Large-sample hydrology: recent progress,guidelines for new datasets and grand challenges

ABSTRACT

Large-sample hydrology (LSH) relies on data from large sets (tens to thousands) of catchments to go beyond individual case studies and derive robust conclusions on hydrological processes and models. Numerous LSH datasets have recently been released, covering a wide range of regions and relying on increasingly diverse data sources to characterize catchment behaviour. These datasets offer novel opportunities, yet they are also limited by their lack of comparability, uncertainty estimates and characterization of human impacts. This article (i) underscores the key role of LSH datasets in hydrological studies, (ii) provides a review of currently available LSH datasets, (iii) highlights current limitations of LSH datasets and (iv) proposes guidelines and coordinated actions to overcome these limitations. These guidelines and actions aim to standardize and automatize the creation of LSH datasets worldwide, and to enhance the reproducibility and comparability of hydrological studies.     

海洋沉积物动力学的示踪物方法

本文的论题是示踪物方法在海洋物源追踪和沉积物输运率计算中的应用 ,以及示踪物方法的普适性理论框架。定量的物源追踪需要适当的示踪标记和物质混合模型 ,有必要根据沉积动力过程的研究来确定示踪标记的变换函数 ,从而将改进的示踪标记用于混合模型分析。人工示踪物实验的现有方法以空间积分法最为常用 ,其关键是示踪物质心运动和沉积物活动层的界定。天然示踪物的质心位置是无法定义的 ,因此不能借用传统人工示踪物方法来估算物质输运率 ;在某些特殊情形下 ,可以利用天然示踪物的质量守衡原理来获得物质输运信息。今后 ,以示踪物质的连续方程为基础 ,有可能建立一种同时适用于人工和天然示踪物的普适理论框架。其中需解决的问题包括示踪物与现场物质的差异、沉积速率和活动层厚度的时间尺度、沉积物扩散过程等。     

La prévision du climat : de l'échelle saisonnière à l'échelle décennale

The atmosphere and the ocean are subject to many dynamical instabilities, which limit the time during which their behaviour can be deterministically forecasted. At longer timescales, the atmosphere can be predicted at best using statistical methods, as a response to external forcing linked to sea- and land-surface anomalies. Climate being defined as the mean of atmospheric states, it appears that it can be predicted up to a few months in advance, which is the characteristic time of the so-called slow components of the climate system. Forecasting can sometimes be extended to longer time ranges, especially when the coupled ocean–atmosphere system exhibits internal variability modes, with characteristic times of a few years. Seasonal climate forecasting is most often based upon Monte-Carlo simulations, where the various realisations correspond to slightly different initial conditions. The present sate-of-the-art in Europe (ECMWF) and/or in the USA (IRI) allows to forecast such major phenomena, as El Niño, up to six months in advance. Finally, some parameters may exhibit predictability at still longer time-ranges (inter-annual to decadal), but only for certain regions. The example of electricity production is used to underline the potentially large economical benefit of seasonal climate forecasting. To cite this article: J.-C. André et al., C. R. Geoscience 334 (2002) 1115–1127.

Résumé

L'atmosphère et l'océan sont le siège d'instabilités dynamiques, qui limitent la durée pendant laquelle il est possible d'en prévoir l'évolution de façon déterministe. Au-delà, l'atmosphère n'est plus prévisible, au mieux, que de façon statistique, en fonction du forçage externe qu'exerce(nt) sur elle l'océan et/ou la surface des continents. Le climat (au sens d'une moyenne des états atmosphériques) se révèle ainsi prévisible jusqu'à des échéances temporelles de quelques mois, échelle de temps caractéristique des composantes dites « lentes » du système climatique. La prévision peut s'étendre à des échéances parfois plus longues, dans le cas où le système couplé océan–atmosphère posséderait des modes de variabilité temporelle de périodes caractéristiques de quelques années. La prévision climatique saisonnière est très souvent construite à partir de simulations de type Monte-Carlo, avec des ensembles de réalisations utilisant des conditions initiales légèrement différentes. Dans l'état actuel de ces prévisions, qu'elles soient réalisées en Europe (CEPMMT) ou aux États-Unis (IRI), il est possible de prévoir environ six mois à l'avance un certain nombre de phénomènes climatiques, en particulier ceux liés aux épisodes dits « El Niño », pour lesquels l'amplitude des variations est suffisamment importante. Il existe, par ailleurs, une prévisibilité à encore plus longue échéance (inter-annuelle à décennale), mais seulement pour certains paramètres et certaines régions. L'exemple de la production d'électricité montre l'importance économique potentielle très grande de la prévision climatique saisonnière. Pour citer cet article : J.-C. André et al., C. R. Geoscience 334 (2002) 1115–1127.     

