Mean monthly wind driven climatological circulation model of the Bay of Bengal

A special feature of the Bay of Bengal circulation is its seasonal variation in response to the monsoonal winds. In the case of the Bay of Bengal, observationally very little is known about the large scale circulation. Theoretically, the problem of driving the circulation in the Bay of Bengal is more complex than that in other basins because of the presence of large quantities of fresh water discharge from Ganga-Brahmaputra-Meghna river systems, and also because the atmospheric driving forces even within a season are highly variable with frequent occurrences of tropical disturbances. Exploring the nature of the circulation in the Bay of Bengal is a problem of great importance in itself as well as for the critical role this region plays in the genesis of tropical disturbances which are the main source of large scale rainfall over the northern part of the Indian subcontinent. The surface circulation of the Bay of Bengal may, therefore, help in understanding the variation of rainfall over time scales ranging from the subseasonal to the interannual. Keeping this in view, an attempt was made towards the development of an oceanic climatological circulation model for the Bay of Bengal, which explains the seasonal variability of the currents. The model is fully non-linear and vertically integrated, with realistic basin geometry. The treatment of coastal boundaries involves a procedure leading to a realistic curvilinear representation of the western and eastern sides of the Bay of Bengal. This coastal representation has the advantage of taking into account the finer resolution in the shallow regions of the northern Bay. The model is forced by the monthly mean wind stress derived from 30 years (1950–79) of Comprehensive Oceanographic Atmospheric Data Sets (COADS). Special emphasis is given to the southern open boundary condition for the model. For this purpose, sensitivity experiments have been performed with six open boundary conditions and a comparative study of the results has been made. These sensitivity tests for the open boundary condition will help the development of a suitable coupled ocean-atmosphere model for this region. The model-generated main features are in general agreement with the known climatological circulation of the Bay of Bengal.     

Historic and Future Perspectives of Storm and Cyclone

In weather sciences, the two specific terms “storm” and “cyclone” frequently appear in literature and usually refer to the violent nature of a number of weather systems characterized by central low pressure, strong winds, large precipitation amounts in the form of rain, freezing rain, or snow, as well as thunder and lightning. But what is the connection between these two specific terms? In this paper, the historic evolutions of the terms “storm” and “cyclone” are reviewed from the perspective of...     

贵州省分月太阳辐射参数模型计算

利用贵州省2011—2015年10个太阳辐射站观测资料,采用最小二乘法分月拟合太阳辐射计算参数a、b,结合相应站点的地理信息(纬度和海拔高度),建立参数随地理位置变化的分月模型,进行1962—1990年威宁站独立样本检验,利用2001—2010年贵阳站数据与海拔分区法进行比较;结合1981—2010年85个常规气象站日照时数资料和相应站点的地理信息推算累年各月太阳总辐射量,并探讨其空间分布规律。结果表明:用分月参数模型计算贵州省太阳辐射误差更小、精度更高,提高了太阳辐射计算的准确率;贵州省气象台站年平均太阳总辐射在3415.76~4737.04 MJ·m~(-2)之间,西部和西南部多,北部少,其中年总辐射最大值出现在威宁,最低值出现在务川。     

近50年安徽省太阳总辐射的时空变化特征

采用1961—2010年安徽省辐射观测数据和常规气象要素观测资料,建立了太阳总辐射的气候学计算方法;进而推算了安徽省各地太阳总辐射,并采用趋势分析、突变检验和小波分析等方法研究了其时空变化特征。结果表明:以理论天文辐射为起始值所建立的全省统一公式,能够较好的拟合安徽省月尺度的太阳总辐射值。根据公式推算的安徽省各地太阳总辐射资源的丰富程度以3级为主,空间分布呈北多南少的特征,季节分布为夏多冬少单峰型,但在梅雨期存在波谷。近50年来安徽省各地太阳总辐射量基本呈一致的减少趋势,全省平均下降趋势为每10年减少0.31 MJ·m-2·d-1,近年来辐射下降趋缓。安徽省太阳总辐射在20世纪80年代初存在一次突变现象;近50年总辐射量以准10年和4~6年左右周期振荡较为明显,而20世纪80年代以来年代际振荡信号减弱,并且太阳总辐射气候态以偏少为主。     

近40年潍坊地区雷暴日的气候特征

利用潍坊地区不同地理位置的 4测站观测资料 ,分析了 1 96 0～ 1 999年 (4 0年 )潍坊地区初、终雷暴日各地域的差异和变化趋势。结果表明 :初雷暴日 4 0年提前了 8天 ,终雷暴日变化趋势呈抛物线型 ;雷暴期各地域不同 ,基本规律是 :寿光 >青州 >诸城 >潍坊 ;雷暴日的年均频数寿光 2 8 0天 ,青州 2 7 5天 ,诸城 2 6 5天 ,潍坊 2 6 3天 ,平均倾向率每 1 0年 - 1 2天 ;雷暴频数的月分布呈单峰形 ,前半夏沿海大于山区 ,后半夏山区大于沿海 ;候平均气温上升 (下降 )稳定通过 8℃ ,是初雷暴日 (终雷暴日 )的温度阈值     

Climatological characteristics of monsoons and tropical cyclone activities over China seas and their influences on hydrological and seasonal structures over the South China Sea

The aim of this paper is to study whether the features of perennial summer over the South China Sea remain constant all the year round or not , and whether there are any seasonal differences throughout the year or not. According to the characteristics of remarkable monsoon and frequent typhoon, the influences of monsoon and tropical cyclone on the hydrological features and the seasonal structure over the South China Sea are analysed by using examples. It may be considered that in the perennial summer area over the South China Sea, it is summer all the year round, but it does not remain constant throughout the year. On the basis of index dates of developing stages for winter and summer monsoons as well as the seasonal characteristics of typhoon frequency,the perennial summer season over the South China Sea may be divided into four periods, namely, early summer, midsummer, sweltering summer and late summer. The concrete classification and the hydrological seasonal feature of each period are discussed.     

