scholarly journals Using observed river flow data to improve the hydrological functioning of the JULES land surface model (vn4.3) used for regional coupled modelling in Great Britain (UKC2)

2019 ◽  
Vol 12 (2) ◽  
pp. 765-784 ◽  
Author(s):  
Alberto Martínez-de la Torre ◽  
Eleanor M. Blyth ◽  
Graham P. Weedon
Keyword(s):  
Great Britain ◽  
Surface Runoff ◽  
Land Surface ◽  
River Flow ◽  
Model Performance ◽  
Soil Conditions ◽  
Surface Model ◽  
Climate Modelling ◽  
Prediction System ◽  
Runoff Production

Abstract. Land surface models (LSMs) represent terrestrial hydrology in weather and climate modelling operational systems and research studies. We aim to improve hydrological performance in the Joint UK Land Environment Simulator (JULES) LSM that is used for distributed hydrological modelling within the new land–atmosphere–ocean coupled prediction system UKC2 (UK regional Coupled environmental prediction system 2). Using river flow observations from gauge stations, we study the capability of JULES to simulate river flow at 1 km2 spatial resolution within 13 catchments in Great Britain that exhibit a variety of climatic and topographic characteristics. Tests designed to identify where the model results are sensitive to the scheme and parameters chosen for runoff production indicate that different catchments require different parameters and even different runoff schemes for optimal results. We introduce a new parameterisation of topographic variation that produces the best daily river flow results (in terms of Nash–Sutcliffe efficiency and mean bias) for all 13 catchments. The new parameterisation introduces a dependency on terrain slope, constraining surface runoff production to wet soil conditions over flatter regions, whereas over steeper regions the model produces surface runoff for every rainfall event regardless of the soil wetness state. This new parameterisation improves the model performance across Great Britain. As an example, in the Thames catchment, which has extensive areas of flat terrain, the Nash–Sutcliffe efficiency exceeds 0.8 using the new parameterisation. We use cross-spectral analysis to evaluate the amplitude and phase of the modelled versus observed river flows over timescales of 2 days to 10 years. This demonstrates that the model performance is modified by changing the parameterisation by different amounts over annual, weekly-to-monthly and multi-day timescales in different catchments, providing insights into model deficiencies on particular timescales, but it reinforces the newly developed parameterisation.

scholarly journals Using observed river flow data to improve the hydrological functioning of the JULES land surface model (vn4.3) used for regional coupled modelling in Great Britain (UKC2)

2018 ◽  
Author(s):  
Alberto Martínez-de la Torre ◽  
Eleanor M. Blyth ◽  
Graham P. Weedon
Keyword(s):  
Great Britain ◽  
Surface Runoff ◽  
Land Surface ◽  
River Flow ◽  
Soil Conditions ◽  
Surface Model ◽  
Climate Modelling ◽  
Prediction System ◽  
Coupled Modelling ◽  
Runoff Production

Abstract. Land surface models (LSMs) represent terrestrial hydrology in weather and climate modelling operational systems and research studies. We aim to improve hydrological performance in the Joint UK Land Environment Simulator (JULES) LSM that is suitable for distributed hydrological modelling within the new land-atmosphere-ocean coupled prediction system UKC2 (UK regional Coupled environmental prediction system 2). Using river flow observations from gauge stations, we study the capability of JULES to simulate river flow over 13 catchments in Great Britain, each representing different climatic and topographic characteristics at 1 km2 spatial resolution. A series of tests, carried out to identify where the model results are sensitive to the scheme and parameters chosen for runoff production, suggests that different catchments require different parameters and even different runoff schemes to produce the best results. From these results, we introduce a new topographical parametrization that produces the best daily river flow results (in terms of Nash-Sutcliffe efficiency and mean bias) for all 13 catchments. The new parametrization introduces a dependency on terrain slope, constraining surface runoff production to wet soil conditions over flatter regions (like the Thames catchment; Nash-Sutcliffe efficiency above 0.8), whereas over steeper regions the model produces surface runoff for every rainfall event regardless of the soil wetness state. This new parametrization improves the model capability in regional (Great Britain wide) assessments. The new choice of parameters is reinforced by examining the amplitude and phase of the modelled versus observed river flows, via cross-spectral analysis for time scales longer than daily.

scholarly journals Improving river flow generation over Great Britain in a land surface model required for coupled land-atmosphere interactions

2018 ◽  
Author(s):  
Alberto Martínez-de la Torre ◽  
Eleanor M. Blyth ◽  
Graham P. Weedon
Keyword(s):  
Great Britain ◽  
Surface Runoff ◽  
Land Surface ◽  
River Flow ◽  
Land Surface Model ◽  
Soil Conditions ◽  
Surface Model ◽  
Climate Modelling ◽  
Operational Systems ◽  
Runoff Production

