scholarly journals Mesoscale modelling of the CO<sub>2</sub> interactions between the surface and the atmosphere applied to the April 2007 CERES field experiment

2009 ◽  
Vol 6 (4) ◽  
pp. 633-646 ◽  
Author(s):  
C. Sarrat ◽  
J. Noilhan ◽  
P. Lacarrère ◽  
E. Ceschia ◽  
P. Ciais ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Land Surface ◽  
Mesoscale Model ◽  
Regional Scale ◽  
Co2 Concentration ◽  
Surface Model ◽  
Model Errors ◽  
Spatial Integration ◽  
Area Index ◽  
Aircraft Observations

Abstract. This paper describes a numerical interpretation of the April 2007, CarboEurope Regional Experiment Strategy (CERES) campaign, devoted to the study of the CO2 cycle at the regional scale. Four consecutive clear sky days with intensive observations of CO2 concentration, fluxes at the surface and in the boundary layer have been simulated with the Meso-NH mesoscale model, coupled to ISBA-A-gs land surface model. The main result of this paper is to show how aircraft observations of CO2 concentration have been used to identify surface model errors and to calibrate the CO2 driving component of the surface model. In fact, the comparisons between modelled and observed CO2 concentrations within the Atmospheric Boundary Layer (ABL) allow to calibrate and correct not only the parameterization of respired CO2 fluxes by the ecosystem but also the Leaf Area Index (LAI) of the dominating land cover. After this calibration, the paper describes systematic comparisons of the model outputs with numerous data collected during the CERES campaign, in April 2007. For instance, the originality of this paper is the spatial integration of the comparisons. In fact, the aircraft observations of CO2 concentration and fluxes and energy fluxes are used for the model validation from the local to the regional scale. As a conclusion, the CO2 budgeting approach from the mesoscale model shows that the winter croplands are assimilating more CO2 than the pine forest, at this stage of the year and this case study.

scholarly journals Mesoscale modeling of the CO<sub>2</sub> interactions between the surface and the atmosphere applied to the April 2007 CERES field experiment

2009 ◽  
Vol 6 (1) ◽  
pp. 515-544 ◽  
Author(s):  
C. Sarrat ◽  
J. Noilhan ◽  
P. Lacarrère ◽  
A. J. Dolman ◽  
C. Gerbig ◽  
...  
Keyword(s):  
Mesoscale Model ◽  
Regional Scale ◽  
Co2 Concentration ◽  
Mesoscale Modeling ◽  
Surface Model ◽  
Surface Modelling ◽  
Clear Sky ◽  
Aircraft Observations ◽  
Model Aircraft ◽  
Intensive Observations

Abstract. The paper describes a numerical interpretation of the April 2007 CarboEurope Regional Experiment Strategy (CERES) campaign, devotedto the study of CO2 cycle at the regional scale. The four consecutive clear sky days with intensive observations of CO2 concentration, fluxes at the the surface and in the boundary layer have been simulated with the Meso-NH mesoscale model. Aircraft observations of CO2 have been used to identify surface modelling errors and to calibrate the CO2 components of the surface model. After this calibration, the paper describes a systematic comparison of the model outputs with all the data collected during CERES, in April 2007. As a conclusion, an example of CO2 budgeting from the mesoscale model is given.

Assimilation of vegetation conditions improves the representation of drought over agricultural areas

2021 ◽  
Author(s):  
David M. Mocko ◽  
Sujay V. Kumar ◽  
Christa D. Peters-Lidard ◽  
Shugong Wang
Keyword(s):  
Land Surface ◽  
Land Surface Model ◽  
Agricultural Drought ◽  
False Alarms ◽  
Surface Model ◽  
Model Errors ◽  
Physical Processes ◽  
Area Index ◽  
Agricultural Areas ◽  
The Impact

AbstractThis study presents an evaluation of the impact of vegetation conditions on a land-surface model (LSM) simulation of agricultural drought. The Noah-MP LSM is used to simulate water and energy fluxes and states, which are transformed into drought categories using percentiles over the continental U.S. from 1979 to 2017. Leaf Area Index (LAI) observations are assimilated into the dynamic vegetation scheme of Noah-MP. A weekly operational drought monitor (the U.S. Drought Monitor) is used for the evaluation. The results show that LAI assimilation into Noah-MP’s dynamic vegetation scheme improves the model's ability to represent drought, particularly over cropland areas. LAI assimilation improves the simulation of the drought category, detection of drought conditions, and reduces the instances of drought false alarms. The assimilation of LAI in these locations not only corrects model errors in the simulation of vegetation, but also can help to represent unmodeled physical processes such as irrigation towards improved simulation of agricultural drought.

