in the Flexible Global Ocean-Atmosphere-Land System model, Grid-point Version 2 (FGOALS-g2) forced by historical external forcing data. The oceanic temperatures and circulations in FGOALS-g2 were found to be comparable to those observed, and substantially improved compared to those simulated by the previous version, FGOALS-g1.0. Compared with simulations by FGOALS-g1.0, the shallow mixed layer depths were better captured in the eastern Atlantic and Pacific Ocean in FGOALS-g2. In the high latitudes of the Northern Hemisphere, the cold biases of SST were about 1°C–5°C smaller in FGOALS-g2. The associated sea ice distributions and their seasonal cycles were more realistic in FGOALS-g2. The pattern of Atlantic Meridional Overturning Circulation (AMOC) was better simulated in FGOALS-g2, although its magnitude was larger than that found in observed data. The simulated Antarctic Circumpolar Current (ACC) transport was about 140 Sv through the Drake Passage, which is close to that observed. Moreover, Antarctic Intermediate Water (AAIW) was better captured in FGOALS-g2. However, large SST cold biases (>3°C) were still found to exist around major western boundary currents and in the Barents Sea, which can be explained by excessively strong oceanic cold advection and unresolved processes owing to the coarse resolution. In the Indo-Pacific warm pool, the cold biases were partly related to the excessive loss of heat from the ocean. Along the eastern coast in the Atlantic and Pacific Oceans, the warm biases were due to overestimation of shortwave radiation. In the Indian Ocean and Southern Ocean, the surface fresh biases were mainly due to the biases of precipitation. In the tropical Pacific Ocean, the surface fresh biases (>2 psu) were mainly caused by excessive precipitation and oceanic advection. In the Indo-Pacific Ocean, fresh biases were also found to dominate in the upper 1000 m, except in the northeastern Indian Ocean. There were warm and salty biases (3°C–4°C and 1–2 psu) from the surface to the bottom in the Labrador Sea, which might be due to large amounts of heat transport and excessive evaporation, respectively. For vertical structures, the maximal biases of temperature and salinity were found to be located at depths of >600 m in the Arctic Ocean, and their values exceeded 4°C and 2 psu, respectively.     

一维热扩散湖模式在太湖的应用研究

利用在太湖获得的2010年8月11-28日的观测资料研究了一维热扩散湖模式在太湖的适用性,通过对比模拟进一步研究了影响太湖湖表温度模拟的主要因子。该湖模式对太湖最初的模拟结果并不理想,模拟的湖表面温度与观测有较大的系统性偏差,温度的日变化幅度与观测相比也偏小。通过分析该模式对太湖的模拟效果不理想的可能原因,针对太湖的生态环境和污染情况,设计了18个测试参数的敏感性试验,从敏感性试验的结果分析得到,适用于太湖的、依赖于湖泊类型的3个参数应做如下修改:消光系数（η₀）应放大3倍,湖泊表层吸收的太阳辐射系数（β）应取0.8,粗糙长度（z₀）采用公式计算得到。用新得到的适用于太湖的3个参数,模拟得到的结果与最初的模拟结果和观测资料对比,发现采用新的参数后,模拟结果比最初的模拟结果有了很大的改进,模拟的湖表温度基本接近观测,模拟的湖水垂直剖面时间序列图也跟观测吻合得较好,随之的感热、潜热通量的模拟也都与观测接近。最后,对输入湖模式的主要大气参量（太阳辐射、2 m气温及风场）±10%的误差引起的模式模拟的湖表面温度误差进行分析,结果表明该湖模式对大气强迫场的误差敏感度不高;相比之下,模拟结果对风场敏感性最小,对辐射和气温的敏感度相当。     

Recent trends in winter temperature extremes in eastern China and their relationship with the Arctic Oscillation and ENSO

Interannual variations in the number of winter extreme warm and cold days over eastern China （EC） and their relationship with the Arctic Oscillation （AO） and E1 Nifio-Southern Oscillation （ENSO） were investigated using an updated temperature dataset comprising 542 Chinese stations during the period 1961- 2011. Results showed that the number of winter extreme warm （cold） days across EC experienced a significant increase （decrease） around the mid-1980s, which could be attributed to interdecadal variation of the East Asian Winter Monsoon （EAWM）. Probability distribution functions （PDFs） of winter temperature extremes in different phases of the AO and ENSO were estimated based on Generalized Extreme Value Distribution theory. Correlation analysis and the PDF technique consistently demonstrated that interannual variation of winter extreme cold days in the northern part of EC （NEC） is closely linked to the AO, while it is most strongly related to the ENSO in the southern part （SEC）. However, the number of winter extreme warm days across EC has little correlation with both AO and ENSO. Furthermore, results indicated that, whether before or after the mid-1980s shift, a significant connection existed between winter extreme cold days in NEC and the AO. However, a significant connection between winter extreme cold days in SEC and the ENSO was only found after the mid-1980s shift. These results highlight the different roles of the AO and ENSO in influencing winter temperature extremes in different parts of EC and in different periods, thus providing important clues for improving short-term climate prediction for winter temperature extremes.