scholarly journals Integration of nitrogen dynamics into the Noah-MP land model v1.1 for climate and environmental predictions

2015 ◽  
Vol 8 (5) ◽  
pp. 4113-4153 ◽  
Author(s):  
X. Cai ◽  
Z.-L. Yang ◽  
J. B. Fisher ◽  
X. Zhang ◽  
M. Barlage ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Net Primary Productivity ◽  
Assessment Tool ◽  
Land Surface Model ◽  
Coupled Model ◽  
Nitrogen Dynamics ◽  
Surface Model ◽  
Meteorological Model ◽  
Environmental Models

Abstract. Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. In this study, we add capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long-term Ecological Research site within the U.S. Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of the carbon and water cycles (e.g., net primary productivity and evapotranspiration). The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.

scholarly journals Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

2016 ◽  
Vol 9 (1) ◽  
pp. 1-15 ◽  
Author(s):  
X. Cai ◽  
Z.-L. Yang ◽  
J. B. Fisher ◽  
X. Zhang ◽  
M. Barlage ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Net Primary Productivity ◽  
Assessment Tool ◽  
Land Surface Model ◽  
Coupled Model ◽  
Nitrogen Dynamics ◽  
Surface Model ◽  
Meteorological Model ◽  
Environmental Models

Abstract. Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. In this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.

Diagnosing Present and Future Permafrost from Climate Models

2013 ◽  
Vol 26 (15) ◽  
pp. 5608-5623 ◽  
Author(s):  
Andrew G. Slater ◽  
David M. Lawrence
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Land Surface Model ◽  
Coupled Model ◽  
Temporal Distribution ◽  
Surface Model ◽  
Permafrost Region ◽  
Near Surface ◽  
Surface Climate ◽  
Soil Temperatures

Abstract Permafrost is a characteristic aspect of the terrestrial Arctic and the fate of near-surface permafrost over the next century is likely to exert strong controls on Arctic hydrology and biogeochemistry. Using output from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), the authors assess its ability to simulate present-day and future permafrost. Permafrost extent diagnosed directly from each climate model's soil temperature is a function of the modeled surface climate as well as the ability of the land surface model to represent permafrost physics. For each CMIP5 model these two effects are separated by using indirect estimators of permafrost driven by climatic indices and compared to permafrost extent directly diagnosed via soil temperatures. Several robust conclusions can be drawn from this analysis. Significant air temperature and snow depth biases exist in some model's climates, which degrade both directly and indirectly diagnosed permafrost conditions. The range of directly calculated present-day (1986–2005) permafrost area is extremely large (~4–25 × 106 km2). Several land models contain structural weaknesses that limit their skill in simulating cold region subsurface processes. The sensitivity of future permafrost extent to temperature change over the present-day observed permafrost region averages (1.67 ± 0.7) × 106 km2 °C−1 but is a function of the spatial and temporal distribution of climate change. Because of sizable differences in future climates for the representative concentration pathway (RCP) emission scenarios, a wide variety of future permafrost states is predicted by 2100. Conservatively, the models suggest that for RCP4.5, permafrost will retreat from the present-day discontinuous zone. Under RCP8.5, sustainable permafrost will be most probable only in the Canadian Archipelago, Russian Arctic coast, and east Siberian uplands.

scholarly journals Assimilation of SMOS brightness temperature into a large-scale distributed conceptual hydrological model

2019 ◽  
Author(s):  
Renaud Hostache ◽  
Dominik Rains ◽  
Kaniska Mallick ◽  
Marco Chini ◽  
Ramona Pelich ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Brightness Temperature ◽  
Land Surface ◽  
Large Scale ◽  
Hydrological Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Meteorological Model ◽  
Temperature Observations

Abstract. The main objective of this study is to investigate how brightness temperature observations from satellite microwave sensors may help in reducing errors and uncertainties in soil moisture simulations with a large-scale conceptual hydro-meteorological model. In particular, we use as forcings the ERA-Interim public dataset and we couple the CMEM radiative transfer model with a hydro-meteorological model enabling therefore soil moisture and SMOS-like brightness temperature simulations. The hydro-meteorological model is configured using recent developments of the SUPERFLEX framework, which enables tailoring the model structure to the specific needs of the application as well as to data availability and computational requirements. In this case, the model spatial resolution is adapted to the spatial grid of the satellite data, and the soil stratification is tailored to the satellite datasets to be assimilated and the forcing data. The hydrological model is first calibrated using a sample of SMOS brightness temperature observations (period 2010–2011). Next, SMOS-derived brightness temperature observations are sequentially assimilated into the coupled SUPERFLEX-CMEM model (period 2010–2015). For this experiment, a Local Ensemble Transform Kalman Filter is used and the meteorological forcings (ERA interim-based rainfall, air and soil temperature) are perturbed to generate a background ensemble. Each time a SMOS observation is available, the SUPERFLEX state variables related to the water content in the various soil layers are updated and the model simulations are resumed until the next SMOS observation becomes available. Our empirical results show that the SUPERFLEX-CMEM modelling chain is capable of predicting soil moisture at a performance level similar to that obtained for the same study area and with a quasi-identical experimental set up using the CLM land surface model. This shows that a simple model, when carefully calibrated, can yield performance level similar to that of a much more complex model. The correlation between simulated and in situ observed soil moisture ranges from 0.62 to 0.72. The assimilation of SMOS brightness temperature observation into the SUPERFLEX-CMEM modelling chain improves the correlation between predicted and in situ observed soil moisture by 0.03 on average showing improvements similar to those obtained using the CLM land surface model.