Is the annual maximum leaf area index an important driver of water fluxes simulated by a land surface model in temperate forests?

2021 ◽  
pp. 1-9
Author(s):  
Audrey Maheu ◽  
Cybèle Cholet ◽  
Rebeca Cordero Montoya ◽  
Louis Duchesne
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Land Surface ◽  
Regional Scale ◽  
Surface Model ◽  
Annual Maximum ◽  
Water Fluxes ◽  
Mixed Forests ◽  
Area Index ◽  
Study Region

In land surface models, vegetation is often described using plant functional types (PFTs), a classification that aggregates plant species into a few groups based on similar characteristics. Within-PFT variability of these characteristics can introduce considerable uncertainty in the simulation of water fluxes in forests. Our objectives were to (i) compare the variability of the annual maximum leaf area index (LAImax) within and between PFTs and (ii) assess whether this variability leads to significant differences in simulated water fluxes at a regional scale. We classified our study region in southwestern Quebec (Canada) into three PFTs (evergreen needleleaf, deciduous broadleaf, and mixed forests) and characterized LAImax using remotely sensed MODIS-LAI data. We simulated water fluxes with the Canadian Land Surface Scheme (CLASS) and performed a sensitivity analysis. We found that within-PFT variability of LAImax was 1.7 times more important than variability between PFTs, with similar mean values for the two dominant PFTs, deciduous broadleaf forests (6.6 m2·m−2) and mixed forests (6.3 m2·m−2). In CLASS, varying LAImax within the observed range of values (4.0–7.5 m2·m−2) led to changes of less than 2% in mean evapotranspiration. Overall, LAImax is likely not an important driver of the spatial variability of water fluxes at the regional level.

Development and Evaluation of a Coupled Photosynthesis-Based Gas Exchange Evapotranspiration Model (GEM) for Mesoscale Weather Forecasting Applications

2009 ◽  
Vol 48 (2) ◽  
pp. 349-368 ◽  
Author(s):  
Dev Niyogi ◽  
Kiran Alapaty ◽  
Sethu Raman ◽  
Fei Chen
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Gas Exchange ◽  
Surface Energy ◽  
Land Surface ◽  
Weather Forecasting ◽  
Stomatal Resistance ◽  
Surface Fluxes ◽  
Surface Model ◽  
Area Index

Abstract Current land surface schemes used for mesoscale weather forecast models use the Jarvis-type stomatal resistance formulations for representing the vegetation transpiration processes. The Jarvis scheme, however, despite its robustness, needs significant tuning of the hypothetical minimum-stomatal resistance term to simulate surface energy balances. In this study, the authors show that the Jarvis-type stomatal resistance/transpiration model can be efficiently replaced in a coupled land–atmosphere model with a photosynthesis-based scheme and still achieve dynamically consistent results. To demonstrate this transformative potential, the authors developed and coupled a photosynthesis, gas exchange–based surface evapotranspiration model (GEM) as a land surface scheme for mesoscale weather forecasting model applications. The GEM was dynamically coupled with a prognostic soil moisture–soil temperature model and an atmospheric boundary layer (ABL) model. This coupled system was then validated over different natural surfaces including temperate C4 vegetation (prairie grass and corn field) and C3 vegetation (soybean, fallow, and hardwood forest) under contrasting surface conditions (such as different soil moisture and leaf area index). Results indicated that the coupled model was able to realistically simulate the surface fluxes and the boundary layer characteristics over different landscapes. The surface energy fluxes, particularly for latent heat, are typically within 10%–20% of the observations without any tuning of the biophysical–vegetation characteristics, and the response to the changes in the surface characteristics is consistent with observations and theory. This result shows that photosynthesis-based transpiration/stomatal resistance models such as GEM, despite various complexities, can be applied for mesoscale weather forecasting applications. Future efforts for understanding the different scaling parameterizations and for correcting errors for low soil moisture and/or wilting vegetation conditions are necessary to improve model performance. Results from this study suggest that the GEM approach using the photosynthesis-based soil vegetation atmosphere transfer (SVAT) scheme is thus superior to the Jarvis-based approaches. Currently GEM is being implemented within the Noah land surface model for the community Weather Research and Forecasting (WRF) Advanced Research Version Modeling System (ARW) and the NCAR high-resolution land data assimilation system (HRLDAS), and validation is under way.

