时空序列预测误差的敏感性试验分析

利用33模Lorenz系统得到的"理想"混沌时空序列,作为时空混沌序列"发生器".通过状态空间重构,建立"场时间序列"局域近似预测模型,对资料空间分辨率,资料的长度、噪音,以及模型的参数选取等因素进行敏感性试验分析,了解时空混沌序列预测中误差产生和增长的一些影响因素.得到以下初步结论:对于理想混沌时空序列(33模Lorenz系统)而言,与系统相适应的资料空间分辨率和较长的资料长度都将会提高预测精度;可预报时效与资料长度之间近似服从指数关系.另外,在建立预测模型时,适当的邻近点数目,以及采用二阶映射关系和迭代法都可以有效地改善预测精度.对于加入噪音的混沌时间序列,通过"场时间序列"的局域近似方法和4阶自回归方法的预测试验的对比表明,前者显示了更强的抗"干扰"能力.以上结论可以有分析地应用于短期气候预测中.     

地-井电磁成像的灵敏度分析

本文着重讨论地—井电磁成像的灵敏度,包括不同观测分量、不同观测位置和不同工作频率的灵敏度函数的分布,为成像系统的布置和数据解释提供理论上的指导     

“96.8”暴雨的水汽来源及对水汽敏感性的模拟分析

首先用实例资料分析了河北“９６．８”暴雨过程的水汽来源,指出造成这次暴雨的水汽主要来自南海、孟加拉湾和台风低压本身携带的水汽。最后用ＭＭ４模式模拟分析了暴雨水汽的敏感性,得知水汽条件小的变化可能引起降水量大的改变,潜热释放对暴雨有正反馈作用。     

An improvement of the mass flux convection parameterization scheme and its sensitivity tests for seasonal prediction over China

A modified cumulus parameterization scheme, suitable for use in a seasonal forecast model, is presented. This parameterization scheme is an improvement of the mass flux convection scheme developed by Gregory and Rowntree (1989; 1990). This convection scheme uses a “bulk” cloud model to present an ensemble of convective clouds, and aims to represent shallow, deep, and mid-level convection. At present,this convection scheme is employed in the NCC T63L20 model (National Climate Center, China Meteorological Administration). Simulation results with this scheme have revealed some deficiencies in the scheme,although to some extent, it improves the accuracy of the simulation. In order to alleviate the deficiencies and reflect the effect of cumulus convection in the actual atmosphere, the scheme is modified and improved.The improvements include (i) the full estimation of the effects of the large-scale convergence in the lower layer upon cumulus convection, (ii) the revision of the initial convective mass flux, and (iii) the regulation of convective-scale downdrafts. A comparison of the results obtained by using the original model and the modified one shows that the improvement and modification of the original convection scheme is successful in simulating the precipitation and general circulation field, because the modified scheme provides a good simulation of the main features of seasonal precipitation in China, and an analysis of the anomaly correlation eoetfieient between the simulation and the observations confirms the improved results.     

太湖叶绿素a同化系统敏感性分析

太湖叶绿素a同化系统对于不同参数的敏感性将直接影响到该系统能否精确的估算太湖叶绿素a的浓度分布.利用2009年4月21日环境一号卫星(HJ-1B CCD2)影像数据反演太湖叶绿素a浓度场信息.以此作为背景场信息,结合基于集合均方根滤波的太湖叶绿素a同化系统,分析和评价了样本数目、同化时长、背景场误差、观测误差和模型误差对于同化系统性能的影响.结果表明:从计算成本、系统运行时间和同化效果等方面分析,当集合样本数目达到30~40左右时同化系统取得了较好的结果;同化系统对于背景场误差的估计变化不是很敏感,即初始场的估计是否准确对于同化系统的性能影响不是很大;同化系统对于模型误差和观测误差的变化较为敏感,不同的测试点位由于水体动力学性质不一,其敏感性的表现形式有所差异;利用数据同化方法可以有效地估算太湖叶绿素a浓度.     

Sensitivity of the Penman-Monteith reference evapotranspiration to sunshine duration in the Upper Mekong River Basin

Sensitivity analysis is important in understanding the relationship between sunshine duration (SD) and reference evapotranspiration (ET_ref). This study was developed in the Lancang-Mekong River Basin using a non-dimensional relative sensitivity coefficient (S_N) relating ET_ref to SD. The S_N for January and July for each station were calculated. The results indicate that (a) the SD and S_N change in similar ways, where January and July are selected as two representative time slices; (b) the spatial distributions of the long-term averaged S_N for January and July are the reverse of each other; (c) the most abrupt changes in climate occur in the 1980s and the middle region is sensitive to climate change; and (d) periodicities of 2–4 and 14–16 years are detected in the basin generally. The significant increase of inter-decadal filter variance indicates changes in the long-term memory of the local climate system.

