scholarly journals Simulation of Surface Fluxes in Two Distinct Environments along a Topographic Gradient in a Central Amazonian Forest using the INtegrated LAND Surface Model

2017 ◽  
Author(s):  
Elisângela Broedel ◽  
Celso Von Randow ◽  
Luz Adriana Cuartas ◽  
Antonio Donato Nobre ◽  
Alessandro Carioca de Araújo ◽  
...  
Keyword(s):  
Heat Flux ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Land Surface Model ◽  
Net Ecosystem Exchange ◽  
Surface Fluxes ◽  
Surface Model ◽  
Terra Firme ◽  
Topographic Gradient ◽  
Valley Area

Abstract. The Integrated Land Surface model (INLAND) land surface model, in offline mode, was adjusted and forced with prescribed climate to represent two contrasting environments along a topographic gradient in a central Amazon Terra Firme forest, which is distinguished by well-drained, flat plateaus and poorly drained, broad river valleys. To correctly simulate the valley area, a lumped unconfined aquifer model was included in the INLAND model to represent the water table dynamics and results show reasonable agreement with observations. Field data from both areas are used to evaluate the model simulations of energy, water and carbon fluxes. The model is able to characterize with good accuracy the main differences that appear in the seasonal energy and carbon partitioning of plateau and valley fluxes, which are related to features of the vegetation associated with soils and topography. The simulated latent heat flux (LE) and net ecosystem exchange of carbon (NEE), for example, are higher on the plateau area while at the bottom of the valley the sensible heat flux (H) is noticeably higher than at the plateau, in agreement with observed data. Differences in simulated hydrological fluxes are also linked to the topography, showing a higher surface runoff (R) and lower evapotranspiration (ET) in the valley area. The different behavior of the fluxes on both annual and diurnal time scales confirms the benefit of a tiling mechanism in the presence of large contrast and the importance to incorporate subgrid-scale variability by including relief attributes of topography, soil and vegetation to better representing Terra Firme forests in land surface models.

scholarly journals Assimilation of Satellite-Derived Skin Temperature Observations into Land Surface Models

2010 ◽  
Vol 11 (5) ◽  
pp. 1103-1122 ◽  
Author(s):  
Rolf H. Reichle ◽  
Sujay V. Kumar ◽  
Sarith P. P. Mahanama ◽  
Randal D. Koster ◽  
Q. Liu
Keyword(s):  
Heat Flux ◽  
Data Assimilation ◽  
Skin Temperature ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Land Surface Model ◽  
Open Loop ◽  
Surface Model ◽  
Ground Heat Flux ◽  
Assimilation System

Abstract Land surface (or “skin”) temperature (LST) lies at the heart of the surface energy balance and is a key variable in weather and climate models. In this research LST retrievals from the International Satellite Cloud Climatology Project (ISCCP) are assimilated into the Noah land surface model and Catchment land surface model (CLSM) using an ensemble-based, offline land data assimilation system. LST is described very differently in the two models. A priori scaling and dynamic bias estimation approaches are applied because satellite and model LSTs typically exhibit different mean values and variabilities. Performance is measured against 27 months of in situ measurements from the Coordinated Energy and Water Cycle Observations Project at 48 stations. LST estimates from Noah and CLSM without data assimilation (“open loop”) are comparable to each other and superior to ISCCP retrievals. For LST, the RMSE values are 4.9 K (CLSM), 5.5 K (Noah), and 7.6 K (ISCCP), and the anomaly correlation coefficients (R) are 0.61 (CLSM), 0.63 (Noah), and 0.52 (ISCCP). Assimilation of ISCCP retrievals provides modest yet statistically significant improvements (over an open loop, as indicated by nonoverlapping 95% confidence intervals) of up to 0.7 K in RMSE and 0.05 in the anomaly R. The skill of the latent and sensible heat flux estimates from the assimilation integrations is essentially identical to the corresponding open loop skill. Noah assimilation estimates of ground heat flux, however, can be significantly worse than open loop estimates. Provided the assimilation system is properly adapted to each land model, the benefits from the assimilation of LST retrievals are comparable for both models.

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 On the use of the post-closure methods uncertainty band to evaluate the performance of land surface models against eddy covariance flux data

2015 ◽  
Vol 12 (8) ◽  
pp. 2311-2326 ◽  
Author(s):  
J. Ingwersen ◽  
K. Imukova ◽  
P. Högy ◽  
T. Streck
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Eddy Covariance ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Land Surface Model ◽  
Bowen Ratio ◽  
Surface Model ◽  
Flux Data ◽  
Uncertainty Band