线性矩法估计参数的保证修正值系数B的推求

在设计洪水的抽样误差估计中,采用保证修正值系数B方法估计均方差简单易用。应用线性矩法估计频率分布曲线的参数,有较好的无偏性和有效性,具有一定的应用前景。目前线性矩法的B值诺模图尚未确定,给用线性矩法确定参数时估计抽样误差带来了难度与不便。采用统计试验,分析了离差系数、偏态系数和样本长度对B值的影响,结果表明线性矩法估计参数时仍可采用保证修正值系数B值诺模图方法来估计抽样误差,并推求了不同偏态系数、设计频率情形下的B值,制成了线性矩法的B值诺模图备用。     

多普勒天气雷达资料对中尺度模式短时预报的影响

利用中尺度模式ARPS(The Advanced Regional Prediction System)及其资料分析系统ADAS(ARPS Data Analysis System),将国内新一代多普勒雷达(CINRAD)反射率及径向风资料直接用于中尺度数值模拟,通过一次华北地区暴雨过程的模拟对比试验,分析了雷达资料对初始场的改进效果及其对模拟结果的影响,结果表明:(1)利用雷达径向风资料对初始风场进行调整后,自近地面到对流层顶的u,v,w都发生了变化,调整后的初始风场在对流层中层变化最大.(2)利用雷达反射率进行微物理调整和云分析能调整初始场中的云水信息,使得雷达回波附近3 km以下的水汽混合比(qv)增加,4 km以下的雨水混合比(qr)增加,对流层(约10 km以下)的云水混合比(qc)增加,4～9 km的对流层上部云冰混合比(qi)和雪混合比(qs)增加.ADAS通过非绝热初始化调整温度场,从而得到了一个动力和热力上平衡的初始场.(3)模拟的1 h雨量与实况的对比表明,同时利用雷达反射率和径向风改进过的初始场能明显增强3 h内的降水强度和落区预报,改善中尺度数值模式短时定量降水预报.模拟的1 h流场对比分析表明,经雷达径向风调整后,能够在初始场中增加气旋性涡旋等中小尺度风信息,明显减少模式的spin-up时间.(4)通过对雷达径向风和反射率对模式初始场和模拟结果影响的对比分析发现,雷达径向风主要是改进初始风场,而雷达反射率主要是改进初始场中的湿度参数,增加初始场中云水等的含量,调整温度场.通过模拟的6 h降水对比发现,利用雷达径向风调整初始场后,对降水模拟有一定的改进,但效果不甚明显,而雷达反射率资料对定量降水预报改进效果明显,同时使用雷达径向风和反射率资料改进初始场后对降水的模拟效果最明显.     

