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1.
So far, large uncertainties of the Indonesian throughflow(ITF) reside in the eastern Indonesian seas, such as the Maluku Sea and the Halmahera Sea. In this study, the water sources of the Maluku Sea and the Halmahera Sea are diagnosed at seasonal and interannual timescales and at different vertical layers, using the state-of-the-art simulations of the Ocean General Circulation Model(OGCM) for Earth Simulator(OFES). Asian monsoon leaves clear seasonal footprints on the eastern Indonesian seas. Consequently, the subsurface waters(around 24.5σ_θ and at ~150 m) in both the Maluku Sea and the Halmahera Sea stem from the South Pacific(SP) during winter monsoon, but during summer monsoon the Maluku Sea is from the North Pacific(NP), and the Halmahera Sea is a mixture of waters originating from the NP and the SP. The monsoon impact decreases with depth, so that in the Maluku Sea, the intermediate water(around 26.8σ_θ and at ~480 m) is always from the northern Banda Sea and the Halmahera Sea water is mainly from the SP in winter and the Banda Sea in summer. The deep waters(around27.2σ_θ and at ~1 040 m) in both seas are from the SP, with weak seasonal variability. At the interannual timescale,the subsurface water in the Maluku Sea originates from the NP/SP during El Ni?o/La Ni?a, while the subsurface water in the Halmahera Sea always originates from the SP. Similar to the seasonal variability, the intermediate water in Maluku Sea mainly comes from the Banda Sea and the Halmahera Sea always originates from the SP. The deep waters in both seas are from the SP. Our findings are helpful for drawing a comprehensive picture of the water properties in the Indonesian seas and will contribute to a better understanding of the ocean-atmosphere interaction over the maritime continent.  相似文献   
2.
To investigate stable isotopic variability of precipitation in Singapore, we continuously analysed the δ‐value of individual rain events from November 2014 to August 2017 using an online system composed of a diffusion sampler coupled to Cavity Ring‐Down Spectrometer. Over this period, the average value (δ18OAvg), the lowest value (δ18OLow), and the initial value (δ18OInit) varied significantly, ranging from ?0.45 to ?15.54‰, ?0.9 to ?17.65‰, and 0 to ?13.13‰, respectively. All 3 values share similar variability, and events with low δ18OLow and δ18OAvg values have low δ18OInit value. Individual events have limited intraevent variability in δ‐value (Δδ) with the majority having a Δδ below 4‰. Correlation of δ18OLow and δ18OAvg with δ18OInit is much higher than that with Δδ, suggesting that convective activities prior to events have more control over δ‐value than on‐site convective activities. The d‐excess of events also varies considerably in response to the seasonal variation in moisture sources. A 2‐month running mean analysis of δ18O reveals clear seasonal and interannual variability. Seasonal variability is associated with the meridional movement of the Intertropical Convergence Zone and evolution of the Asian monsoon. El Niño–Southern Oscillation is a likely driver of interannual variability. During 2015–2016, the strongest El Niño year in recorded history, the majority of events have a δ18O value higher than the weighted average δ18O of daily precipitation. δ18O shows a positive correlation with outgoing longwave radiation in the western Pacific and the Asian monsoon region, and also with Oceanic Niño Index. During El Niño, the convection centre shifts eastward to the central/eastern Pacific, weakening convective activities in Southeast Asia. Our study shows that precipitation δ‐value contains information about El Niño–Southern Oscillation and the Intertropical Convergence Zone, which has a significant implication for the interpretation of water isotope data and understanding of hydrological processes in tropical regions.  相似文献   
3.