scholarly journals La représentation des surfaces continentales dans la modélisation du climat à Météo-France

2020 ◽  
pp. 067
Author(s):  
Bertrand Decharme ◽  
Christine Delire ◽  
Aaron Boone
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Land Surface Model ◽  
Global Scale ◽  
Surface Model ◽  
Climate Modelling ◽  
History Of ◽  
International Climate ◽  
Land Surfaces ◽  
Computational Resources

Les surfaces continentales jouent un rôle non négligeable dans le système climatique de la Terre. Elles occupent d'ailleurs une place majeure dans les cycles globaux de l'eau et du carbone. Elles ont été prises en compte dès les premiers modèles numériques de climat et, avec l'évolution des connaissances, des capacités de calcul et de la demande sociétale, leur représentation s'est aujourd'hui considérablement complexifiée. Nous présentons ici une brève histoire de l'évolution du modèle de surfaces Isba (Interactions sol-biosphère-atmosphère) de Météo-France dans son utilisation à l'échelle du globe en la replaçant dans le contexte international de la modélisation climatique. Land surfaces play a significant role in the Earth climate system, and they are a major component of the global carbon and water cycles. The first numerical climate models took them into account in very simple ways. Through time the complexity of their representation has increased a lot owing to improved knowledge, larger computational resources and changing societal demands. We present here a brief history of the ISBA (Interactions Soil-Biosphere-Atmosphere) land surface model developed at Météo-France when used at the global scale and how it evolved in the context of international climate modelling.

scholarly journals Coupling a groundwater model with a land surface model to improve water and energy cycle simulation

2012 ◽  
Vol 9 (1) ◽  
pp. 1163-1205 ◽  
Author(s):  
W. Tian ◽  
X. Li ◽  
X.-S. Wang ◽  
B. X. Hu
Keyword(s):  
Groundwater Flow ◽  
Land Surface ◽  
Flow Model ◽  
Land Surface Model ◽  
Coupled Model ◽  
Subsurface Water ◽  
Surface Model ◽  
Groundwater Flow Model ◽  
Groundwater Model ◽  
Depth Zone

Abstract. The water and energy cycles interact, making them generally closely related. Land surface models (LSMs) can describe the water and energy cycles of the land surface, but their description of the subsurface water processes is oversimplified, and lateral groundwater flow is ignored. Groundwater models (GWMs) well describe the dynamic movement of subsurface water flow, but they cannot depict the physical mechanism of the evapotranspiration (ET) process in detail. In this study, a coupled model of groundwater with simple biosphere (GWSiB) is developed based on the full coupling of a typical land surface model (SiB2) and a three-dimensional variably saturated groundwater model (AquiferFlow). In this model, the infiltration, ET and energy transfer are simulated by SiB2 via the soil moisture results given by the groundwater flow model. The infiltration and ET results are applied iteratively to drive the groundwater flow model. The developed model is then applied to study water cycle processes in the middle reaches of the Heihe River Basin in the northwest of China. The model is validated through data collected at three stations in the study area. The stations are located in a shallow groundwater depth zone, a deeper groundwater depth zone and an agricultural irrigation area. The study results show that the coupled model can well depict the land surface and groundwater interaction and can more comprehensively and accurately simulate the water and energy cycles compared with uncoupled models.

scholarly journals Towards a more detailed representation of high-latitude vegetation in the global land surface model ORCHIDEE (ORC-HL-VEGv1.0)

2017 ◽  
Vol 10 (12) ◽  
pp. 4693-4722 ◽  
Author(s):  
Arsène Druel ◽  
Philippe Peylin ◽  
Gerhard Krinner ◽  
Philippe Ciais ◽  
Nicolas Viovy ◽  
...  
Keyword(s):  
Land Surface ◽  
Vascular Plants ◽  
Net Primary Productivity ◽  
Water Discharge ◽  
Land Surface Model ◽  
The Arctic ◽  
Surface Model ◽  
C3 Grasses ◽  
In Situ Observations

