Quantifying contributions of uncertainties in physical parameterization schemes and model parameters to overall errors in Noah-MP land modeling using observations from eddy flux sites

2020 ◽  
Author(s):  
Jianduo Li ◽  
Fei Chen
Keyword(s):  
Heat Flux ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Model Performance ◽  
Soil Parameters ◽  
Surface Model ◽  
Model Parameters ◽  
Eddy Flux ◽  
Parameterization Schemes ◽  
Model Improvement

<p>Quantifying contributions of errors in model structure and model parameters to biases in a land surface model (LSM) is critical for model improvement, but has not been done systematically for many global land surface models. This paper investigates the uncertainties in the Noah with multiparameterization (Noah-MP) LSM with dynamic vegetation by examining the interactions between imperfect parameterization schemes (PSs) and improper parameter values (PVs). A number of Noah-MP physical ensemble simulations were conducted at 92 eddy flux sites to quantitatively assess the impacts of the PS uncertainties on model performance, and then the key parameters in the two combinations of schemes with significant differences were calibrated. The results show that five subprocesses—the surface exchange coefficient (SFC), soil moisture threshold, radiation transfer (RAD), runoff and groundwater, and surface resistance to evaporation—have the most significant influence on the performances of simulated sensible heat flux, latent heat flux, net absorbed radiation and gross primary productivity in the Noah-MP LSM with dynamic vegetation, and that the interaction between SFC and RAD contributed up to 80% of the variation in the model performance at some sites. It is also shown that tuning the PSs and optimizing the PVs should be jointly applied to reduce the errors in the Noah-MP LSM, although compared to tuning PSs, parameter optimization happens to make less robust model improvement. Finally, this study emphasizes that reducing the significant uncertainties in soil parameters and exploring the errors caused by missing physical features are crucial to improving LSMs with dynamic vegetation.</p>

scholarly journals A land surface model combined with a crop growth model for paddy rice (MATCRO-Rice v. 1) – Part 2: Model validation

2016 ◽  
Vol 9 (11) ◽  
pp. 4155-4167 ◽  
Author(s):  
Yuji Masutomi ◽  
Keisuke Ono ◽  
Takahiro Takimoto ◽  
Masayoshi Mano ◽  
Atsushi Maruyama ◽  
...  
Keyword(s):  
Heat Flux ◽  
Crop Yield ◽  
Land Surface ◽  
Crop Yields ◽  
Sensible Heat Flux ◽  
Paddy Rice ◽  
Surface Model ◽  
Model Parameters ◽  
Carbon Uptake ◽  
Mean Square Errors

Abstract. We conducted two types of validation for the simulations by MATCRO-Rice developed by Masutomi et al. (2016). In the first validation, we compared simulations with observations for latent heat flux (LHF), sensible heat flux (SHF), net carbon uptake by crop, and paddy rice yield from 2003 to 2006 at the site where model parameters are parameterized. In the second validation, we compared the observed and simulated paddy rice yields over Japan from 1991 to 2010 between observations and simulations. The 4-year average root mean square errors (RMSEs) of the first validation for LHF and SHF were 18.20 and 15.47 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 at the parameterization site shows that the simulations were in agreement with the observations, indicating that the model can reproduce the net carbon uptake by crops well. The 4-year average RMSE of the first validation for crop yield in the same period was 410.6 kg ha−1, which accounted for 8.1 % of the mean observed yields. The error of the second validation for crop yield was 16.7 % and the correlation of crop yields between observations and simulations from 1991 to 2010 was significant at 0.663 (P < 0.01). These results indicate that MATCRO-Rice has high ability to accurately and consistently simulate LHF, SHF, net carbon uptake by crop, and crop yield.

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 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 The interactions between soil–biosphere–atmosphere (ISBA) land surface model multi-energy balance (MEB) option in SURFEXv8 – Part 2: Introduction of a litter formulation and model evaluation for local-scale forest sites

2017 ◽  
Vol 10 (4) ◽  
pp. 1621-1644 ◽  
Author(s):  
Adrien Napoly ◽  
Aaron Boone ◽  
Patrick Samuelsson ◽  
Stefan Gollvik ◽  
Eric Martin ◽  
...  
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Soil Temperature ◽  
Latent Heat ◽  
Land Surface ◽  
Forest Floor ◽  
Land Surface Model ◽  
Local Scale ◽  
Surface Model ◽  
Model Parameters