Abstract. Land surface models (LSMs) represent terrestrial hydrology in weather and climate modelling operational systems and research studies. Using river flow observations from gauge stations, we study the capability of the Joint UK Land Environment Simulator (JULES) LSM to simulate river flow over 13 catchments in Great Britain, each representing different climatic and topographic characteristics at the 1 km2 spatial resolution. A series of tests, carried out to identify where the model results are sensitive to the scheme and parameters chosen for runoff production, suggests that different catchments require different parameters and even different runoff schemes to produce the best results. From these results, we introduce a new topographical parametrization that produces the best daily river flow results (in terms of Nash-Sutcliffe efficiency and mean bias) for all 13 catchments. The new parametrization introduces a dependency on terrain slope, constraining surface runoff production to wet soil conditions over flatter regions (like the Thames catchment; Nash-Sutcliffe efficiency above 0.8), whereas over steeper regions the model produces surface runoff for every rainfall event regardless of the soil wetness state. This new parametrization improves the model capability in regional (Great Britain wide) assessments. The new choice of parameters is reinforced by examining the amplitude and phase of the modelled versus observed river flows, via cross-spectral analysis for time scales longer than daily.

River parametrisation of the JULES land surface model for improved runoff routing at the global scale.

2021 ◽  
Author(s):  
Aristeidis Koutroulis ◽  
Manolis Grillakis ◽  
Camilla Mathison ◽  
Eleanor Burke
Keyword(s):  
Spatial Resolution ◽  
Land Surface ◽  
River Flow ◽  
Land Surface Model ◽  
Flow Simulation ◽  
Surface Model ◽  
Routing Scheme ◽  
Basin Scale ◽  
River Flow Simulation ◽  
River Routing

<p>The JULES land surface model has a wide ranging application in studying different processes of the earth system including hydrological modeling [1]. Our aim is to tune the existing configuration of the global river routing scheme at 0.5<sup>o</sup> spatial resolution [2] and improve river flow simulation performance at finer temporal scales. To do so, we develop a factorial experiment of varying effective river velocity and meander coefficient, components of the Total Runoff Integrating Pathways (TRIP) river routing scheme. We test and adjust best performing configurations at the basin scale based on observations from GRDC 230 stations that exhibiting a variety of hydroclimatic and physiographic conditions. The analysis was focused on watersheds of near-natural conditions [3] to avoid potential influences of human management on river flow. The HydroATLAS database [4] was employed to identify basin scale descriptive hydro-environmental indicators that could be associated with the components of the TRIP. These indicators summarize hydrologic and physiographic characteristics of the drainage area of each flow gauge. For each basin we select the best performing set of TRIP parameters per basin resulting to the optimal efficiency of river flow simulation based on the Nash–Sutcliffe and Kling–Gupta efficiency metrics. We find that better performance is driven predominantly by characteristics related to the stream gradient and terrain slope. These indicators can serve as descriptors for extrapolating the adjustment of TRIP parameters for global land configurations at 0.5<sup>o</sup> spatial resolution using regression models.</p><p> </p><p>[1] Papadimitriou et al 2017, Hydrol. Earth Syst. Sci., 21, 4379–4401</p><p>[2] Falloon et al 2007. Hadley Centre Tech. Note 72, 42 pp.</p><p>[3] Fang Zhao et al 2017 Environ. Res. Lett. 12 075003</p><p>[4] Linke et al 2019, Scientific Data 6: 283.</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 Development and application of the WRFPLUS-Chem online chemistry adjoint and WRFDA-Chem assimilation system

2015 ◽  
Vol 8 (6) ◽  
pp. 1857-1876 ◽  
Author(s):  
J. J. Guerrette ◽  
D. K. Henze
Keyword(s):  
Land Surface ◽  
Vertical Mixing ◽  
Model Performance ◽  
Land Surface Model ◽  
Sensitivity Study ◽  
Climate Impacts ◽  
Surface Model ◽  
Time Period ◽  
Develop Land ◽  
The Impact

