scholarly journals Representation of dissolved organic carbon in the JULES land surface model (vn4.4_JULES-DOCM)

2017 ◽  
Author(s):  
Mahdi Nakhavali ◽  
Pierre Friedlingstein ◽  
Ronny Lauerwald ◽  
Jing Tang ◽  
Sarah Chadburn ◽  
...  
Keyword(s):  
Land Surface ◽  
Soil Column ◽  
Model Performance ◽  
Land Surface Model ◽  
Terrestrial Ecosystems ◽  
Surface Model ◽  
Organic C ◽  
Run Off ◽  
C Cycle ◽  
Doc Concentration

Abstract. Current global models of the carbon (C) cycle consider only vertical gas exchanges between terrestrial or oceanic reservoirs and the atmosphere, thus not considering lateral transport of carbon from the continents to the oceans. Therefore, those models implicitly consider that all the C which is not respired to the atmosphere is stored on land, hence overestimating the land C sink capability. A model that represents the whole continuum from atmosphere to land and into the ocean would provide better understanding of the Earth's C cycle and hence more reliable historical or future projections. We present an original representation of Dissolved Organic C (DOC) processes in the Joint UK Land Environment Simulator (JULES-DOCM). The standard version of JULES represents energy, water and carbon dynamics between vegetation, soil and atmosphere, while lateral fluxes only account for water run-off. Here we integrate a representation of DOC production in terrestrial ecosystems based on incomplete decomposition of organic matter, DOC decomposition within the soil column, and DOC export to the river network via leaching. The model performance is evaluated in five specific sites for which observations of soil DOC concentration are available. Results show that the model is able to reproduce the DOC concentration and controlling processes including leaching to the riverine system which is fundamental for integrating terrestrial and aquatic ecosystems.

scholarly journals Representation of dissolved organic carbon in the JULES land surface model (vn4.4_JULES-DOCM)

2018 ◽  
Vol 11 (2) ◽  
pp. 593-609 ◽  
Author(s):  
Mahdi Nakhavali ◽  
Pierre Friedlingstein ◽  
Ronny Lauerwald ◽  
Jing Tang ◽  
Sarah Chadburn ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Dissolved Organic Carbon ◽  
Land Surface ◽  
Soil Column ◽  
River System ◽  
Terrestrial Ecosystems ◽  
Surface Model ◽  
Organic C ◽  
C Cycle ◽  
Doc Concentration

Abstract. Current global models of the carbon (C) cycle consider only vertical gas exchanges between terrestrial or oceanic reservoirs and the atmosphere, thus not considering the lateral transport of carbon from the continents to the oceans. Therefore, those models implicitly consider all of the C which is not respired to the atmosphere to be stored on land and hence overestimate the land C sink capability. A model that represents the whole continuum from atmosphere to land and into the ocean would provide a better understanding of the Earth's C cycle and hence more reliable historical or future projections. A first and critical step in that direction is to include processes representing the production and export of dissolved organic carbon in soils. Here we present an original representation of dissolved organic C (DOC) processes in the Joint UK Land Environment Simulator (JULES-DOCM) that integrates a representation of DOC production in terrestrial ecosystems based on the incomplete decomposition of organic matter, DOC decomposition within the soil column, and DOC export to the river network via leaching. The model performance is evaluated in five specific sites for which observations of soil DOC concentration are available. Results show that the model is able to reproduce the DOC concentration and controlling processes, including leaching to the riverine system, which is fundamental for integrating terrestrial and aquatic ecosystems. Future work should include the fate of exported DOC in the river system as well as DIC and POC export from soil.

scholarly journals Modelling northern peatlands area and carbon dynamics since the Holocene with the ORCHIDEE-PEAT land surface model (SVN r5488)

2018 ◽  
Author(s):  
Chunjing Qiu ◽  
Dan Zhu ◽  
Philippe Ciais ◽  
Bertrand Guenet ◽  
Shushi Peng ◽  
...  
Keyword(s):  
Carbon Storage ◽  
Land Surface ◽  
Net Primary Production ◽  
Soil Column ◽  
Land Surface Model ◽  
Surface Model ◽  
Past Century ◽  
Positive Trend ◽  
Peat Core ◽  
Northern Peatlands