Abstract. Simulation of vegetation–climate feedbacks in high latitudes in the ORCHIDEE land surface model was improved by the addition of three new circumpolar plant functional types (PFTs), namely non-vascular plants representing bryophytes and lichens, Arctic shrubs and Arctic C3 grasses. Non-vascular plants are assigned no stomatal conductance, very shallow roots, and can desiccate during dry episodes and become active again during wet periods, which gives them a larger phenological plasticity (i.e. adaptability and resilience to severe climatic constraints) compared to grasses and shrubs. Shrubs have a specific carbon allocation scheme, and differ from trees by their larger survival rates in winter, due to protection by snow. Arctic C3 grasses have the same equations as in the original ORCHIDEE version, but different parameter values, optimised from in situ observations of biomass and net primary productivity (NPP) in Siberia. In situ observations of living biomass and productivity from Siberia were used to calibrate the parameters of the new PFTs using a Bayesian optimisation procedure. With the new PFTs, we obtain a lower NPP by 31 % (from 55° N), as well as a lower roughness length (−41 %), transpiration (−33 %) and a higher winter albedo (by +3.6 %) due to increased snow cover. A simulation of the water balance and runoff and drainage in the high northern latitudes using the new PFTs results in an increase of fresh water discharge in the Arctic ocean by 11 % (+140 km3 yr−1), owing to less evapotranspiration. Future developments should focus on the competition between these three PFTs and boreal tree PFTs, in order to simulate their area changes in response to climate change, and the effect of carbon–nitrogen interactions.

scholarly journals Analysis and Simulation of Human Activity Impact on Streamflow in the Huaihe River Basin with a Large-Scale Hydrologic Model

2010 ◽  
Vol 11 (3) ◽  
pp. 810-821 ◽  
Author(s):  
Chuanguo Yang ◽  
Zhaohui Lin ◽  
Zhongbo Yu ◽  
Zhenchun Hao ◽  
Shaofeng Liu
Keyword(s):  
Land Surface ◽  
Land Surface Model ◽  
Coupled Model ◽  
Hydrologic Model ◽  
Water Withdrawal ◽  
Surface Model ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Hydrologic Processes ◽  
The Huaihe River

Abstract A hydrologic model coupled with a land surface model is applied to simulate the hydrologic processes in the Huaihe River basin, China. Parameters of the land surface model are interpolated from global soil and vegetation datasets. The characteristics of the basin are derived from digital elevation models (DEMs) and a national geological survey atlas using newly developed algorithms. The NCEP–NCAR reanalysis dataset and observed precipitation data are used as meteorological inputs for simulating the hydrologic processes in the basin. The coupled model is first calibrated and validated by using observed streamflow over the period of 1980–87. A long-term continuous simulation is then carried out for 1980–2003, forced with observed rainfall data. Results show that the model behavior is reasonable for flood years, whereas streamflows are sometimes overestimated for dry years since the 1990s when water withdrawal increased substantially because of the growing industrial activities and the development of water projects. Observed streamflow and water withdrawal data showed that human activities have obviously affected the surface rainfall–runoff process, especially in dry years. Two methods are proposed to study the human dimension in the hydrologic cycle. One method is to reconstruct the natural streamflow series using local volumes of withdrawals. The simulated results are more consistent with the reconstructed hydrograph than the initially observed hydrograph. The other method is to integrate a designated module into the coupled model system to represent the effect of human activities. This method can significantly improve the model performance in terms of streamflow simulation.

scholarly journals A Modeling and Observational Framework for Diagnosing Local Land–Atmosphere Coupling on Diurnal Time Scales

2009 ◽  
Vol 10 (3) ◽  
pp. 577-599 ◽  
Author(s):  
Joseph A. Santanello ◽  
Christa D. Peters-Lidard ◽  
Sujay V. Kumar ◽  
Charles Alonge ◽  
Wei-Kuo Tao
Keyword(s):  
Great Plains ◽  
Land Surface ◽  
Field Experiments ◽  
Climate Models ◽  
Mesoscale Model ◽  
Weather Prediction ◽  
Critical Role ◽  
Land Surface Model ◽  
Surface Model ◽  
Test Bed

Abstract Land–atmosphere interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture states. The degree of coupling between the land surface and PBL in numerical weather prediction and climate models remains largely unexplored and undiagnosed because of the complex interactions and feedbacks present across a range of scales. Furthermore, uncoupled systems or experiments [e.g., the Project for the Intercomparison of Land-Surface Parameterization Schemes (PILPS)] may lead to inaccurate water and energy cycle process understanding by neglecting feedback processes such as PBL-top entrainment. In this study, a framework for diagnosing local land–atmosphere coupling is presented using a coupled mesoscale model with a suite of PBL and land surface model (LSM) options along with observations during field experiments in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting Model (WRF) has been coupled to the Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. Within this framework, the coupling established by each pairing of the available PBL schemes in WRF with the LSMs in LIS is evaluated in terms of the diurnal temperature and humidity evolution in the mixed layer. The coevolution of these variables and the convective PBL are sensitive to and, in fact, integrative of the dominant processes that govern the PBL budget, which are synthesized through the use of mixing diagrams. Results show how the sensitivity of land–atmosphere interactions to the specific choice of PBL scheme and LSM varies across surface moisture regimes and can be quantified and evaluated against observations. As such, this methodology provides a potential pathway to study factors controlling local land–atmosphere coupling (LoCo) using the LIS–WRF system, which will serve as a test bed for future experiments to evaluate coupling diagnostics within the community.

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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