This work provides a comprehensive physically based framework for the interpretation of the north Australian rainfall stable isotope record (δ18O and δ2H). Until now, interpretations mainly relied on statistical relationships between rainfall amount and isotopic values on monthly timescales. Here, we use multiseason daily rainfall stable isotope and high resolution (10 min) ground‐based C‐band polarimetric radar data and show that the five weather types (monsoon regimes) that constitute the Australian wet season each have a characteristic isotope ratio. The data suggest that this is not only due to changes in regional rainfall amount during these regimes but, more importantly, is due to different rain and cloud types that are associated with the large scale circulation regimes. Negative (positive) isotope anomalies occurred when stratiform rainfall fractions were large (small) and the horizontal extent of raining areas were largest (smallest). Intense, yet isolated, convective conditions were associated with enriched isotope values whereas more depleted isotope values were observed when convection was widespread but less intense. This means that isotopic proxy records may record the frequency of which these typical wet season regimes occur. Positive anomalies in paleoclimatic records are most likely associated with periods where continental convection dominates and convection is sea‐breeze forced. Negative anomalies may be interpreted as periods when the monsoon trough is active, convection is of the oceanic type, less electric, and stratiform areas are wide spread. This connection between variability of rainfall isotope anomalies and the intrinsic properties of convection and its large‐scale environment has important implications for all fields of research that use rainfall stable isotopes.  相似文献   
4.
Based on the ERA-Interim atmospheric reanalysis data from the European Medium-Term Weather Forecast Center from 1979 to 2016 and the ERSSTv4 sea surface temperature data from the US National Oceanic and Atmospheric Administration, the regional climate model CWRF was used to simulate the climate characteristics in East Asia. The results show that the CWRF model can well reproduce the average characteristics of the East Asian winter monsoon circulation, including the location and intensity of the low-level continental cold high pressure and variation characteristics of wind field in high and low levels. The occurrence area and frequency of the north wind in the simulation and the reanalysis data were further calculated and compared. It is shown that they are basically consistent. The distribution of air temperature and precipitation over China are well represented by the model. The water vapor transport is also in good agreement with the reanalysis data. The water vapor from the Bay of Bengal plays a vital role in the precipitation over South China. The simulation results of apparent heat source and apparent moisture sink show that the model can well simulate the thermal difference between the East Asian continent and the adjacent sea area. The analysis results indicate that CWRF model has the ability to simulate the main characteristics of the East Asian winter monsoon.  相似文献   
5.
基于同一区划方法、指标体系,使用1961—2014年辽宁省52站气象观测资料,分析辽宁省气温、气候区划指标、范围及界线的变动特征。结果表明:辽宁省年均气温在1988年发生一次突变,突变后气温开始显著上升;≥10 ℃积温日数比较显著地响应气温突变,而干燥指数、7月平均气温变化不显著。在空间分布上区划指标值均存在不同程度的变化。① 全省≥10 ℃积温日数均出现增加,但在中西部地区显著增加;② 在盘锦-抚顺一线以北(南),气候总体呈不显著变湿(干)趋势;③ 7月平均气温呈缓慢上升趋势。区划范围及界线位置出现更加显著地变化:① 暖温带范围主要向北向东扩展,中温带向东收缩;② 半湿润区范围主要向北向西扩展,半干旱区向西北方向收缩,湿润区范围基本不变;③ Tb范围显著向北向东扩展,Ta范围向北向东收缩。在此基础上分析了气候格局变化的可能气候成因,发现突变后≥10 ℃积温日数期间500 hPa高度场增加与4月和10月东亚冬季风减弱,4—10月东北冷涡持续天数增加和7月500 hPa高度场增加,可能分别是温度带,Tb区、Ta区和半湿润区、半干旱区变化的原因。  相似文献   
6.
基于非结构有限体积法海洋模型FVCOM(Finite-Volume Community Ocean Model), 建立了马六甲海峡及其毗邻海域高分辨率水动力数值模型, 研究了风和潮流作用下的余环流结构以及水体输运特征。结果表明, 马六甲海峡航道中央潮流运动以往复流为主, 边缘存在旋转流; 主要研究区域内落潮流速略大于涨潮流速, 东南窄道处流速最大; 因峡道束窄变浅, 在涨落潮过程中潮流发生汇聚与分离; 主要研究区域东南段存在3个显著的潮致余环流; 东北季风驱动时模型响应为海峡海流整体向西北方向流动, 西南季风时反之; 季风期间潮致表层余环流结构被破坏, 但底层余流仍存在水平环流结构, 且随着风速增加, 底层余环流的数目、大小、形状、位置均会产生变化; 季风过渡期余环流结构也会发生部分改变, 尤其是小潮期间风场影响效果显著。  相似文献   
7.
