Evaluation of the WAMME model surface fluxes using results from the AMMA land-surface model intercomparison project

2009 ◽  
Vol 35 (1) ◽  
pp. 127-142 ◽  
Author(s):  
Aaron Anthony Boone ◽  
Isabelle Poccard-Leclercq ◽  
Yongkang Xue ◽  
Jinming Feng ◽  
Patricia de Rosnay
Keyword(s):  
Land Surface ◽  
Land Surface Model ◽  
Surface Fluxes ◽  
Surface Model ◽  
Model Intercomparison ◽  
Model Surface ◽  
Intercomparison Project

scholarly journals The AMMA Land Surface Model Intercomparison Project (ALMIP)

2009 ◽  
Vol 90 (12) ◽  
pp. 1865-1880 ◽  
Author(s):  
Aaron Boone ◽  
Patricia de Rosnay ◽  
Gianpaolo Balsamo ◽  
Anton Beljaars ◽  
Franck Chopin ◽  
...  
Keyword(s):  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
Model Intercomparison ◽  
Intercomparison Project

scholarly journals CAS-LSM Datasets for the CMIP6 Land Surface Snow and Soil Moisture Model Intercomparison Project

2021 ◽  
Author(s):  
Binghao Jia ◽  
Longhuan Wang ◽  
Yan Wang ◽  
Ruichao Li ◽  
Xin Luo ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Grid Point ◽  
Global Ocean ◽  
Surface Model ◽  
Past Century ◽  
Model Intercomparison ◽  
Soil Moisture Model ◽  
Surface Snow ◽  
Intercomparison Project

AbstractThe datasets of the five Land-offline Model Intercomparison Project (LMIP) experiments using the Chinese Academy of Sciences Land Surface Model (CAS-LSM) of CAS Flexible Global-Ocean-Atmosphere-Land System Model Grid-point version 3 (CAS FGOALS-g3) are presented in this study. These experiments were forced by five global meteorological forcing datasets, which contributed to the framework of the Land Surface Snow and Soil Moisture Model Intercomparison Project (LS3MIP) of CMIP6. These datasets have been released on the Earth System Grid Federation node. In this paper, the basic descriptions of the CAS-LSM and the five LMIP experiments are shown. The performance of the soil moisture, snow, and land-atmosphere energy fluxes was preliminarily validated using satellite-based observations. Results show that their mean states, spatial patterns, and seasonal variations can be reproduced well by the five LMIP simulations. It suggests that these datasets can be used to investigate the evolutionary mechanisms of the global water and energy cycles during the past century.

ECLand: an ECMWF land surface modelling platform

2021 ◽  
Author(s):  
Gianpaolo Balsamo ◽  
Souhail Boussetta
Keyword(s):  
Land Surface ◽  
Urban Areas ◽  
Land Surface Model ◽  
Open Water ◽  
Surface Fluxes ◽  
Surface Model ◽  
New Developments ◽  
Surface Modelling ◽  
Land Surface Modelling ◽  
New Research

<p>The ECMWF operational land surface model, based on the Carbon-Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (CHTESSEL) is the baseline for global weather, climate and environmental applications at ECMWF. In order to expedite its progress and benefit from international collaboration, an ECLand platform has been designed to host advanced and modular schemes. ECLand is paving the way toward a land model that could support a wider range of modelling applications, facilitating global kilometer scales testing as envisaged in the Copernicus and Destination Earth programmes. This presentation introduces the CHTESSEL and its recent new developments that aims at hosting new research applications.</p><p>These new improvements touch upon different components of the model: (i) vegetation, (ii) snow, (iii) soil hydrology, (iv) open water/lakes (v) rivers and (vi) urban areas. The developments are evaluated separately with either offline simulations or coupled experiments, depending on their level of operational readiness, illustrating the benchmarking criteria for assessing process fidelity with regards to land surface fluxes and reservoirs involved in water-energy-carbon exchange, and within the Earth system prediction framework, as foreseen to enter upcoming ECMWF operational cycles.</p><p>Reference: Souhail Boussetta, Gianpaolo Balsamo*, Anna Agustì-Panareda, Gabriele Arduini, Anton Beljaars, Emanuel Dutra, Glenn Carver, Margarita Choulga, Ioan Hadade, Cinzia Mazzetti, Joaquìn Munõz-Sabater, Joe McNorton, Christel Prudhomme, Patricia De Rosnay, Irina Sandu, Nils Wedi, Dai Yamazaki, Ervin Zsoter, 2021: ECLand: an ECMWF land surface modelling platform, MDPI Atmosphere, (in prep).</p>

