Can a physically-based land surface model accurately represent evapotranspiration partitioning? A case study in a humid boreal forest

2021 ◽  
Vol 304-305 ◽  
pp. 108410
Author(s):  
Bram Hadiwijaya ◽  
Pierre-Erik Isabelle ◽  
Daniel F. Nadeau ◽  
Steeve Pepin
Keyword(s):  
Boreal Forest ◽  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
Physically Based ◽  
Evapotranspiration Partitioning

scholarly journals Introducing Hysteresis in Snow Depletion Curves to Improve the Water Budget of a Land Surface Model in an Alpine Catchment

2014 ◽  
Vol 15 (2) ◽  
pp. 631-649 ◽  
Author(s):  
Claire Magand ◽  
Agnès Ducharne ◽  
Nicolas Le Moine ◽  
Simon Gascoin
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Water Budget ◽  
Land Surface Model ◽  
Surface Model ◽  
Depletion Curve ◽  
Physically Based ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference ◽  
Snow Model

Abstract The Durance watershed (14 000 km2), located in the French Alps, generates 10% of French hydropower and provides drinking water to 3 million people. The Catchment land surface model (CLSM), a distributed land surface model (LSM) with a multilayer, physically based snow model, has been applied in the upstream part of this watershed, where snowfall accounts for 50% of the precipitation. The CLSM subdivides the upper Durance watershed, where elevations range from 800 to 4000 m within 3580 km2, into elementary catchments with an average area of 500 km2. The authors first show the difference between the dynamics of the accumulation and ablation of the snow cover using Moderate Resolution Imaging Spectroradiometer (MODIS) images and snow-depth measurements. The extent of snow cover increases faster during accumulation than during ablation because melting occurs at preferential locations. This difference corresponds to the presence of a hysteresis in the snow-cover depletion curve of these catchments, and the CLSM was adapted by implementing such a hysteresis in the snow-cover depletion curve of the model. Different simulations were performed to assess the influence of the parameterizations on the water budget and the evolution of the extent of the snow cover. Using six gauging stations, the authors demonstrate that introducing a hysteresis in the snow-cover depletion curve improves melting dynamics. They conclude that their adaptation of the CLSM contributes to a better representation of snowpack dynamics in an LSM that enables mountainous catchments to be modeled for impact studies such as those of climate change.

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 Analysis of WRF Model Performance over Subtropical Region of Delhi, India

2011 ◽  
Vol 2011 ◽  
pp. 1-13 ◽  
Author(s):  
Manju Mohan ◽  
Shweta Bhati
Keyword(s):  
Surface Layer ◽  
Land Surface ◽  
Model Performance ◽  
Wrf Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Subtropical Region ◽  
Statistical Measures ◽  
Current Availability

Model performance and sensitivity to model physics options are studied with the Weather Research and Forecasting model (version 3.1.1) over Delhi region in India for surface and upper air meteorological parameters in summer and winter seasons. A case study with the model has been performed with different configurations, and the best physics options suited for this region have been, determined. Comparison between estimated and observed data was carried out through standard statistical measures. Generally, the combination of Pleim-Xiu land surface model, Pleim surface layer scheme, and Asymmetric Convective Model has been found to produce better estimates of temperature and relative humidity for Delhi region. Wind speed and direction estimations were observed best for MM5 similarity surface layer along with Yonsei University boundary layer scheme. Nested domains with higher resolutions were not helpful in improving the simulation results as per the current availability of the data. Overall, the present case study shows that the model has performed reasonably well over the subtropical region of Delhi.

scholarly journals Technical Note: Evaluation of the Skill in Monthly-to-Seasonal Soil Moisture Forecasting Based on SMAP Satellite Observations over the Southeast US

2019 ◽  
Author(s):  
Amirhossein Mazrooei ◽  
Venkat Lakshmi ◽  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Weather Forecasting ◽  
Land Surface Model ◽  
Technical Note ◽  
Surface Model ◽  
Lead Times ◽  
Agricultural Planning ◽  
Southeast Us