Abstract. Here we present the online meteorology and chemistry adjoint and tangent linear model, WRFPLUS-Chem (Weather Research and Forecasting plus chemistry), which incorporates modules to treat boundary layer mixing, emission, aging, dry deposition, and advection of black carbon aerosol. We also develop land surface and surface layer adjoints to account for coupling between radiation and vertical mixing. Model performance is verified against finite difference derivative approximations. A second-order checkpointing scheme is created to reduce computational costs and enable simulations longer than 6 h. The adjoint is coupled to WRFDA-Chem, in order to conduct a sensitivity study of anthropogenic and biomass burning sources throughout California during the 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaign. A cost-function weighting scheme was devised to reduce the impact of statistically insignificant residual errors in future inverse modeling studies. Results of the sensitivity study show that, for this domain and time period, anthropogenic emissions are overpredicted, while wildfire emission error signs vary spatially. We consider the diurnal variation in emission sensitivities to determine at what time sources should be scaled up or down. Also, adjoint sensitivities for two choices of land surface model (LSM) indicate that emission inversion results would be sensitive to forward model configuration. The tools described here are the first step in conducting four-dimensional variational data assimilation in a coupled meteorology–chemistry model, which will potentially provide new constraints on aerosol precursor emissions and their distributions. Such analyses will be invaluable to assessments of particulate matter health and climate impacts.

scholarly journals Improved representations of coupled soil-canopy processes in the CABLE land surface model

2016 ◽  
Author(s):  
Vanessa Haverd ◽  
Matthias Cuntz ◽  
Lars P. Nieradzik ◽  
Ian N. Harman
Keyword(s):  
Water Use ◽  
Land Surface ◽  
Land Surface Model ◽  
Heat Fluxes ◽  
Soil Conditions ◽  
Surface Model ◽  
Drought Response ◽  
Deep Soil ◽  
Stable Conditions ◽  
Water Use Efficiencies

Abstract. CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. While CABLE performs well in comparison with other land surface models, results are impacted by decoupling of transpiration and photosynthesis fluxes under drying soil conditions, often leading to implausibly high water use efficiencies. Here we present a solution to this problem, ensuring that modeled transpiration is always consistent with modeled photosynthesis, while introducing a parsimonious single-parameter drought response function which is coupled to root water uptake. We further improve CABLE’s simulation of coupled soil-canopy processes by introducing an alternative hydrology model with a physically accurate representation of coupled energy and water fluxes at the soil/air interface, including a more realistic formulation of transfer under atmospherically stable conditions within the canopy and in the presence of leaf litter. The effects of these model developments are assessed using data from 18 stations from the global Eddy covariance flux network FLUXNET, selected to span a large climatic range. Marked improvements are demonstrated, with root-mean-squared errors for monthly latent heat fluxes and water use efficiencies being reduced by 40 %. Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation.

scholarly journals Presentation and discussion of the high resolution atmosphere-land surface subsurface simulation dataset of the virtual Neckar catchment for the period 2007–2015

2020 ◽  
Author(s):  
Bernd Schalge ◽  
Gabriele Baroni ◽  
Barbara Haese ◽  
Daniel Erdal ◽  
Gernot Geppert ◽  
...  
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Overland Flow ◽  
Water Cycle ◽  
Numerical Models ◽  
Model Performance ◽  
Surface Model ◽  
Meteorological Model ◽  
The Real ◽  
Terrestrial System

Abstract. Coupled numerical models, which simulate water and energy fluxes in the subsurface-land surface-atmosphere system in a physically consistent way are a prerequisite for the analysis and a better understanding of heat and matter exchange fluxes at compartmental boundaries and interdependencies of states across these boundaries. Complete state evolutions generated by such models may be regarded as a proxy of the real world, provided they are run at sufficiently high resolution and incorporate the most important processes. Such a virtual reality can be used to test hypotheses on the functioning of the coupled terrestrial system. Coupled simulation systems, however, face severe problems caused by the vastly different scales of the processes acting in and between the compartments of the terrestrial system, which also hinders comprehensive tests of their realism. We used the Terrestrial Systems Modeling Platform TerrSysMP, which couples the meteorological model COSMO, the land-surface model CLM, and the subsurface model ParFlow, to generate a virtual catchment for a regional terrestrial system mimicking the Neckar catchment in southwest Germany. Simulations for this catchment are made for the period 2007–2015, and at a spatial resolution of 400 m for the land surface and subsurface and 1.1 km for the atmosphere. Among a discussion of modelling challenges, the model performance is evaluated based on real observations covering several variables of the water cycle. We find that the simulated (virtual) catchment behaves in many aspects quite close to observations of the real Neckar catchment, e.g. concerning atmospheric boundary-layer height, precipitation, and runoff. But also discrepancies become apparent, both in the ability of the model to correctly simulate some processes which still need improvement such as overland flow, and in the realism of some observation operators like the satellite based soil moisture sensors. The whole raw dataset is available for interested users. The dataset described here is available via the CERA database (Schalge et al., 2020): https://doi.org/10.26050/WDCC/Neckar_VCS_v1.

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