scholarly journals Benchmarking and Process Diagnostics of Land Models

2018 ◽  
Vol 19 (11) ◽  
pp. 1835-1852 ◽  
Author(s):  
Grey S. Nearing ◽  
Benjamin L. Ruddell ◽  
Martyn P. Clark ◽  
Bart Nijssen ◽  
Christa Peters-Lidard
Keyword(s):  
Land Surface ◽  
Model Performance ◽  
Land Surface Model ◽  
Surface Model ◽  
Process Diagnostics ◽  
Surface Energy Fluxes ◽  
Structural Error ◽  
Intercomparison Project ◽  
Parameter Values ◽  
Process Level

Abstract We propose a conceptual and theoretical foundation for information-based model benchmarking and process diagnostics that provides diagnostic insight into model performance and model realism. We benchmark against a bounded estimate of the information contained in model inputs to obtain a bounded estimate of information lost due to model error, and we perform process-level diagnostics by taking differences between modeled versus observed transfer entropy networks. We use this methodology to reanalyze the recent Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) land model intercomparison project that includes the following models: CABLE, CH-TESSEL, COLA-SSiB, ISBA-SURFEX, JULES, Mosaic, Noah, and ORCHIDEE. We report that these models (i) use only roughly half of the information available from meteorological inputs about observed surface energy fluxes, (ii) do not use all information from meteorological inputs about long-term Budyko-type water balances, (iii) do not capture spatial heterogeneities in surface processes, and (iv) all suffer from similar patterns of process-level structural error. Because the PLUMBER intercomparison project did not report model parameter values, it is impossible to know whether process-level error patterns are due to model structural error or parameter error, although our proposed information-theoretic methodology could distinguish between these two issues if parameter values were reported. We conclude that there is room for significant improvement to the current generation of land models and their parameters. We also suggest two simple guidelines to make future community-wide model evaluation and intercomparison experiments more informative.

scholarly journals Modeling Land Surface Fluxes from Uncertain Rainfall: A Case Study in the Sahel with Field-Driven Stochastic Rainfields

Atmosphere ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 465
Author(s):  
Bernard Cappelaere ◽  
Denis Feurer ◽  
Théo Vischel ◽  
Catherine Ottlé ◽  
Hassane Bil-Assanou Issoufou ◽  
...  
Keyword(s):  
Land Surface ◽  
Monsoon Season ◽  
Land Surface Model ◽  
Surface Fluxes ◽  
Energy Budgets ◽  
Substantial Part ◽  
Surface Model ◽  
Time Space ◽  
Flux Variability ◽  
Sahel Region

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.

scholarly journals Influence of thermodynamic soil and vegetation parameterizations on the simulation of soil temperature states and surface fluxes by the Noah LSm over a Tibetan plateau site

2009 ◽  
Vol 6 (1) ◽  
pp. 455-499 ◽  
Author(s):  
R. van der Velde ◽  
Z. Su ◽  
M. Ek ◽  
M. Rodell ◽  
Y. Ma
Keyword(s):  
Thermal Properties ◽  
Tibetan Plateau ◽  
Land Surface ◽  
Land Surface Model ◽  
Soil Heat Flux ◽  
Stomatal Resistance ◽  
Surface Fluxes ◽  
Surface Model ◽  
The Tibetan Plateau ◽  
Soil Thermal Properties