Abstract. The importance of northern peatlands in the global carbon cycle has recently been recognized, especially for long-term changes. Yet, the complex interactions between climate and peatland hydrology, carbon storage and area dynamics make it challenging to represent these systems in land surface models. This study describes how peatland are included as an independent sub-grid hydrological soil unit (HSU) into the ORCHIDEE-MICT land surface model. The peatland soil column in this tile is characterized by multi-layered vertical water and carbon transport, and peat-specific hydrological properties. A cost-efficient TOPMODEL approach is implemented to simulate the dynamics of peatland area, calibrated by present-day wetland areas that are regularly inundated or subject to shallow water tables. The model is tested across a range of northern peatland sites and for gridded simulations over the Northern Hemisphere (> 30° N). Simulated northern peatland area (3.9 million km2), peat carbon stock (463 PgC) and peat depth are generally consistent with observed estimates of peatland area (3.4–4.0 million km2), peat carbon (270–540 PgC) and data compilations of peat core depths. Our results show that both net primary production (NPP) and heterotrophic respiration (HR) of northern peatlands increased over the past century in response to CO2 and climate change. NPP increased more rapidly than HR, and thus net ecosystem production (NEP) exhibited a positive trend, contributing a cumulative carbon storage of 11.13 Pg C since 1901, most of it being realized after the 1950s.

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 Implementing the Water, HEat and Transport model in GEOframe (WHETGEO-1D v.1.0): algorithms, informatics, design patterns, open science features, and 1D deployment

2022 ◽  
Vol 15 (1) ◽  
pp. 75-104
Author(s):  
Niccolò Tubini ◽  
Riccardo Rigon
Keyword(s):  
Land Surface ◽  
Design Patterns ◽  
Transport Model ◽  
Soil Column ◽  
Land Surface Model ◽  
Richards Equation ◽  
Energy Budgets ◽  
Programming Approach ◽  
Generic Programming ◽  
Surface Model

Abstract. This paper presents WHETGEO and its 1D deployment: a new physically based model simulating the water and energy budgets in a soil column. The purpose of this contribution is twofold. First, we discuss the mathematical and numerical issues involved in solving the Richardson–Richards equation, conventionally known as the Richards equation, and the heat equation in heterogeneous soils. In particular, for the Richardson–Richards equation (R2) we take advantage of the nested Newton–Casulli–Zanolli (NCZ) algorithm that ensures the convergence of the numerical solution in any condition. Second, starting from numerical and modelling needs, we present the design of software that is intended to be the first building block of a new customizable land-surface model that is integrated with process-based hydrology. WHETGEO is developed as an open-source code, adopting the object-oriented paradigm and a generic programming approach in order to improve its usability and expandability. WHETGEO is fully integrated into the GEOframe/OMS3 system, allowing the use of the many ancillary tools it provides. Finally, the paper presents the 1D deployment of WHETGEO, WHETGEO-1D, which has been tested against the available analytical solutions presented in the Appendix.

scholarly journals Assessment of WRF Land Surface Model Performance over West Africa

2020 ◽  
Vol 2020 ◽  
pp. 1-30
Author(s):  
Ifeanyi C. Achugbu ◽  
Jimy Dudhia ◽  
Ayorinde A. Olufayo ◽  
Ifeoluwa A. Balogun ◽  
Elijah A. Adefisan ◽  
...  
Keyword(s):  
West Africa ◽  
Land Surface ◽  
Model Performance ◽  
Wrf Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Reanalysis Dataset ◽  
The North ◽  
Temperature And Precipitation ◽  
Moisture Advection