Abstract. Land surface models (LSMs) need to balance a complicated trade-off between computational cost and complexity in order to adequately represent the exchanges of energy, water and matter with the atmosphere and the ocean. Some current generation LSMs use a simplified or composite canopy approach that generates recurrent errors in simulated soil temperature and turbulent fluxes. In response to these issues, a new version of the interactions between soil–biosphere–atmosphere (ISBA) land surface model has recently been developed that explicitly solves the transfer of energy and water from the upper canopy and the forest floor, which is characterized as a litter layer. The multi-energy balance (MEB) version of ISBA is first evaluated for three well-instrumented contrasting local-scale sites, and sensitivity tests are performed to explore the behavior of new model parameters. Second, ISBA-MEB is benchmarked against observations from 42 forested sites from the global micro-meteorological network (FLUXNET) for multiple annual cycles.It is shown that ISBA-MEB outperforms the composite version of ISBA in improving the representation of soil temperature, ground, sensible and, to a lesser extent, latent heat fluxes. Both versions of ISBA give comparable results in terms of simulated latent heat flux because of the similar formulations of the water uptake and the stomatal resistance. However, MEB produces a better agreement with the observations of sensible heat flux than the previous version of ISBA for 87.5 % of the simulated years across the 42 forested FLUXNET sites. Most of this improvement arises owing to the improved simulation of the ground conduction flux, which is greatly improved using MEB, especially owing to the forest litter parameterization. It is also shown that certain processes are also modeled more realistically (such as the partitioning of evapotranspiration into transpiration and ground evaporation), even if certain statistical performances are neutral. The analyses demonstrate that the shading effect of the vegetation, the explicit treatment of turbulent transfer for the canopy and ground, and the insulating thermal and hydrological effects of the forest floor litter turn out to be essential for simulating the exchange of energy, water and matter across a large range of forest types and climates.

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 The Interactions between Soil-Biosphere-Atmosphere (ISBA) land surface model Multi-Energy Balance (MEB) option in SURFEX – Part 2: Model evaluation for local scale forest sites

2016 ◽  
Author(s):  
Adrien Napoly ◽  
Aaron Boone ◽  
Patrick Samuelsson ◽  
Stefan Gollvik ◽  
Eric Martin ◽  
...  
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Soil Temperature ◽  
Latent Heat ◽  
Land Surface ◽  
Forest Floor ◽  
Land Surface Model ◽  
Local Scale ◽  
Surface Model ◽  
Model Parameters

Abstract. Land surface models (LSMs) need to balance a complicated trade-off between computational cost and complexity in order to adequately represent the exchanges of energy, water and matter with the atmosphere and the ocean. Some current generation LSMs use a simplified or composite canopy approach that generates recurrent errors in simulated soil temperature and turbulent fluxes. In response to these issues, a new version of the Interactions between the Surface Biosphere Atmosphere (ISBA) land surface model has recently been developed which explicitly solves the transfer of energy and water from the upper canopy and the forest floor which is characterized as a litter layer. The so-called Multi Energy Balance (MEB) version of ISBA is first evaluated for three well-instrumented contrasting local scale sites, and sensitivity tests are performed to explore the behavior of new model parameters. Second, ISBA-MEB is benchmarked against observations from 42 forested sites from the global micro-meteorological network (FluxNet) for multiple annual cycles. It is shown that ISBA-MEB outperforms the composite version of ISBA in improving the representation of soil temperature, ground, sensible and to a lesser extent latent heat fluxes. Both versions of ISBA give comparable results in terms of simulated latent heat flux because of the similar formulations of the water uptake and the stomatal resistance. However, MEB produces a better agreement with the observations of sensible heat flux than the previous version of ISBA for 87.5 % of the simulated years across the 42 forested FluxNet sites. Most of this improvement arises owing to the improved simulation of the ground conduction flux, which is greatly improved using MEB, especially owing to the forest litter parameterization. It is also shown that certain processes are also modeled more realistically (such as the partitioning of evapotranspiration into transpiration and ground evaporation), even if certain statistical performances are neutral. The analyses demonstrate that shading effect of the vegetation, the explicit treatment of turbulent transfer for the canopy and ground, and the insulating thermal and hydrological effects of the forest floor litter turn out to be essential for simulating the exchange of energy, water and matter across a large range of forest types and climates.

scholarly journals The Plumbing of Land Surface Models: Benchmarking Model Performance

2015 ◽  
Vol 16 (3) ◽  
pp. 1425-1442 ◽  
Author(s):  
M. J. Best ◽  
G. Abramowitz ◽  
H. R. Johnson ◽  
A. J. Pitman ◽  
G. Balsamo ◽  
...  
Keyword(s):  
Heat Flux ◽  
Land Surface ◽  
Model Performance ◽  
Land Surface Model ◽  
Shortwave Radiation ◽  
Surface Model ◽  
Land Surface Models ◽  
Downward Shortwave Radiation ◽  
Surface Models ◽  
Physically Based

