海洋平流的季节变化对La Nia事件成熟位相锁定的作用

用一个中等复杂程度的热带海气耦合模式模拟LaNi na事件成熟位相锁定在年底左右的特征并研究其形成的机制。结果表明 ,模式能很好地模拟观测到的LaNi na事件成熟位相锁定在年底左右的特征。LaNi na事件成熟位相锁定在年底主要由海洋气候基本态引起。海洋垂直平均流是LaNi na事件成熟位相锁定在年底左右的最主要因子。由海洋气候基本态的季节变化所引起的冷平流的季节变化是LaNi na事件成熟位相锁定在年底的机制。在LaNi na事件期间 ,1～ 5月份 ,赤道中东太平洋地区的冷平流较弱 ,它不能平衡海气热量交换过程的影响 ,因而海洋表面温度增加。这一过程使海气耦合不稳定度减弱 ,从而使LaNi na事件衰减。 6～ 12月份 ,赤道中东太平洋地区的冷平流较强。海气热量交换过程的影响不能平衡较强冷平流的影响 ,因而海洋表面温度减小。这一过程使海气耦合不稳定度加强 ,从而使LaNi na事件发展。这样 ,LaNi na事件成熟位相容易出现在年底左右。     

Temporal Characteristics of Pacific Decadal Oscillation (PDO) and ENSO and Their Relationship Analyzed with Method of Empirical Mode Decomposition (EMD)

1. IntroductionPacific Decadal Oscillation (PDO) is a long-termENSO-like variability of the North Pacific. It can becharacterized by the first principal component of EOFof the North Pacific SST (Zhu and Yang, 2003; Tren-berth, 1990; Yang and Zhang, 2003). ENSO is thestrongest signal of annular change of global climatesystem (Trenberth, 1997). The spatial pattern of PDOis a wedge similar to El Nino. In the cool (warm)phases of PDO, the central and northwest Pacific is ofwarm (co…     

泥浆脉冲随钻测量系统研究

介绍了泥浆脉冲随钻测量系统信号传输的3种基本工作方式:压力正脉冲、压力负脉冲和连续压力波.泥浆脉冲信号在传输过程中主要受钻探泵、井底动力机、泥浆中的气泡及活动钻具的干扰;钻井深度、泥浆中的气泡量、含砂量和泥浆类型对信号衰减有一定的影响.     

Quantifying flows along hydrological pathways by applying a new filtering algorithm in conjunction with master recession curve analysis

Quantifying the proportion of the river hydrograph derived from the different hydrological pathways is essential for understanding the behaviour of a catchment. This paper describes a new approach using the output from master recession curve analysis to inform a new algorithm based on the Lyne and Hollick ‘one‐parameter’ signal analysis filtering algorithm. This approach was applied to six catchments (including two subcatchments of these) in Ireland. The conceptual model for each catchment consists of four main flow pathways: overland flow, interflow, shallow groundwater and deep groundwater. The results were compared with those of the master recession curve analysis, a recharge coefficient approach developed in Ireland and the semi‐distributed, lumped and deterministic hydrological model Nedbør‐Afstrømings‐Model. The new algorithm removes the ‘free variable’ aspect that is typically associated with filtering algorithms and provides a means of estimating the contribution of each pathway that is consistent with the results of hydrograph separation in catchments that are dominated by quick response pathways. These types of catchments are underlain by poorly productive aquifers that are not capable of providing large baseflows in the river. Such aquifers underlie over 73% of Ireland, ensuring that this new algorithm is applicable in the majority of catchments in Ireland and potentially in those catchments internationally that are strongly influenced by the quick‐responding hydrological pathways. Copyright © 2013 John Wiley & Sons, Ltd.     

Spatio‐temporal variability of the isotopic input signal in a partly forested catchment: Implications for hydrograph separation

The isotopic composition of precipitation (D and ¹⁸O) has been widely used as an input signal in water tracer studies. Whereas much recent effort has been put into developing methodologies to improve our understanding and modelling of hydrological processes (e.g., transit‐time distributions or young water fractions), less attention has been paid to the spatio‐temporal variability of the isotopic composition of precipitation, used as input signal in these studies. Here, we investigated the uncertainty in isotope‐based hydrograph separation due to the spatio‐temporal variability of the isotopic composition of precipitation. The study was carried out in a Mediterranean headwater catchment (0.56 km²). Rainfall and throughfall samples were collected at three locations across this relatively small catchment, and stream water samples were collected at the outlet. Results showed that throughout an event, the spatial variability of the input signal had a higher impact on hydrograph separation results than its temporal variability. However, differences in isotope‐based hydrograph separation determined preevent water due to the spatio‐temporal variability were different between events and ranged between 1 and 14%. Based on catchment‐scale isoscapes, the most representative sampling location could also be identified. This study confirms that even in small headwater catchments, spatio‐temporal variability can be significant. Therefore, it is important to characterize this variability and identify the best sampling strategy to reduce the uncertainty in our understanding of catchment hydrological processes.     