Simulations with four land surface models (LSMs) (i.e., Noah, Noah-MP, Noah-MP with ground water GW option, and CLM4) using the Weather Research and Forecasting (WRF) model at 12 km horizontal grid resolution were carried out as two sets for 3 months (December–February 2011/2012 and July–September 2012) over West Africa. The objective is to assess the performance of WRF LSMs in simulating meteorological parameters over West Africa. The model precipitation was assessed against TRMM while surface temperature was compared with the ERA-Interim reanalysis dataset. Results show that the LSMs performed differently for different variables in different land-surface conditions. Based on precipitation and temperature, Noah-MP GW is overall the best for all the variables and seasons in combination, while Noah came last. Specifically, Noah-MP GW performed best for JAS temperature and precipitation; CLM4 was the best in simulating DJF precipitation, while Noah was the best in simulating DJF temperature. Noah-MP GW has the wettest Sahel while Noah has the driest one. The strength of the Tropical Easterly Jet (TEJ) is strongest in Noah-MP GW and Noah-MP compared with that in CLM4 and Noah. The core of the African Easterly Jet (AEJ) lies around 12°N in Noah and 15°N for Noah-MP GW. Noah-MP GW and Noah-MP simulations have stronger influx of moisture advection from the southwesterly monsoonal wind than the CLM4 and Noah with Noah showing the least influx. Also, analysis of the evaporative fraction shows sharp gradient for Noah-MP GW and Noah-MP with wetter Sahel further to the north and further to the south for Noah. Noah-MP-GW has the highest amount of soil moisture, while the CLM4 has the least for both the JAS and DJF seasons. The CLM4 has the highest LH for both DJF and JAS seasons but however has the least SH for both DJF and JAS seasons. The principal difference between the LSMs is in the vegetation representation, description, and parameterization of the soil water column; hence, improvement is recommended in this regard.

scholarly journals The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations

2017 ◽  
Vol 10 (4) ◽  
pp. 1487-1520 ◽  
Author(s):  
David Walters ◽  
Ian Boutle ◽  
Malcolm Brooks ◽  
Thomas Melvin ◽  
Rachel Stratton ◽  
...  
Keyword(s):  
Land Surface ◽  
Weather Prediction ◽  
Model Performance ◽  
Land Surface Model ◽  
Unified Model ◽  
Surface Model ◽  
Main Trunk ◽  
Global Land ◽  
Prediction Systems ◽  
The Tropics

Abstract. We describe Global Atmosphere 6.0 and Global Land 6.0 (GA6.0/GL6.0): the latest science configurations of the Met Office Unified Model and JULES (Joint UK Land Environment Simulator) land surface model developed for use across all timescales. Global Atmosphere 6.0 includes the ENDGame (Even Newer Dynamics for General atmospheric modelling of the environment) dynamical core, which significantly increases mid-latitude variability improving a known model bias. Alongside developments of the model's physical parametrisations, ENDGame also increases variability in the tropics, which leads to an improved representation of tropical cyclones and other tropical phenomena. Further developments of the atmospheric and land surface parametrisations improve other aspects of model performance, including the forecasting of surface weather phenomena. We also describe GA6.1/GL6.1, which includes a small number of long-standing differences from our main trunk configurations that we continue to require for operational global weather prediction. Since July 2014, GA6.1/GL6.1 has been used by the Met Office for operational global numerical weather prediction, whilst GA6.0/GL6.0 was implemented in its remaining global prediction systems over the following year.

scholarly journals The ERA5-Land soil temperature bias in permafrost regions

2020 ◽  
Vol 14 (8) ◽  
pp. 2581-2595 ◽  
Author(s):  
Bin Cao ◽  
Stephan Gruber ◽  
Donghai Zheng ◽  
Xin Li
Keyword(s):  
Soil Temperature ◽  
Land Surface ◽  
Soil Column ◽  
Land Surface Model ◽  
Surface Model ◽  
Active Layer Thickness ◽  
Near Surface ◽  
Warm Bias ◽  
Temperature Bias ◽  
Permafrost Regions