Abstract. Providing accurate soil moisture (SM) conditions is a critical step in model initialization in weather forecasting, agricultural planning, and water resources management. This study develops monthly to seasonal (M2S) top layer SM forecasts by forcing 1–3 month ahead precipitation forecasts with Noah3.2 Land Surface Model. The SM forecasts are developed over the Southeast US (SEUS) and the SM forecasting skill is evaluated in comparison with the remotely sensed SM observations collected by Soil Moisture Active Passive (SMAP) satellite. Our results indicate potential in developing real-time SM forecasts. The retrospective 18-months (April 2015–September 2016) comparison between SM forecasts and the SMAP observations shows statistically significant correlations of 0.62, 0.57, and 0.58 over 1–3 month lead times respectively. As a case study, the evaluation of the issued forecasts based on the drought indexes monitored during the 2007 historical drought over the SEUS also indicate promising skill in monthly SM forecasting to support agricultural planning and water management for such natural hazards.

scholarly journals Performance evaluation of the WRF model in a tropical region: wind speed analysis at different sites

2021 ◽  
Author(s):  
Noéle Bissoli Perini Souza ◽  
Erick Giovani Sperandio Nascimento ◽  
Davidson Martins Moreira
Keyword(s):  
Wind Speed ◽  
Land Surface ◽  
Wrf Model ◽  
Land Surface Model ◽  
Weather Research And Forecasting ◽  
Tropical Region ◽  
Surface Model ◽  
Dry And Rainy Seasons

In this study, the performance of the mesoscale Weather Research and Forecasting (WRF) model is evaluated using combinations of three Planetary Boundary Layer (PBL) and three Land Surface Model (LSM) schemes, in order to identify the optimal parameters for the determination of wind speed in a tropical region. The state of Bahia in Brazil is selected as the location for the case study and simulations are performed over a period of eight months between 2015 and 2016. This is done to ensure that the dry and rainy seasons at the three different experimental sites—Esplanada, Mucuri, and Mucugê—are well separated from each other. The results of the simulations are compared with the observational data obtained from three towers equipped with anemometers at heights of 80, 100, 120 and 150 m, strategically placed at each site. Overestimation of wind speed is observed in the simulations, despite similarities between the simulated and observed wind directions. In addition, the accuracies of simulations corresponding to sites that are closer to the ocean are observed to be lower—the most accurate wind speed estimates are obtained corresponding to Mucugê, which is located farthest from the ocean. Finally, analysis of the results obtained from each tower accounting for periods with higher and lower precipitation reveals that the combination of the PBL-YSU scheme with the LSM-RUC scheme yields the best results.

scholarly journals Ensemble Evaluation of Hydrologically Enhanced Noah-LSM: Partitioning of the Water Balance in High-Resolution Simulations over the Little Washita River Experimental Watershed

2011 ◽  
Vol 12 (1) ◽  
pp. 45-64 ◽  
Author(s):  
Enrique Rosero ◽  
Lindsey E. Gulden ◽  
Zong-Liang Yang ◽  
Luis G. De Goncalves ◽  
Guo-Yue Niu ◽  
...  
Keyword(s):  
Water Table ◽  
Land Surface ◽  
Water Cycle ◽  
Land Surface Model ◽  
Surface Model ◽  
Model Parameters ◽  
Shallow Water Table ◽  
Total Runoff ◽  
Physically Based ◽  
Subsurface Runoff

Abstract The ability of two versions of the Noah land surface model (LSM) to simulate the water cycle of the Little Washita River experimental watershed is evaluated. One version that uses the standard hydrological parameterizations of Noah 2.7 (STD) is compared another version that replaces STD’s subsurface hydrology with a simple aquifer model and topography-related surface and subsurface runoff parameterizations (GW). Simulations on a distributed grid at fine resolution are compared to the long-term distribution of observed daily-mean runoff, the spatial statistics of observed soil moisture, and locally observed latent heat flux. The evaluation targets the typical behavior of ensembles of models that use realistic, near-optimal sets of parameters important to runoff. STD and GW overestimate the ratio of runoff to evapotranspiration. In the subset of STD and GW runs that best reproduce the timing and the volume of streamflow, the surface-to-subsurface runoff ratio is overestimated and simulated streamflow is much flashier than observations. Both models’ soil columns wet and dry too quickly, implying that there are structural shortcomings in the formulation of STD that cannot be overcome by adding GW’s increased complexity to the model. In its current formulation, GW extremely underestimates baseflow’s contribution to total runoff and requires a shallow water table to function realistically. In the catchment (depth to water table >10 m), GW functions as a simple bucket model. Because model parameters are likely scale and site dependent, the need for even “physically based” models to be extensively calibrated for all domains on which they are applied is underscored.

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