Climatological annual cycles of nutrients and chlorophyll in the North Sea

A large amount of nutrient and chlorophyll data from the North Sea were compiled and organised in a research data base to produce annual cycles on a relatively fine spatial resolution of 1° in each horizontal direction. The data originate from many different sources and were partly provided by the ECOMOD data base of the Institut fur Meereskunde in Hamburg and partly by ICES in Copenhagen to cover the time range from 1950 to 1994. While the annual cycles of nutrients and chlorophyll derived for the continental coastal zone are representative for the decade 1984–1993 only, those for the remaining parts of the North Sea may be considered climatological annual cycles based on data from more than four decades. The composite data set of climatological annual cycles of medians and their climatological ranges is well suited to serve for validational and forcing purposes for ecosystem models of the North Sea, which have a resolution larger than or equal to 1° in both longitude and latitude. The annual cycles of the macronutrients and chlorophyll presented here for 1° × 1° squares in the North Sea show especially that sufficient observational data exist to provide initial, forcing and validational data for the simulations with the 130-box setup (ND130) of the ecosystem model ERSEM. The annual cycles presented give a clear picture for the whole of the North Sea. The highest concentrations occur at the continental coasts as a result of continued river input, which is added to the ongoing atmospheric input over the North Sea. Also, from the Atlantic Ocean water with relatively high nutrient concentrations enters the North Sea via the northern boundary. In the productive areas on and around the Dogger Bank nutrient concentrations are lower than in the other parts of the North Sea, even in winter. The areas with seasonal stratification have very different annual cycles in the upper (0–30 m) and lower layers (30 m-bottom). The shallow boxes are fully mixed and exhibit a relatively fast increase of nutrient concentrations caused by summer regeneration of nutrients.     

Importance of Reference Dataset Improvements for Argo Delayed-Mode Quality Control

For the Argo Project, monitoring the global upper ocean by a large number of profiling floats, maintaining the quality of salinity data is critical; the goal for measurement accuracy is ±0.01. Experiments using the method of Wong et al. (2003), the standard delayed-mode quality control (dQC) for the Project, show that its performance depends critically on the reference datasets used. This study concludes that the method is useful for Argo and has sufficient potential to achieve the goal for salinity measurement in the North Pacific, when suitable reference datasets are prepared. Considering the Wong et al. (2003) algorithms, we suggest that reference datasets with the following characteristics will be most suitable for Argo dQC: They should be basically derived from the most extensive datasets, such as the latest World Ocean Database; in regions with denser observations, datasets with carefully quality controls should be used; in the regions with subsurface temperature inversions, such as the subarctic North Pacific, the profiles used for the reference must extend below the deepest temperature maximum to prepare proper salinities for the deep layer reference.     

1962—2017年恩平市气温与降水的气候特征

采用数理统计、线性趋势、复Morlet小波变换、M-K突变检验和滑动平均T检验等方法,分析了恩平市1962—2017年气温和降水的气候特征,结果表明:恩平市近56年年平均气温上升趋势极端显著,在1993年发生由偏低向偏高的突变,并包含13、9、4年左右的多重周期变化。气温波动的幅度先增大后减小,气温冷和暖的年份相对集中。年、汛期、前汛期、后汛期降水均呈递减趋势,在1999年年降水发生由偏多向偏少的突变,并包含20、13、10、5、3年左右的多重周期变化。年降水呈Weibull分布,50年一遇年降水对应重现期的雨量阈值为3 665.6 mm。近10年年平均气温呈自东向西降低分布,年平均降水呈自西南向东北递减分布。     

A descriptive analysis of temporal and spatial patterns of variability in Puget Sound oceanographic properties

Temporal and spatial patterns of variability in Puget Sound's oceanographic properties are determined using continuous vertical profile data from two long-term monitoring programs; monthly observations at 16 stations from 1993 to 2002, and biannual observations at 40 stations from 1998 to 2003. Climatological monthly means of temperature, salinity, and density reveal strong seasonal patterns. Water temperatures are generally warmest (coolest) in September (February), with stations in shallow finger inlets away from mixing zones displaying the largest temperature ranges. Salinities and densities are strongly influenced by freshwater inflows from major rivers during winter and spring from precipitation and snowmelt, respectively, and variations are greatest in the surface waters and at stations closest to river mouths. Vertical density gradients are primarily determined by salinity variations in the surface layer, with stations closest to river mouths most frequently displaying the largest buoyancy frequencies at depths of approximately 4–6 m. Strong tidal stirring and reflux over sills at the entrance to Puget Sound generally removes vertical stratification. Mean summer and winter values of oceanographic properties reveal patterns of spatial connectivity in Puget Sound's three main basins; Whidbey Basin, Hood Canal, and Main Basin. Surface waters that are warmed in the summer are vertically mixed over the sill at Admiralty Inlet and advected at depth into Whidbey Basin and Hood Canal. Cooler and fresher surface waters cap these warmer waters during winter, producing temperature inversions.