Abstract. ERA5-Land (ERA5L) is a reanalysis product derived by running the land component of ERA5 at increased resolution. This study evaluates ERA5L soil temperature in permafrost regions based on observations and published permafrost products. We find that ERA5L overestimates soil temperature in northern Canada and Alaska but underestimates it in mid–low latitudes, leading to an average bias of −0.08 ∘C. The warm bias of ERA5L soil is stronger in winter than in other seasons. As calculated from its soil temperature, ERA5L overestimates active-layer thickness and underestimates near-surface (<1.89 m) permafrost area. This is thought to be due in part to the shallow soil column and coarse vertical discretization of the land surface model and to warmer simulated soil. The soil temperature bias in permafrost regions correlates well with the bias in air temperature and with maximum snow height. A review of the ERA5L snow parameterization and a simulation example both point to a low bias in ERA5L snow density as a possible cause for the warm bias in soil temperature. The apparent disagreement of station-based and areal evaluation techniques highlights challenges in our ability to test permafrost simulation models. While global reanalyses are important drivers for permafrost simulation, we conclude that ERA5L soil data are not well suited for informing permafrost research and decision making directly. To address this, future soil temperature products in reanalyses will require permafrost-specific alterations to their land surface models.

scholarly journals CE-DYNAM (v1), a spatially explicit, process-based carbon erosion scheme for the use in Earth system models

2019 ◽  
Author(s):  
Victoria Naipal ◽  
Ronny Lauerwald ◽  
Philippe Ciais ◽  
Bertrand Guenet ◽  
Yilong Wang
Keyword(s):  
Soil Erosion ◽  
Land Surface ◽  
Land Surface Model ◽  
Spatially Explicit ◽  
Surface Model ◽  
Erosion Rates ◽  
C Cycle ◽  
Atmospheric Co2 Concentrations ◽  
Rhine Catchment ◽  
Soc Stocks

Abstract. Soil erosion by rainfall and runoff is an important process behind the redistribution of soil organic carbon (SOC) over land, hereby impacting the exchange of carbon (C) between land, atmosphere and rivers. However, the net role of soil erosion in the global C cycle is still unclear as it involves small-scale SOC removal, transport and re-deposition processes that can only be addressed over selected small regions with measurements and models. This leads to uncertainties in future projections of SOC stocks and complicates the evaluation of strategies to mitigate climate change through increased SOC sequestration. In this study we present the parsimonious process-based Carbon Erosion DYNAMics model (CE-DYNAM) that links sediment dynamics resulting from water erosion with the C cycle along a cascade of hillslopes, floodplains and rivers. The model simulates horizontal soil and C transfers triggered by erosion across landscapes and the resulting changes in land-atmosphere CO2 fluxes at a resolution of about 8 km at the catchment scale. CE-DYNAM is the result of the coupling of a previously developed coarse-resolution sediment budget model and the ecosystem C cycle and erosion removal model derived from the ORCHIDEE land surface model. CE-DYNAM is driven by spatially explicit historical land use change, climate forcing, and global atmospheric CO2 concentrations affecting ecosystem productivity, erosion rates and residence times of sediment and C in deposition sites. The main features of CE-DYNAM are (1) the spatially explicit simulation of sediment and C fluxes linking hillslopes and floodplains, (2) the low number of parameters that allow running the model at large spatial scales and over long-time scales, and (3) its compatibility with any global land surface model, hereby, providing opportunities to study the effect of soil erosion under global changes. We present the model structure, concepts, and evaluation at the scale of the Rhine catchment for the period 1850–2005 AD. Model results are validated against independent estimates of gross and net soil and C erosion rates, and the spatial variability of SOC stocks from high-resolution modeling studies and observational datasets. We show that despite local differences, the resulting soil and C erosion rates, and SOC stocks from our rather coarse-resolution modelling approach are comparable to high-resolution estimates and observations at sub-basin level. The model also shows that SOC storage increases exponentially with basin area for floodplains in contrast to hillslopes as is seen in observations. We find that soil erosion mobilized 159 Tg (1012 g) of C under changing climate and land use, assuming that the erosion loop of the C cycle was in near steady-state by 1850. This caused a net C sink equal to 1 % of the Net Primary Productivity of the Rhine catchment over 1850–2005 AD. This sink is a result of the dynamic replacement of C on eroding sites that increases in this period due to rising atmospheric CO2 concentrations enhancing the litter C input to the soil from primary production.

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