Author
Aaron Boone
Bio: Aaron Boone is an academic researcher from Centre national de la recherche scientifique. The author has contributed to research in topics: Evapotranspiration & Snow. The author has an hindex of 37, co-authored 91 publications receiving 5542 citations.
Topics: Evapotranspiration, Snow, Water cycle, Snowpack, Surface runoff
Papers published on a yearly basis
Papers
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TL;DR: SURFEX as mentioned in this paper is an externalized land and ocean surface platform that describes the surface fluxes and the evolution of four types of surfaces: nature, town, inland water and ocean.
Abstract: . SURFEX is a new externalized land and ocean surface platform that describes the surface fluxes and the evolution of four types of surfaces: nature, town, inland water and ocean. It is mostly based on pre-existing, well-validated scientific models that are continuously improved. The motivation for the building of SURFEX is to use strictly identical scientific models in a high range of applications in order to mutualise the research and development efforts. SURFEX can be run in offline mode (0-D or 2-D runs) or in coupled mode (from mesoscale models to numerical weather prediction and climate models). An assimilation mode is included for numerical weather prediction and monitoring. In addition to momentum, heat and water fluxes, SURFEX is able to simulate fluxes of carbon dioxide, chemical species, continental aerosols, sea salt and snow particles. The main principles of the organisation of the surface are described first. Then, a survey is made of the scientific module (including the coupling strategy). Finally, the main applications of the code are summarised. The validation work undertaken shows that replacing the pre-existing surface models by SURFEX in these applications is usually associated with improved skill, as the numerous scientific developments contained in this community code are used to good advantage.
573 citations
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TL;DR: The detailed snowpack model Crocus as mentioned in this paper is such a scheme, and has been run operationally for avalanche forecasting over the French mountains for 20 years, and is also used for climate or hydrological studies.
Abstract: . Detailed studies of snow cover processes require models that offer a fine description of the snow cover properties. The detailed snowpack model Crocus is such a scheme, and has been run operationally for avalanche forecasting over the French mountains for 20 yr. It is also used for climate or hydrological studies. To extend its potential applications, Crocus has been recently integrated within the framework of the externalized surface module SURFEX. SURFEX computes the exchanges of energy and mass between different types of surface and the atmosphere. It includes in particular the land surface scheme ISBA (Interactions between Soil, Biosphere, and Atmosphere). It allows Crocus to be run either in stand-alone mode, using a time series of forcing meteorological data or in fully coupled mode (explicit or fully implicit numerics) with atmospheric models ranging from meso-scale models to general circulation models. This approach also ensures a full coupling between the snow cover and the soil beneath. Several applications of this new simulation platform are presented. They range from a 1-D stand-alone simulation (Col de Porte, France) to fully-distributed simulations in complex terrain over a whole mountain range (Massif des Grandes Rousses, France), or in coupled mode such as a surface energy balance and boundary layer simulation over the East Antarctic Ice Sheet (Dome C).
516 citations
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University of Sheffield1, University of Edinburgh2, University of Saskatchewan3, University of Helsinki4, University of Washington5, Colorado State University6, Environment Canada7, University of California, Los Angeles8, University of Lisbon9, United States Forest Service10, Royal Institute of Technology11, Bridgewater State University12, University of Yamanashi13, Silver Spring Networks14, University of California, Davis15, Swedish Meteorological and Hydrological Institute16, University of Reading17, National Oceanic and Atmospheric Administration18, University of Colorado Boulder19, Swiss Federal Institute for Forest, Snow and Landscape Research20, MeteoSwiss21, Ludwig Maximilian University of Munich22, University of Texas at Austin23, Japan Agency for Marine-Earth Science and Technology24, Kyoto University25, Instituto Português do Mar e da Atmosfera26, Durham University27, Met Office28, Tohoku University29
TL;DR: In this article, three snowpack models of varying complexity and purpose were evaluated across a wide range of hydrometeorological and forest canopy conditions at five Northern Hemisphere locations, for up to three months.
Abstract: Thirty-three snowpack models of varying complexity and purpose were evaluated across a wide range of hydrometeorological and forest canopy conditions at five Northern Hemisphere locations, for up t ...
334 citations
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TL;DR: In this paper, the authors presented the databases used by the SIM model and assessed the 10-year simulation by using the observations of daily stream-flow, piezometric head, and snow depth.