Abstract The Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) was designed to be a land surface model (LSM) benchmarking intercomparison. Unlike the traditional methods of LSM evaluation or comparison, benchmarking uses a fundamentally different approach in that it sets expectations of performance in a range of metrics a priori—before model simulations are performed. This can lead to very different conclusions about LSM performance. For this study, both simple physically based models and empirical relationships were used as the benchmarks. Simulations were performed with 13 LSMs using atmospheric forcing for 20 sites, and then model performance relative to these benchmarks was examined. Results show that even for commonly used statistical metrics, the LSMs’ performance varies considerably when compared to the different benchmarks. All models outperform the simple physically based benchmarks, but for sensible heat flux the LSMs are themselves outperformed by an out-of-sample linear regression against downward shortwave radiation. While moisture information is clearly central to latent heat flux prediction, the LSMs are still outperformed by a three-variable nonlinear regression that uses instantaneous atmospheric humidity and temperature in addition to downward shortwave radiation. These results highlight the limitations of the prevailing paradigm of LSM evaluation that simply compares an LSM to observations and to other LSMs without a mechanism to objectively quantify the expectations of performance. The authors conclude that their results challenge the conceptual view of energy partitioning at the land surface.

scholarly journals Simulation and Analysis of Land-Surface Processes in the Taklimakan Desert Based on Noah LSM

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Huoqing Li ◽  
Ali Mamtimin ◽  
Chenxiang Ju
Keyword(s):  
Heat Flux ◽  
Soil Moisture ◽  
Land Surface ◽  
Exchange Process ◽  
Model Performance ◽  
Surface Model ◽  
Taklimakan Desert ◽  
Observation Data ◽  
Net Radiation ◽  
The Taklimakan Desert

This study evaluated the Noah land-surface model performance to simulate the land-surface process during different weather conditions in the hinterland of the Taklimakan Desert. This study is based on observation data from the Taklimakan Desert Meteorology Field Experiment Station in 2014. The results illustrated that the energy-exchange process between the land surface and the atmosphere in the drifting desert can be simulated by Noah effectively. However, the effects of soil moisture and latent heat flux were very poor. For sunny days, the soil temperature and heat flux were underestimated significantly in the nighttime and overestimated in the daytime. The simulation results are very good in sand-dust weather. The simulation of heat flux and net radiation is very consistent with the observation during cloudy days. For rainy days, the model can successfully model the diurnal variation of soil moisture, but it has obvious deviations in the net radiation, heat flux, and soil heat flux.

scholarly journals ORCHIDEE-MICT (revision 4126), a land surface model for the high-latitudes: model description and validation

2017 ◽  
Author(s):  
Matthieu Guimberteau ◽  
Dan Zhu ◽  
Fabienne Maignan ◽  
Ye Huang ◽  
Chao Yue ◽  
...  
Keyword(s):  
High Latitude ◽  
Land Surface ◽  
Model Performance ◽  
Land Surface Model ◽  
Co2 Flux ◽  
Model Description ◽  
Surface Model ◽  
Model Parameters ◽  
Terrestrial Environment ◽  
Temperature Bias

Abstract. The high-latitude regions of the northern hemisphere are a nexus for the interaction between land surface physical properties and their exchange of carbon and energy with the atmosphere. At these latitudes, two carbon pools of planetary significance – those of the permanently frozen soils (permafrost), and of the great expanse of boreal forest – are vulnerable to destabilization in the face of currently observed climatic warming, the speed and intensity of which are expected to increase with time. Improved projections of future Arctic and boreal ecosystem transformation require improved land surface models that integrate processes specific to these cold biomes. To this end, this study lays out relevant new parameterizations in the ORCHIDEE-MICT land surface model. These describe the interactions between soil carbon, soil temperature and hydrology, and their resulting feedbacks on water and CO2 fluxes, in addition to a recently-developed fire module. Outputs from ORCHIDEE-MICT, when forced by two climate input data sets, are extensively evaluated against: (i) temperature gradients between the atmosphere and deep soils; (ii) the hydrological components comprising the water balance of the largest high-latitude basins, and (iii) CO2 flux and carbon stock observations. The model performance is good with respect to empirical data, despite a simulated excessive plant water stress and a positive land surface temperature bias. In addition, acute model sensitivity to the choice of input forcing data suggests that the calibration of model parameters is strongly forcing-dependent. Overall, we suggest that this new model design is at the forefront of current efforts to reliably estimate future perturbations to the high-latitude terrestrial environment.

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

2014 ◽  
Vol 11 (12) ◽  
pp. 16911-16951
Author(s):  
J. Ingwersen ◽  
K. Imukova ◽  
P. Högy ◽  
T. Streck
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Eddy Covariance ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Bowen Ratio ◽  
Surface Model ◽  
Flux Data ◽  
Uncertainty Band ◽  
Closure Method

Abstract. The energy balance of eddy covariance (EC) flux data is normally not closed. Therefore, at least if used for modeling, 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 method 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 of 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.

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