Abstract. The energy balance of eddy covariance (EC) flux data is normally not closed. Therefore, at least if used for modelling, EC flux data are usually post-closed, i.e. the measured turbulent fluxes are adjusted so as to close the energy balance. At the current state of knowledge, however, it is not clear how to partition the missing energy in the right way. Eddy flux data therefore contain some uncertainty due to the unknown nature of the energy balance gap, which should be considered in model evaluation and the interpretation of simulation results. We propose to construct the post-closure methods uncertainty band (PUB), which essentially designates the differences between non-adjusted flux data and flux data adjusted with the three post-closure methods (Bowen ratio, latent heat flux (LE) and sensible heat flux (H) method). To demonstrate this approach, simulations with the NOAH-MP land surface model were evaluated based on EC measurements conducted at a winter wheat stand in southwest Germany in 2011, and the performance of the Jarvis and Ball–Berry stomatal resistance scheme was compared. The width of the PUB of the LE was up to 110 W m−2 (21% of net radiation). Our study shows that it is crucial to account for the uncertainty in EC flux data originating from lacking energy balance closure. Working with only a single post-closing method might result in severe misinterpretations in model–data comparisons.

scholarly journals Simulating the IHOP_2002 Fair-Weather CBL with the WRF-ARW–Noah Modeling System. Part I: Surface Fluxes and CBL Structure and Evolution along the Eastern Track

2010 ◽  
Vol 138 (3) ◽  
pp. 722-744 ◽  
Author(s):  
Margaret A. LeMone ◽  
Fei Chen ◽  
Mukul Tewari ◽  
Jimy Dudhia ◽  
Bart Geerts ◽  
...  
Keyword(s):  
Heat Flux ◽  
Land Surface ◽  
Roughness Length ◽  
Vegetation Type ◽  
Sensible Heat Flux ◽  
Surface Fluxes ◽  
Weather Data ◽  
Surface Model ◽  
Fair Weather ◽  
Convective Boundary

Abstract Fair-weather data from the May–June 2002 International H2O Project (IHOP_2002) 46-km eastern flight track in southeast Kansas are compared to simulations using the advanced research version of the Weather Research and Forecasting model coupled to the Noah land surface model (LSM), to gain insight into how the surface influences convective boundary layer (CBL) fluxes and structure, and to evaluate the success of the modeling system in representing CBL structure and evolution. This offers a unique look at the capability of the model on scales the length of the flight track (46 km) and smaller under relatively uncomplicated meteorological conditions. It is found that the modeled sensible heat flux H is significantly larger than observed, while the latent heat flux (LE) is much closer to observations. The slope of the best-fit line ΔLE/ΔH to a plot of LE as a function of H, an indicator of horizontal variation in available energy H + LE, for the data along the flight track, was shallower than observed. In a previous study of the IHOP_2002 western track, similar results were explained by too small a value of the parameter C in the Zilitinkevich equation used in the Noah LSM to compute the roughness length for heat and moisture flux from the roughness length for momentum, which is supplied in an input table; evidence is presented that this is true for the eastern track as well. The horizontal variability in modeled fluxes follows the soil moisture pattern rather than vegetation type, as is observed; because the input land use map does not capture the observed variation in vegetation. The observed westward rise in CBL depth is successfully modeled for 3 of the 4 days, but the actual depths are too high, largely because modeled H is too high. The model reproduces the timing of observed cumulus cloudiness for 3 of the 4 days. Modeled clouds lead to departures from the typical clear-sky straight line relating surface H to LE for a given model time, making them easy to detect. With spatial filtering, a straight slope line can be recovered. Similarly, larger filter lengths are needed to produce a stable slope for observed fluxes when there are clouds than for clear skies.

scholarly journals A land surface model combined with a crop growth model for paddy rice (MATCRO-Rice Ver. 1) – Part II: Model validation

2016 ◽  
Author(s):  
Yuji Masutomi ◽  
Keisuke Ono ◽  
Takahiro Takimoto ◽  
Masayoshi Mano ◽  
Atsushi Maruyama ◽  
...  
Keyword(s):  
Heat Flux ◽  
Crop Yield ◽  
Land Surface ◽  
Carbon Flux ◽  
Sensible Heat Flux ◽  
Land Surface Model ◽  
Paddy Rice ◽  
Surface Model ◽  
The Mean ◽  
Mean Square Errors

Abstract. We conducted a comprehensive validation of the simulations by MATCRO-Rice developed by Masutomi et al. (2016). In the validation, we compared simulations with observations for latent heat flux (LHF), sensible heat flux (SHF), net carbon flux, and paddy rice yield from 2003 to 2006. The observation site used for the comparison is located in Tsukuba, Japan, where inputs for running the model and outputs for the validation were fully observed. The 4-year average root mean square errors (RMSEs) between simulations and observations for LHF and SHF were 18.57 and 12.66 W m−2, respectively. These values for errors are comparable to those reported in earlier studies. The comparison of biomass growth during growing periods from 2003 to 2006 shows that the simulations were in agreement with the observations, indicating that the model can reproduce the net carbon flux well. The 4-year average RMSE for crop yield in the same period was 402.4 kg ha−1, which accounted for 7.9 % of the mean observed yields. These results indicate that MATCRO-Rice has high ability to accurately and consistently simulate LHF, SHF, net carbon flux, and crop yield.

scholarly journals Evaluation of the Soil, Vegetation, and Snow (SVS) Land Surface Model for the Simulation of Surface Energy Fluxes and Soil Moisture under Snow-Free Conditions