A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling

During the last 50 years, the management of agroecosystems has been undergoing major changes to meet the growing demand for food, timber, fibre and fuel. As a result of this intensified use, the ecological status of many agroecosystems has been severely deteriorated. Modeling the behavior of agroecosystems is, therefore, of great help since it allows the definition of management strategies that maximize (crop) production while minimizing the environmental impacts. Remote sensing can support such modeling by offering information on the spatial and temporal variation of important canopy state variables which would be very difficult to obtain otherwise.In this paper, we present an overview of different methods that can be used to derive biophysical and biochemical canopy state variables from optical remote sensing data in the VNIR-SWIR regions. The overview is based on an extensive literature review where both statistical–empirical and physically based methods are discussed. Subsequently, the prevailing techniques of assimilating remote sensing data into agroecosystem models are outlined. The increasing complexity of data assimilation methods and of models describing agroecosystem functioning has significantly increased computational demands. For this reason, we include a short section on the potential of parallel processing to deal with the complex and computationally intensive algorithms described in the preceding sections.The studied literature reveals that many valuable techniques have been developed both for the retrieval of canopy state variables from reflective remote sensing data as for assimilating the retrieved variables in agroecosystem models. However, for agroecosystem modeling and remote sensing data assimilation to be commonly employed on a global operational basis, emphasis will have to be put on bridging the mismatch between data availability and accuracy on one hand, and model and user requirements on the other. This could be achieved by integrating imagery with different spatial, temporal, spectral, and angular resolutions, and the fusion of optical data with data of different origin, such as LIDAR and radar/microwave.     

Geophysical phenomena during an ionospheric modification experiment at Tromsø, Norway

We present an analysis of phenomena observed by HF distance-diagnostic tools located in St. Petersburg combined with multi-instrument observation at Tromsø in the HF modified ionosphere during a magnetospheric substorm. The observed phenomena that occurred during the Tromsø heating experiment in the nightside auroral E_s region of the ionosphere depend on the phase of substorm. The heating excited small-scale field-aligned irregularities in the E region responsible for field-aligned scattering of diagnostic HF waves. The equipment used in the experiment was sensitive to electron density irregularities with wavelengths 12–15 m across the geomagnetic field lines. Analysis of the Doppler measurement data shows the appearance of quasiperiodic variations with a Doppler frequency shift, f_d and periods about 100–120 s during the heating cycle coinciding in time with the first substorm activation and initiation of the upward field-aligned currents. A relationship between wave variations in f_d and magnetic pulsations in the Y-component of the geomagnetic field at Tromsø was detected. The analysis of the magnetic field variations from the IMAGE magnetometer stations shows that ULF waves occurred, not only at Tromsø, but in the adjacent area bounded by geographical latitudes from 70.5° to 68° and longitudes from 16° to 27°. It is suggested that the ULF observed can result from superposition of the natural and heater-induced ULF waves. During the substorm expansion a strong stimulated electromagnetic emission (SEE) at the third harmonic of the downshifted maximum frequency was found. It is believed that SEE is accompanied by excitation of the VLF waves penetrating into magneto-sphere and stimulating the precipitation of the energetic electrons (10–40 keV) of about 1-min duration. This is due to a cyclotron resonant interaction of natural precipitating electrons (1–10 keV) with heater-induced whistler waves in the magnetosphere. It is reasonable to suppose that a new substorm activation, exactly above Tromsø, was closely connected with the heater-induced precipitation of energetic electrons.     

A comparison of estimated and calculated effective porosity

 Effective porosity in solute-transport analyses is usually estimated rather than calculated from tracer tests in the field or laboratory. Calculated values of effective porosity in the laboratory on three different textured samples were compared to estimates derived from particle-size distributions and soil–water characteristic curves. The agreement was poor and it seems that no clear relationships exist between effective porosity calculated from laboratory tracer tests and effective porosity estimated from particle-size distributions and soil–water characteristic curves. A field tracer test in a sand-and-gravel aquifer produced a calculated effective porosity of approximately 0.17. By comparison, estimates of effective porosity from textural data, moisture retention, and published values were approximately 50–90% greater than the field calibrated value. Thus, estimation of effective porosity for chemical transport is highly dependent on the chosen transport model and is best obtained by laboratory or field tracer tests. Received, March 1997 · Revised, August 1997 · Accepted, August 1997     

A baroclinic typhoon model with a moving multi-nested grid and variational adjustment initialization Ⅱ. Forecast experiments

INTRODUCTIONBeingoneofthemestdisastrousweathersystemsinfluencingthesoutheaStcoastofChinainsurnmerandautumn,typhoonsalsocausestrongstormsUrgeSandseawavesI'eSultinginsevereoceandisasters,whichthreaten~theasternChina'sagriculture,navigation,offshoreoila...