scholarly journals Modelling LAI at a regional scale with ISBA-A-gs: comparison with satellite-derived LAI over southwestern France

2009 ◽  
Vol 6 (8) ◽  
pp. 1389-1404 ◽  
Author(s):  
A. Brut ◽  
C. Rüdiger ◽  
S. Lafont ◽  
J.-L. Roujean ◽  
J.-C. Calvet ◽  
...  
Keyword(s):  
Land Surface ◽  
Regional Scale ◽  
Land Surface Model ◽  
Temperature Response ◽  
Climatic Conditions ◽  
Surface Model ◽  
Model Parameters ◽  
Area Index ◽  
Satellite Signal

Abstract. A CO2-responsive land surface model (the ISBA-A-gs model of Météo-France) is used to simulate photosynthesis and Leaf Area Index (LAI) in southwestern France for a 3-year period (2001–2003). A domain of about 170 000 km2 is covered at a spatial resolution of 8 km. The capability of ISBA-A-gs to reproduce the seasonal and the interannual variability of LAI at a regional scale, is assessed with satellite-derived LAI products. One originates from the CYCLOPES programme using SPOT/VEGETATION data, and two products are based on MODIS data. The comparison reveals discrepancies between the satellite LAI estimates and between satellite and simulated LAI values, both in their intensity and in the timing of the leaf onset. The model simulates higher LAI values for the C3 crops than the satellite observations, which may be due to a saturation effect within the satellite signal or to uncertainties in model parameters. The simulated leaf onset presents a significant delay for C3 crops and mountainous grasslands. In-situ observations at a mid-altitude grassland site show that the generic temperature response of photosynthesis used in the model is not appropriate for plants adapted to the cold climatic conditions of the mountainous areas. This study demonstrates the potential of LAI remote sensing products for identifying and locating models' shortcomings at a regional scale.

scholarly journals Development and Testing of Polar Weather Research and Forecasting (WRF) Model. Part I: Greenland Ice Sheet Meteorology*

2008 ◽  
Vol 136 (6) ◽  
pp. 1971-1989 ◽  
Author(s):  
Keith M. Hines ◽  
David H. Bromwich
Keyword(s):  
Boundary Layer ◽  
Land Surface ◽  
Mesoscale Model ◽  
Ice Sheet ◽  
Wrf Model ◽  
Greenland Ice Sheet ◽  
Forecast Skill ◽  
Weather Research And Forecasting ◽  
Surface Model ◽  
Weather Research

Abstract A polar-optimized version of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) was developed to fill climate and synoptic needs of the polar science community and to achieve an improved regional performance. To continue the goal of enhanced polar mesoscale modeling, polar optimization should now be applied toward the state-of-the-art Weather Research and Forecasting (WRF) Model. Evaluations and optimizations are especially needed for the boundary layer parameterization, cloud physics, snow surface physics, and sea ice treatment. Testing and development work for Polar WRF begins with simulations for ice sheet surface conditions using a Greenland-area domain with 24-km resolution. The winter month December 2002 and the summer month June 2001 are simulated with WRF, version 2.1.1, in a series of 48-h integrations initialized daily at 0000 UTC. The results motivated several improvements to Polar WRF, especially to the Noah land surface model (LSM) and the snowpack treatment. Different physics packages for WRF are evaluated with December 2002 simulations that show variable forecast skill when verified with the automatic weather station observations. The WRF simulation with the combination of the modified Noah LSM, the Mellor–Yamada–Janjić boundary layer parameterization, and the WRF single-moment microphysics produced results that reach or exceed the success standards of a Polar MM5 simulation for December 2002. For summer simulations of June 2001, WRF simulates an improved surface energy balance, and shows forecast skill nearly equal to that of Polar MM5.