Atmosphere ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 278 ◽  
Author(s):  
Gonzalo Leonardini ◽  
François Anctil ◽  
Maria Abrahamowicz ◽  
Étienne Gaborit ◽  
Vincent Vionnet ◽  
...  
Keyword(s):  
Heat Flux ◽  
Soil Moisture ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Land Surface Model ◽  
Soil Heat Flux ◽  
Heat Fluxes ◽  
Surface Model ◽  
Point Scale ◽  
Energy Fluxes

The recently developed Soil, Vegetation, and Snow (SVS) land surface model is being progressively implemented at Environment and Climate Change Canada (ECCC) for operational numerical weather and hydrological predictions. The objective of this study is to evaluate the ability of SVS, in offline point-scale mode and under snow-free conditions, to simulate the surface heat fluxes and soil moisture when compared to flux tower observations and simulations from the Canadian Land Surface Scheme (CLASS), used here as a benchmark model. To do this, we performed point-scale simulations of between 4 and 12 years of data records at six selected sites of the FLUXNET network under arid, Mediterranean and tropical climates. At all sites, SVS shows realistic simulations of latent heat flux, sensible heat flux and net radiation. Soil heat flux is reasonably well simulated for the arid sites and one Mediterranean site and poorly simulated for the tropical sites. On the other hand, surface soil moisture was reasonably well simulated at the arid and Mediterranean sites and poorly simulated at the tropical sites. SVS performance was comparable to CLASS not only for energy fluxes and soil moisture, but also for more specific processes such as evapotranspiration and water balance.

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 (1) ◽  
pp. 1559-1598
Author(s):  
T. L. Smallman ◽  
J. B. Moncrieff ◽  
M. Williams
Keyword(s):  
Land Surface ◽  
Wrf Model ◽  
Land Surface Model ◽  
Net Ecosystem Exchange ◽  
Terrestrial Ecosystem ◽  
Co2 Exchange ◽  
Surface Fluxes ◽  
Surface Model ◽  
Terrestrial Ecosystem Model ◽  
Atmospheric Profiles

Abstract. The Weather Research &amp; 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 management/land use 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). WRF-SPA generates more realistic seasonal behaviour at the site level compared to an unmodified version of WRF, and produces realistic CO2 exchanges. 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 indicating appropriate source sink distribution and CO2 exchange. WRF-SPA makes use of CO2 tracer pools and can therefore identify and quantify land surface contributions to the modelled atmospheric CO2 signal at a specified location.

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

&lt;p&gt;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&amp;#160;introduces the CHTESSEL and its recent new developments that aims at hosting new research applications.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;Reference: Souhail Boussetta, Gianpaolo Balsamo*, Anna Agust&amp;#236;-Panareda, Gabriele Arduini, Anton Beljaars, Emanuel Dutra, Glenn Carver, Margarita Choulga, Ioan Hadade, Cinzia Mazzetti, Joaqu&amp;#236;n Mun&amp;#245;z-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).&lt;/p&gt;

scholarly journals Evaluating terrestrial CO<sub>2</sub> flux diagnoses and uncertainties from a simple land surface model and its residuals

2014 ◽  
Vol 11 (2) ◽  
pp. 217-235 ◽  
Author(s):  
T. W. Hilton ◽  
K. J. Davis ◽  
K. Keller
Keyword(s):  
Carbon Dioxide ◽  
Parameter Estimation ◽  
North American ◽  
Land Surface ◽  
Atmospheric Carbon Dioxide ◽  
Ecosystem Respiration ◽  
Land Surface Model ◽  
Net Ecosystem Exchange ◽  
Surface Model ◽  
Considerable Uncertainty

Abstract. Global terrestrial atmosphere–ecosystem carbon dioxide fluxes are well constrained by the concentration and isotopic composition of atmospheric carbon dioxide. In contrast, considerable uncertainty persists surrounding regional contributions to the net global flux as well as the impacts of atmospheric and biological processes that drive the net flux. These uncertainties severely limit our ability to make confident predictions of future terrestrial biological carbon fluxes. Here we use a simple light-use efficiency land surface model (the Vegetation Photosynthesis Respiration Model, VPRM) driven by remotely sensed temperature, moisture, and phenology to diagnose North American gross ecosystem exchange (GEE), ecosystem respiration, and net ecosystem exchange (NEE) for the period 2001 to 2006. We optimize VPRM parameters to eddy covariance (EC) NEE observations from 65 North American FluxNet sites. We use a separate set of 27 cross-validation FluxNet sites to evaluate a range of spatial and temporal resolutions for parameter estimation. With these results we demonstrate that different spatial and temporal groupings of EC sites for parameter estimation achieve similar sum of squared residuals values through radically different spatial patterns of NEE. We also derive a regression model to estimate observed VPRM errors as a function of VPRM NEE, temperature, and precipitation. Because this estimate is based on model-observation residuals it is comprehensive of all the error sources present in modeled fluxes. We find that 1 km interannual variability in VPRM NEE is of similar magnitude to estimated 1 km VPRM NEE errors.

Sign in / Sign up

Export Citation Format

Share Document