The confounding effects of step change invalidate the stationarity assumption of commonly used trend analysis methods such as the Mann–Kendall test technique, so previous studies have failed to explain inconsistencies between detected trends and observed large precipitation anomalies. The objectives of this study were to (1) formulate a trend analysis approach that considers nonstationarity due to step changes, (2) use this approach to detect trends and extreme occurrences of precipitation in a mid‐latitude Eurasian steppe watershed in North China, and (3) examine how runoff responds to precipitation trends in the study watershed. Our results indicate that annual precipitation underwent a marginal step jump around 1995. The significant annual downward trend after 1994 was primarily due to a decrease in summer rainfall; other seasons exhibited no significant precipitation trends. At a monthly scale, July rainfall after 1994 exhibited a significant downward trend, whereas precipitation in other months had no trend. The percentage of wet days also underwent a step jump around 1994 following a significant decreasing trend, although the precipitation intensity exhibited neither a step change nor any significant trend. However, both low‐frequency and high‐frequency precipitation events in the study watershed occurred more often after than before 1994; probably as either a result or an indicator of climate change. In response to these precipitation changes, the study watershed had distinctly different precipitation‐runoff relationships for observed annual precipitations of less than 300 mm, between 300 and 400 mm, and greater than 400 mm. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   
8.
9.
高原季风特征及其与东亚夏季风关系的研究   总被引:1,自引:0,他引:1  
利用ERA-Interim的位势高度场、温度场和风场再分析资料,计算了1988-2017年的传统高原季风指数(Trational Plateau Monsoon Index,TPMI)和动态高原季风指数(Dynamic Plateau Monsoon Index,DPMI),分析了高原季风的空间分布特征和时间演变规律,结合东亚夏季风指数(East Asian Summer Monsoon Index,EASMI),探讨了高原季风与东亚季风的关系。研究表明:(1)高原夏季风从4月开始形成,暖性低值系统在高原上生成;6月暖性低压系统中心形成并达到最强,此时高原夏季风强度也达到最大;10月暖性闭合低压系统向东北方向移动且强度也随之减弱并退出,高原夏季风结束。(2)DPMI和EASMI具有明显的年际变化特征,在关键年高原夏季风和东亚夏季风的强度表现一致。(3)中纬度受东亚季风所影响区域的位势高度场和青藏高原区域的位势高度场均处于同一正相关区域,而且超前两个月的DPMI同EASMI的相关系数最大,表明高原夏季风对东亚夏季风具有一定的指示意义。(4)东亚夏季风经圈环流受高原温度场变化的影响而移动,高原夏季风的低压系统与高原温度场关系密切。  相似文献   
10.
乔梁  张强  岳平  金红梅 《大气科学》2019,43(2):251-265
利用中国西北中部具有代表性的非季风区、夏季风影响过渡区和季风区的7个高空站的2013年夏季晴天07时、13时、19时(北京时)的大气边界层资料,通过分析大气边界层位温、比湿、风速的垂直结构,发现大气边界层结构及厚度在不同区域的分布特征:稳定边界层厚度、残余层顶高度和对流边界层厚度从非季风区、夏季风影响过渡区至季风区出现阶梯性大幅降低,从非季风区至夏季风影响过渡区,以及从夏季风影响过渡区至季风区,对流边界层厚度降幅依次为25.6%和81.8%,稳定边界层厚度降幅依次为58.3%和41.8%;在稳定边界层条件下,可观察到低空急流的存在,非季风区低空急流出现高度明显高于夏季风影响过渡区和季风区,且非季风区的低空急流风速也明显大于夏季风影响过渡区和季风区。通过分析与大气边界层发展最为密切的陆面热力因素在不同气候区的分布,净辐射值、日地-气温差最大值以及感热通量值在非季风区大于夏季风影响过渡区和季风区,从陆面热力过程为非季风区大气边界层厚度大于夏季风影响过渡区和季风区提供了理论依据。  相似文献   
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