Abstract. In this paper, we investigate the ability of the Noah Land Surface model (LSm) to simulate temperature states in the soil profile and surface fluxes measured during a 7-day dry period at a micrometeorological station on the Tibetan Plateau. Adjustments in soil and vegetation parameterizations required to ameliorate the Noah simulation on these two aspects are presented, which include: (1) Differentiating the soil thermal properties of top- and subsoils, (2) Investigation of the different numerical soil discretizations and (3) Calibration of the parameters utilized to describe the transpiration dynamics of the Plateau vegetation. Through the adjustments in the parameterization of the soil thermal properties (STP) simulation of the soil heat transfer is improved, which results in a reduction of Root Mean Squared Differences (RMSD's) by 14%, 18% and 49% between measured and simulated skin, 5-cm and 25-cm soil temperatures, respectively. Further, decreasing the minimum stomatal resistance (Rc, min) and the optimum temperature for transpiration (Topt) of the vegetation parameterization reduces RMSD's between measured and simulated energy balance components by 30%, 20% and 5% for the sensible, latent and soil heat flux, respectively.

Assessment of the uncertainty related to irrigation modeling by a land surface model across India

2020 ◽  
Author(s):  
Dazhi Li ◽  
Xujun Han ◽  
Dhanya C.t. ◽  
Stefan Siebert ◽  
Harry Vereecken ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Monsoon Season ◽  
Land Surface Model ◽  
Surface Fluxes ◽  
Spatiotemporal Pattern ◽  
Surface Model ◽  
Irrigation Requirement ◽  
Community Land Model ◽  
Surface Models

<p>Irrigation is very important for maintaining the agricultural production and sustaining the increasing population of India. The irrigation requirement can be estimated with land surface models by modeling water storage changes but the estimates are affected by various uncertainties such as regarding the spatiotemporal distribution of areas where and when irrigation is potentially applied. In the present work, this uncertainty is analyzed for the whole Indian domain. The irrigation requirements and hydrological fluxes over India were reconstructed by multiple simulation experiments with the Community Land Model (CLM) version 4.5 for the year of 2010.</p><p>These multiple simulation scenarios showed that the modeled irrigation requirement and the land surface fluxes differed between the scenarios, representing the spatiotemporal uncertainty of the irrigation maps. Using a season-specific irrigation map resulted in a higher transpiration-evapotranspiration ratio (T/ET) in the pre-monsoon season compared to the application of a static irrigation map, which implies a higher irrigation efficiency. The remote sensing based evapotranspiration products GLEAM and MODIS ET were used for comparison, showing a similar increasing ET-trend in the pre-monsoon season as the irrigation induced land surface modeling. The correspondence is better if the seasonal irrigation map is used as basis for simulations with CLM. We conclude that more accurate temporal information on irrigation results in modeled evapotranspiration closer to the spatiotemporal pattern of evapotranspiration deduced from remote sensing. Another conclusion is that irrigation modeling should consider the sub-grid heterogeneity to improve the estimation of soil water deficit and irrigation requirement.</p>

scholarly journals WRFv3.2-SPAv2: development and validation of a coupled ecosystem–atmosphere model, scaling from surface fluxes of CO<sub>2</sub> and energy to atmospheric profiles

2013 ◽  
Vol 6 (4) ◽  
pp. 1079-1093 ◽  
Author(s):  
T. L. Smallman ◽  
J. B. Moncrieff ◽  
M. Williams
Keyword(s):  
Air Temperature ◽  
Land Surface ◽  
Wrf Model ◽  
Land Surface Model ◽  
Net Ecosystem Exchange ◽  
Terrestrial Ecosystem ◽  
Surface Fluxes ◽  
Surface Model ◽  
Terrestrial Ecosystem Model ◽  
Atmospheric Profiles