EDITOR Z.W. Kundzewicz

ASSOCIATE EDITOR not assigned     

Hydrological system analysis and modelling of the Kara River basin (West Africa) using a lumped metric conceptual model

This paper discusses the analysis and modelling of the hydrological system of the basin of the Kara River, a transboundary river in Togo and Benin, as a necessary step towards sustainable water resources management. The methodological approach integrates the use of discharge parameters, flow duration curves and the lumped conceptual model IHACRES. A Sobol sensitivity analysis is performed and the model is calibrated by applying the shuffled complex evolution algorithm. Results show that discharge generation in three nested catchments of the basin is affected by landscape physical characteristics. The IHACRES model adequately simulates the rainfall–runoff dynamics in the basin with a mean modified Nash-Sutcliffe efficiency measure of 0.6. Modelling results indicate that parameters controlling rainfall transformation to effective rainfall are more sensitive than those routing the streamflow. This study provides insights into understanding the catchment’s hydrological system. Nevertheless, further investigations are required to better understand detailed runoff generation processes.

EDITOR M.C. Acreman; ASSOCIATE EDITOR N Verhoest     

Enhanced identification of a hydrologic model using streamflow and satellite water storage data: A multicriteria sensitivity analysis and optimization approach

Hydrologic model development and calibration have continued in most cases to focus only on accurately reproducing streamflows. However, complex models, for example, the so‐called physically based models, possess large degrees of freedom that, if not constrained properly, may lead to poor model performance when used for prediction. We argue that constraining a model to represent streamflow, which is an integrated resultant of many factors across the watershed, is necessary but by no means sufficient to develop a high‐fidelity model. To address this problem, we develop a framework to utilize the Gravity Recovery and Climate Experiment's (GRACE) total water storage anomaly data as a supplement to streamflows for model calibration, in a multiobjective setting. The VARS method (Variogram Analysis of Response Surfaces) for global sensitivity analysis is used to understand the model behaviour with respect to streamflow and GRACE data, and the BORG multiobjective optimization method is applied for model calibration. Two subbasins of the Saskatchewan River Basin in Western Canada are used as a case study. Results show that the developed framework is superior to the conventional approach of calibration only to streamflows, even when multiple streamflow‐based error functions are simultaneously minimized. It is shown that a range of (possibly false) system trajectories in state variable space can lead to similar (acceptable) model responses. This observation has significant implications for land‐surface and hydrologic model development and, if not addressed properly, may undermine the credibility of the model in prediction. The framework effectively constrains the model behaviour (by constraining posterior parameter space) and results in more credible representation of hydrology across the watershed.     

Multicriteria sensitivity analysis as a diagnostic tool for understanding model behaviour and characterizing model uncertainty

Complex hydrological models are being increasingly used nowadays for many purposes such as studying the impact of climate and land‐use change on water resources. However, building a high‐fidelity model, particularly at large scales, remains a challenging task, due to complexities in model functioning and behaviour and uncertainties in model structure, parameterization, and data. Global sensitivity analysis (GSA), which characterizes how the variation in the model response is attributed to variations in its input factors (e.g., parameters and forcing data), provides an opportunity to enhance the development and application of these complex models. In this paper, we advocate using GSA as an integral part of the modelling process by discussing its capabilities as a tool for diagnosing model structure and detecting potential defects, identifying influential factors, characterizing uncertainty, and selecting calibration parameters. Accordingly, we conduct a comprehensive GSA of a complex land surface–hydrology model, Modélisation Environmentale–Surface et Hydrologie (MESH), which combines the Canadian land surface scheme with a hydrological routing component, WATROUTE. Various GSA experiments are carried out using a new technique, called Variogram Analysis of Response Surfaces, for alternative hydroclimatic conditions in Canada using multiple criteria, various model configurations, and a full set of model parameters. Results from this study reveal that, in addition to different hydroclimatic conditions and SA criteria, model configurations can also have a major impact on the assessment of sensitivity. GSA can identify aspects of the model internal functioning that are counter‐intuitive and thus help the modeller to diagnose possible model deficiencies and make recommendations for improving development and application of the model. As a specific outcome of this work, a list of the most influential parameters for the MESH model is developed. This list, along with some specific recommendations, is expected to assist the wide community of MESH and Canadian land surface scheme users, to enhance their modelling applications.