期刊论文详细信息
Atmosphere
Modeling Land Surface Fluxes from Uncertain Rainfall: A Case Study in the Sahel with Field-Driven Stochastic Rainfields
Stéphane Saux-Picart1  Benoit Coudert2  HassaneBil-Assanou Issoufou3  Bernard Cappelaere4  Hélène Barral4  Denis Feurer4  Jean-Philippe Chazarin4  Jérôme Demarty4  Ibrahim Maïnassara4  Monique Oï4  Théo Vischel5  Catherine Ottlé6 
[1] Centre National de la Recherche Météorologique (CNRM), Université de Toulouse, Météo-France, 22300 Lannion, France;Centre d’Études Spatiales de la Biosphère UMR 5126, Université de Toulouse, 31400 Toulouse, France;Départment Sciences et Techniques de Productions Végétales, University Dan Dicko Dankoulodo, Maradi BP 465, Niger;HydroSciences Montpellier (HSM), University Montpellier, CNRS, IRD, 300 av. Emile Jeanbrau, 34090 Montpellier, France;IGE, University Grenoble Alpes, CNRS, Grenoble INP, IRD, 38058 Grenoble, France;LSCE/IPSL, CNRS-CEA-UVSQ, University Paris-Saclay, 91191 Gif-sur-Yvette, France;
关键词: uncertainty propagation;    uncertainty measures;    ensemble simulation;    water and energy fluxes;    evapotranspiration;    land surface model;   
DOI  :  10.3390/atmos11050465
来源: DOAJ
【 摘 要 】

In distributed land surface modeling (LSM) studies, uncertainty in the rainfields that are used to force models is a major source of error in predicted land surface response variables. This is particularly true for applications in the African Sahel region, where weak knowledge of highly time/space-variable convective rainfall in a poorly monitored region is a considerable obstacle to such developments. In this study, we used a field-based stochastic rainfield generator to analyze the propagation of the rainfall uncertainty through a distributed land surface model simulating water and energy fluxes in Sahelian ecosystems. Ensemble time/space rainfields were generated from field observations of the local AMMA-CATCH-Niger recording raingauge network. The rainfields were then used to force the SEtHyS-Savannah LSM, yielding an ensemble of time/space simulated fluxes. Through informative graphical representations and innovative diagnosis metrics, these outputs were analyzed to separate the different components of flux variability, among which was the uncertainty represented by ensemble-wise variability. Scale dependence was analyzed for each flux type in the water and energy budgets, producing a comprehensive picture of uncertainty propagation for the various flux types, with its relationship to intrinsic space/time flux variability. The study was performed over a 2530 km2 domain over six months, covering an entire monsoon season and the subsequent dry-down, using a kilometer/daily base resolution of analysis. The newly introduced dimensionless uncertainty measure, called the uncertainty coefficient, proved to be more effective in describing uncertainty patterns and relationships than a more classical measure based on variance fractions. Results show a clear scaling relationship in uncertainty coefficients between rainfall and the dependent fluxes, specific to each flux type. These results suggest a higher sensitivity to rainfall uncertainty for hydrological than for agro-ecological or meteorological applications, even though eddy fluxes do receive a substantial part of that source uncertainty.

【 授权许可】

Unknown   

  文献评价指标  
  下载次数:0次 浏览次数:0次