Performance Assessment of New Land Surface and Planetary Boundary Layer Physics in the WRF-ARW

2010 ◽  
Vol 49 (4) ◽  
pp. 760-774 ◽  
Author(s):  
Robert C. Gilliam ◽  
Jonathan E. Pleim
Keyword(s):  
Boundary Layer ◽  
Air Quality ◽  
Planetary Boundary Layer ◽  
Land Surface ◽  
Mesoscale Model ◽  
New Physics ◽  
The Other ◽  
Surface Model ◽  
Temperature Structure ◽  
Near Surface

Abstract The Pleim–Xiu land surface model, Pleim surface layer scheme, and Asymmetric Convective Model (version 2) are now options in version 3.0 of the Weather Research and Forecasting model (WRF) Advanced Research WRF (ARW) core. These physics parameterizations were developed for the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) and have been used extensively by the air quality modeling community, so there was a need based on several factors to extend these parameterizations to WRF. Simulations executed with the new WRF physics are compared with simulations produced with the MM5 and another WRF configuration with a focus on the replication of near-surface meteorological conditions and key planetary boundary layer features. The new physics in WRF is recommended for retrospective simulations, in particular, those used to drive air quality simulations. In the summer, the error of all variables analyzed was slightly lower across the domain in the WRF simulation that used the new physics than in the similar MM5 configuration. This simulation had an even lower error than the other more common WRF configuration. For the cold season case, the model simulation was not as accurate as the other simulations overall, but did well in terms of lower 2-m temperature error in the western part of the model domain (plains and Rocky Mountains) and most of the Northeast. Both MM5 and the other WRF configuration had lower errors across much of the southern and eastern United States in the winter. The 2-m water vapor mixing ratio and 10-m wind were generally well simulated by the new physics suite in WRF when contrasted with the other simulations and modeling studies. Simulated planetary boundary layer features were compared with both wind profiler and aircraft observations, and the new WRF physics results in a more precise wind and temperature structure not only in the stable boundary layer, but also within most of the convective boundary layer. These results suggest that the WRF performance is now at or above the level of MM5. It is thus recommended to drive future air quality applications.

scholarly journals Integrated validation of assimilating satellite derived observations over France using a hydrological model

2016 ◽  
Author(s):  
D. Fairbairn ◽  
A. L. Barbu ◽  
A. Napoly ◽  
C. Albergel ◽  
J.-F. Mahfouf ◽  
...  
Keyword(s):  
Land Surface ◽  
Radiative Forcing ◽  
River Discharge ◽  
Hydrological Model ◽  
Hydrological Cycle ◽  
Wave Radiation ◽  
Surface Model ◽  
Model Errors ◽  
Area Index ◽  
Observation Operator

Abstract. This study assesses the impacts of assimilating surface soil moisture (SSM) and leaf area index (LAI) observations on river discharge using the SAFRAN-ISBA-MODCOU (SIM) hydrological model. The SIM hydrological model consists of three stages: (1) An atmospheric reanalysis (SAFRAN) over France, which forces (2) a land surface model (ISBA-A-gs), which then provides drainage and runoff inputs to (3) a hydrogeological model (MODCOU). The river discharge from MODCOU is validated using observed river discharge over France from over 500 gauges. The SAFRAN forcing underestimates direct short-wave and long-wave radiation by approximately 5% averaged over France. The ISBA-A-gs model also significantly underestimates the grassland LAI compared with satellite retrievals during winter dormancy. These differences result in an under-estimation (overestimation) of evapotranspiration (drainage and runoff). The excess water flowing into the rivers and aquifers contributes to an overestimation of the SIM discharge. We attempted to resolve these problems by performing the following experiments: (i) a correction of the minimum LAI model parameter for grasslands, (ii) a bias-correction of the model radiative forcing, (iii) the assimilation of LAI observations and (iv) the assimilation of SSM and LAI observations. The data assimilation for (iii) and (iv) was done with a simplified extended Kalman filter (SEKF), which uses finite differences in the observation operator Jacobians to relate the observations to the model variables. Experiments (i) and (ii) improved the average SIM Nash scores by about 12 % and 20 % respectively. Experiment (iii) reduced the LAI phase errors in ISBA-A-gs but only slightly improved the discharge Nash effciency of SIM (by just 2 %). In contrast, experiment (iv) resulted in spurious increases in drainage and runoff, which degraded the discharge Nash effciency by about 35%. The poor performance of the SEKF is an artifact of the observation operator Jacobians. These Jacobians are dampened when the soil is saturated and when the vegetation is dormant, which leads to positive biases in drainage/runoff and insuffcient corrections to the LAI minimum, respectively. This motivates the development of a DA method that can take into account model errors and atmospheric forcing errors. The results also highlight the important role that vegetation plays on the hydrological cycle. It is recommended that a spatially variable LAI minimum parameter be introduced into ISBA-A-gs based on the lowest LAI values derived from satellite observations.