Abstract. The Weather Research and Forecasting meteorological (WRF) model has been coupled to the Soil–Plant–Atmosphere (SPA) terrestrial ecosystem model, to produce WRF-SPA. SPA generates realistic land–atmosphere exchanges through fully coupled hydrological, carbon and energy cycles. The addition of a~land surface model (SPA) capable of modelling biospheric CO2 exchange allows WRF-SPA to be used for investigating the feedbacks between biosphere carbon balance, meteorology, and land use and land cover change. We have extensively validated WRF-SPA using multi-annual observations of air temperature, turbulent fluxes, net radiation and net ecosystem exchange of CO2 at three sites, representing the dominant vegetation types in Scotland (forest, managed grassland and arable agriculture). For example air temperature is well simulated across all sites (forest R2 = 0.92, RMSE = 1.7 °C, bias = 0.88 °C; managed grassland R2 = 0.73, RMSE = 2.7 °C, bias = −0.30 °C; arable agriculture R2 = 0.82, RMSE = 2.2 °C, bias = 0.46 °C; RMSE, root mean square error). WRF-SPA generates more realistic seasonal behaviour at the site level compared to an unmodified version of WRF, such as improved simulation of seasonal transitions in latent heat flux in arable systems. WRF-SPA also generates realistic seasonal CO2 exchanges across all sites. WRF-SPA is also able to realistically model atmospheric profiles of CO2 over Scotland, spanning a 3 yr period (2004–2006), capturing both profile structure, indicating realistic transport, and magnitude (model–data residual

scholarly journals Evaluation of the Noah land-surface model using data from a fair-weather IHOP_2002 day with heterogeneous surface fluxes

2007 ◽  
Vol preprint (2008) ◽  
pp. 1
Author(s):  
Margaret A. LeMone ◽  
Mukul Tewari ◽  
Fei Chen ◽  
Joseph G. Alfieri ◽  
Dev Niyogi
Keyword(s):  
Land Surface ◽  
Land Surface Model ◽  
Surface Fluxes ◽  
Heterogeneous Surface ◽  
Surface Model ◽  
Fair Weather ◽  
Noah Land Surface Model ◽  
Using Data

scholarly journals Investigating the Impact of Soil Moisture and Atmospheric Stability on Cloud Development and Distribution Using a Coupled Large-Eddy Simulation and Land Surface Model

2011 ◽  
Vol 12 (5) ◽  
pp. 787-804 ◽  
Author(s):  
Hsin-Yuan Huang ◽  
Steven A. Margulis
Keyword(s):  
Thermal Stability ◽  
Soil Moisture ◽  
Land Surface ◽  
Atmospheric Stability ◽  
Land Surface Model ◽  
Coupled Model ◽  
Surface Fluxes ◽  
Surface Model ◽  
Eddy Simulation ◽  
Cloud Development

Abstract The influence of soil moisture and atmospheric thermal stability on surface fluxes, boundary layer characteristics, and cloud development are investigated using a coupled large-eddy simulation (LES)–land surface model (LSM) framework. The study day from the Cabauw site in the central part of the Netherlands has been studied to examine the soil moisture–cloud feedback using a parameterized single-column model (SCM) in previous work. Good agreement is seen in the comparison between coupled model results and observations collected at the Cabauw eddy-covariance tower. Simulation results confirm the hypothesis that both surface fluxes and atmospheric boundary layer (ABL) states are strongly affected by soil moisture and atmospheric stability, which was proposed by a previous study using an SCM with simple parameterization. While the ABL-top cloud development is a nonmonotonic function of surface water content under different thermal stability conditions, coupled model simulations find that weak thermal stability has significant impacts on both thermal and moisture fluxes and variances near the entrainment zone, especially for the dry surface cases. Additionally, the impacts of ABL-top stability on thermal and moisture entrainment processes are in a different magnitude. The explicitly resolved cloud cover fraction increases with increasing soil moisture only occurs in cases with strong atmospheric stability, and an opposite result is seen when weak atmospheric stability exists. The elevation of cloud base highly depends on the strength of sensible heat flux. However, results of cloud thickness show that a dry surface with weak thermal stability is able to form a large amount of cumulus cloud, even if the soil provides less water vapor.

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