Abstract: The hydrometeorological model SIM consists in a meterological analysis system (SAFRAN), a land surface model (ISBA) and a hydrogeological model (MODCOU). It generates atmospheric forcing at an hourly time step, and it computes water and surface energy budgets, the river ow at more than 900 rivergauging stations, and the level of several aquifers. SIM was extended over all of France in order to have a homogeneous nation-wide monitoring of the water resources: it can therefore be used to forecast flood risk and to monitor drought risk over the entire nation. The hydrometeorologival model was applied over a 10-year period from 1995 to 2005. In this paper the databases used by the SIM model are presented, then the 10-year simulation is assessed by using the observations of daily stream-flow, piezometric head, and snow depth. This assessment shows that SIM is able to reproduce the spatial and temporal variabilities of the water fluxes. The efficiency is above 0.55 (reasonable results) for 66 % of the simulated rivergages, and above 0.65 (rather good results) for 36 % of them. However, the SIM system produces worse results during the driest years, which is more likely due to the fact that only few aquifers are simulated explicitly. The annual evolution of the snow depth is well reproduced, with a square correlation coeficient around 0.9 over the large altitude range in the domain. The stream ow observations were used to estimate the overall error of the simulated latent heat ux, which was estimated to be less than 4 %.
306 citations
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Environment Canada1, Swiss Federal Institute for Forest, Snow and Landscape Research2, Met Office3, Agencia Estatal de Meteorología4, Russian Academy of Sciences5, Engineer Research and Development Center6, National Oceanic and Atmospheric Administration7, Commonwealth Scientific and Industrial Research Organisation8, University of Colorado Boulder9, Ludwig Maximilian University of Munich10, University of Arizona11
TL;DR: In this paper, the authors focus on the impact of model complexity on the energy-budget components of a snow energy-model and evaluate different albedo parameterizations for different snowpack states (in winter and spring).
Abstract: Many snow models have been developed for various applications such as hydrology, global atmospheric circulation models and avalanche forecasting. The degree of complexity of these models is highly variable, ranging from simple index methods to multi-layer models that simulate snow-cover stratigraphy and texture. In the framework of the Snow Model Intercomparison Project (SnowMIP), 23 models were compared using observed meteorological parameters from two mountainous alpine sites.The analysis here focuses on validation of snow energy-budget simulations. Albedo and snow surface tem- perature observations allow identification of the more realistic simulations and quantifi- cation of errors for two components of the energy budget: the net short- and longwave radiation. In particular, the different albedo parameterizations are evaluated for different snowpack states (in winter and spring). Analysis of results during the melting period allows an investigation of the different ways of partitioning the energy fluxes and reveals the complex feedbacks which occur when simulating the snow energy budget. Particular attention is paid to the impact of model complexity on the energy-budget components. The model complexity has a major role for the net longwave radiation calculation, whereas the albedo parameterization is the most significant factor explaining the accu- racy of the net shortwave radiation simulation.
233 citations
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01 Apr 2003
TL;DR: The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it as mentioned in this paper, and also presents new ideas and alternative interpretations which further explain the success of the EnkF.
Abstract: The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.
2,975 citations
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TL;DR: In this article, the authors present the impact tests that preceded the most recent operational upgrades to the land surface model used in the National Centers for Environmental Prediction (NCEP) mesoscale Eta model, whose operational domain includes North America.
Abstract: [1] We present the impact tests that preceded the most recent operational upgrades to the land surface model used in the National Centers for Environmental Prediction (NCEP) mesoscale Eta model, whose operational domain includes North America. These improvements consist of changes to the “Noah” land surface model (LSM) physics, most notable in the area of cold season processes. Results indicate improved performance in forecasting low-level temperature and humidity, with improvements to (or without affecting) the overall performance of the Eta model quantitative precipitation scores and upper air verification statistics. Remaining issues that directly affect the Noah LSM performance in the Eta model include physical parameterizations of radiation and clouds, which affect the amount of available energy at the surface, and stable boundary layer and surface layer processes, which affect surface turbulent heat fluxes and ultimately the surface energy budget.
2,520 citations
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TL;DR: In this paper, a simple radiative transfer model with vegetation, soil, and atmospheric components is used to illustrate how the normalized difference vegetation index (NDVI), leaf area index (LAI), and fractional vegetation cover are dependent.
2,429 citations
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TL;DR: In this paper, the authors present the impact tests that preceded the most recent operational upgrades to the land surface model used in the National Centers for Environmental Prediction (NCEP) mesoscale Eta model, whose operational domain includes North America.
Abstract: [i] We present the impact tests that preceded the most recent operational upgrades to the land surface model used in the National Centers for Environmental Prediction (NCEP) mesoscale Eta model, whose operational domain includes North America. These improvements consist of changes to the Noah land surface model (LSM) physics, most notable in the area of cold season processes. Results indicate improved performance in forecasting low-level temperature and humidity, with improvements to (or without affecting) the overall performance of the Eta model quantitative precipitation scores and upper air verification statistics. Remaining issues that directly affect the Noah LSM performance in the Eta model include physical parameterizations of radiation and clouds, which affect the amount of available energy at the surface, and stable boundary layer and surface layer processes, which affect surface turbulent heat fluxes and ultimately the surface energy budget.
2,105 citations