Tropical precipitation anomalies and d‐excess evolution during El Niño 2014‐16

The last 2014‐16 El Niño event was among the three strongest episodes on record. El Niño considerably changes annual and seasonal precipitation across the tropics. Here, we present a unique stable isotope data set of daily precipitation collected in Costa Rica prior to, during, and after El Niño 2014‐16, in combination with Lagrangian moisture source and precipitation anomaly diagnostics. δ²H composition ranged from ‐129.4 to +18.1 (‰) while δ¹⁸O ranged from ‐17.3 to +1.0 (‰). No significant difference was observed among δ¹⁸O (P=0.186) and δ²H (P=0.664) mean annual compositions. However, mean annual d‐excess showed a significant decreasing trend (from +13.3 to +8.7 ‰) (P<0.001) with values ranging from +26.6 to ‐13.9 ‰ prior to and during the El Niño evolution. The latter decrease in d‐excess can be partly explained by an enhanced moisture flux convergence across the southeastern Caribbean Sea coupled with moisture transport from northern South America by means of an increased Caribbean Low Level Jet regime. During 2014‐15, precipitation deficit across the Pacific domain averaged 46% resulting in a very severe drought; while a 94% precipitation surplus was observed in the Caribbean domain. Understanding these regional moisture transport mechanisms during a strong El Niño event may contribute to a) better understanding of precipitation anomalies in the tropics and b) re‐evaluate past stable isotope interpretations of ENSO events in paleoclimatic archives within the Central America region.     

无人机信号传输中断解决方案研究

在福建地区从事无人机低空数码航空摄影测量项目时,我们发现数传电台信号中断是无人机飞行的一个重大安全隐患。如不能实时掌握无人机飞行动态,出现异常状况时不能第一时间处理,极有可能出现安全事故,造成重大损失。本文通过具体案例说明,提出无人机信号传输中断的解决方案。     

Weak ENSO Asymmetry Due to Weak Nonlinear Air–Sea Interaction in CMIP5 Climate Models

State-of-the-art climate models have long-standing intrinsic biases that limit their simulation and projection capabilities.Significantly weak ENSO asymmetry and weakly nonlinear air–sea interaction over the tropical Pacific was found in CMIP5(Coupled Model Intercomparison Project, Phase 5) climate models compared with observation. The results suggest that a weak nonlinear air–sea interaction may play a role in the weak ENSO asymmetry. Moreover, a weak nonlinearity in air–sea interaction in the models may be associated with the biases in the mean climate—the cold biases in the equatorial central Pacific. The excessive cold tongue bias pushes the deep convection far west to the western Pacific warm pool region and suppresses its development in the central equatorial Pacific. The deep convection has difficulties in further moving to the eastern equatorial Pacific, especially during extreme El Ni o events, which confines the westerly wind anomaly to the western Pacific. This weakens the eastern Pacific El Ni o events, especially the extreme El Ni o events, and thus leads to the weakened ENSO asymmetry in climate models. An accurate mean state structure(especially a realistic cold tongue and deep convection) is critical to reproducing ENSO events in climate models. Our evaluation also revealed that ENSO statistics in CMIP5 climate models are slightly improved compared with those of CMIP3. The weak ENSO asymmetry in CMIP5 is closer to the observation. It is more evident in CMIP5 that strong ENSO activities are usually accompanied by strong ENSO asymmetry, and the diversity of ENSO amplitude is reduced.     

Long-Term Variability of the Wind Field over the Indian Ocean Based on ERA-Interim Reanalysis

A detailed study of long-term variability of winds using 30 years of data from the European Centre for Medium-range Weather Forecasts global reanalysis (ERA-Interim) over the Indian Ocean has been carried out by partitioning the Indian Ocean into six zones based on local wind extrema. The trend of mean annual wind speed averaged over each zone shows a significant increase in the equatorial region, the Southern Ocean, and the southern part of the trade winds. This indicates that the Southern Ocean winds and the southeast trade winds are becoming stronger. However, the trend for the Bay of Bengal is negative, which might be caused by a weakening of the monsoon winds and northeast trade winds. Maximum interannual variability occurs in the Arabian Sea due to monsoon activity; a minimum is observed in the subtropical region because of the divergence of winds. Wind speed variations in all zones are weakly correlated with the Dipole Mode Index (DMI). However, the equatorial Indian Ocean, the southern part of the trade winds, and subtropical zones show a relatively strong positive correlation with the Southern Oscillation Index (SOI), indicating that the SOI has a zonal influence on wind speed in the Indian Ocean. Monsoon winds have a decreasing trend in the northern Indian Ocean, indicating monsoon weakening, and an increasing trend in the equatorial region because of enhancement of the westerlies. The negative trend observed during the non-monsoon period could be a result of weakening of the northeast trade winds over the past few decades. The mean flux of kinetic energy of wind (FKEW) reaches a minimum of about 100?W?m^?2 in the equatorial region and a maximum of about 1500?W?m^?2 in the Southern Ocean. The seasonal variability of FKEW is large, about 1600?W?m^?2, along the coast of Somalia in the northern Indian Ocean. The maximum monthly variability of the FKEW field averaged over each zone occurs during boreal summer. During the onset and withdrawal of monsoon, FKEW is as low as 50?W?m^?2. The Southern Ocean has a large variation of about 1280?W?m^?2 because of strong westerlies throughout the year.