scholarly journals Importance of crop varieties and management practices: evaluation of a process-based model for simulating CO<sub>2</sub> and H<sub>2</sub>O fluxes at five European maize (<i>Zea mays</i> L.) sites

2011 ◽  
Vol 8 (6) ◽  
pp. 1721-1736 ◽  
Author(s):  
L. Li ◽  
N. Vuichard ◽  
N. Viovy ◽  
P. Ciais ◽  
T. Wang ◽  
...  
Keyword(s):  
Land Surface ◽  
Management Practices ◽  
Ecosystem Respiration ◽  
Gross Primary Production ◽  
Land Surface Model ◽  
Terrestrial Ecosystem ◽  
Surface Model ◽  
Model Errors ◽  
Area Index ◽  
European Maize

Abstract. This paper is a modelling study of crop management impacts on carbon and water fluxes at a range of European sites. The model is a crop growth model (STICS) coupled with a process-based land surface model (ORCHIDEE). The data are online eddy-covariance observations of CO2 and H2O fluxes at five European maize cultivation sites. The results show that the ORCHIDEE-STICS model explains up to 75 % of the observed daily net CO2 ecosystem exchange (NEE) variance, and up to 79 % of the latent heat flux (LE) variance at five sites. The model is better able to reproduce gross primary production (GPP) variations than terrestrial ecosystem respiration (TER) variations. We conclude that structural deficiencies in the model parameterizations of leaf area index (LAI) and TER are the main sources of error in simulating CO2 and H2O fluxes. A number of sensitivity tests, with variable crop variety, nitrogen fertilization, irrigation, and planting date, indicate that any of these management factors is able to change NEE by more than 15 %, but that the response of NEE to management parameters is highly site-dependent. Changes in management parameters are found to impact not only the daily values of NEE and LE, but also the cumulative yearly values. In addition, LE is shown to be less sensitive to management parameters than NEE. Multi-site model evaluations, coupled with sensitivity analysis to management parameters, thus provide important information about model errors, which helps to improve the simulation of CO2 and H2O fluxes across European croplands.

scholarly journals Modelling LAI at a regional scale with ISBA-A-gs: comparison with satellite-derived LAI over southwestern France

2009 ◽  
Vol 6 (2) ◽  
pp. 4059-4093
Author(s):  
A. Brut ◽  
C. Rüdiger ◽  
S. Lafont ◽  
J.-L. Roujean ◽  
J.-C. Calvet ◽  
...  
Keyword(s):  
Land Surface ◽  
Regional Scale ◽  
Land Surface Model ◽  
Temperature Response ◽  
Climatic Conditions ◽  
Surface Model ◽  
Area Index ◽  
Satellite Signal ◽  
Grassland Site

Abstract. A CO2-responsive land surface model (the ISBA-A-gs model of Météo-France) is used to simulate photosynthesis and Leaf Area Index (LAI) in southwestern France for a 3-year period (2001–2003). A domain of about 170 000 km2 is covered at a spatial resolution of 8 km. The capability of ISBA-A-gs to reproduce the seasonal and the inter-annual variability of LAI at a regional scale, is assessed with two satellite-derived LAI products. One originates from the CYCLOPES programme using SPOT/VEGETATION data, and the second is based on MODIS data. The comparison reveals discrepancies between the two satellite LAI estimates and between satellite and simulated LAI values, both in their intensity and in the timing of the leaf onset. The model simulates higher LAI values for the C3 crops and coniferous trees than the satellite observations, which may be due to a saturation effect within the satellite signal. The simulated leaf onset presents a significant delay for mountainous grasslands. In-situ observations at a mid-altitude grassland site show that the generic temperature response of photosynthesis used in the model is not appropriate for plants adapted to the cold climatic conditions of the mountainous areas. This study demonstrates the potential of LAI remote sensing products for identifying and locating models' shortcomings at a regional scale.

Sign in / Sign up

Export Citation Format

Share Document