scholarly journals New Representation of Plant Hydraulics Improves the Estimates of Transpiration in Land Surface Model

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 722
Author(s):  
Hongmei Li ◽  
Xingjie Lu ◽  
Zhongwang Wei ◽  
Siguang Zhu ◽  
Nan Wei ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Interannual Variability ◽  
Land Surface ◽  
Moisture Stress ◽  
Hydraulic Redistribution ◽  
Surface Model ◽  
Bias Score ◽  
Plant Hydraulics ◽  
Common Land Model ◽  
Semi Arid

Transpiration represents more than 30% of the global land–atmosphere water exchange but is highly uncertain. Plant hydraulics was ignored in traditional land surface modeling, but recently plant hydraulics has been found to play an essential role in transpiration simulation. A new physical-based representation of plant hydraulic schemes (PHS) was recently developed and implemented in the Common Land Model (CoLM). However, it is unclear to what extent PHS can reduce these uncertainties. Here, we evaluated the PHS against measurements obtained at 81 FLUXNET sites. The transpiration of each site was estimated using an empirical evapotranspiration partitioning approach. The metric scores defined by the International Land Model Benchmarking Project (ILAMB) were used to evaluate the model performance and compare it with that of the CoLM default scheme (soil moisture stress (SMS)). The bias score of transpiration in PHS was higher than SMS for most sites, and more significant improvements were found in semi-arid and arid sites where transpiration was limited by soil moisture. The hydraulic redistribution in PHS optimized the soil water supply and thus improved the transpiration estimates. In humid sites, no significant improvement in seasonal or interannual variability of transpiration was simulated by PHS, which can be explained by the insensitivity of transpiration demand coupled to the photosynthesis response to precipitation. In arid and semi-arid sites, seasonal or interannual variability of transpiration was better captured by PHS than SMS, which was interpreted by the improved drought sensitivity for transpiration. Arid land is widespread and is expected to expand due to climate change, thus there is an urgent need to couple PHS in land surface models.

What’s the impact of improved soil representations in the ECMWF land surface model and how does it affect the extremes?

2021 ◽  
Author(s):  
Souhail Boussetta ◽  
Gabriele Arduini ◽  
Gianpaolo Balsamo ◽  
Emanuel Dutra ◽  
Anna Agusti-Panareda ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Soil Depth ◽  
Soil Column ◽  
Carbon Fluxes ◽  
Moisture Stress ◽  
Rooting Depth ◽  
Surface Model ◽  
Soil Moisture Stress ◽  
The Impact

<p>With increasingly higher spatial resolution and a broader applications, the importance of soil representation (e.g. soil depth, vertical discretisation, vegetation rooting) within land surface models is enhanced. Those modelling choices actually affects the way land surfaces store and regulate water, energy and also carbon fluxes. Heat and water vapour fluxes towards the atmosphere and deeper soil, exhibit variations spanning a range of time scales from minutes to months in the coupled land-atmosphere system. This is further modulated by the vertical roots' distribution, and soil moisture stress function, which control evapotranspiration under soil moisture stress conditions. Currently in the ECMWF land Surface Scheme the soil column is represented by a fixed 4 layers configuration with a total of approximately 3m depth.</p><p>In the present study we explore new configurations with increased soil depth (up to 8m) and higher vertical discretisation (up to 10 layers) including a dissociation between the treatment of water and heat fluxes. Associated with the soil vertical resolution, the vertical distribution of roots is also investigated. A new scheme that assumes a uniform root distribution with an associated maximum rooting depth is explored. The impact of these new configurations is assessed through surface offline simulations driven by the ERA5 meteorological forcing against in-situ and global products of energy, water and carbon fluxes with a particular focus on the diurnal cycle and extreme events in recent years.</p>

scholarly journals Implementation of a soil albedo scheme in the CABLEv1.4b land surface model and evaluation against MODIS estimates over Australia

2014 ◽  
Vol 7 (5) ◽  
pp. 2121-2140 ◽  
Author(s):  
J. Kala ◽  
J. P. Evans ◽  
A. J. Pitman ◽  
C. B. Schaaf ◽  
M. Decker ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Surface Albedo ◽  
Near Infrared ◽  
Land Surface Model ◽  
Surface Model ◽  
Transfer Scheme ◽  
Control Simulation ◽  
Common Land Model ◽  
Australian Continent

Abstract. Land surface albedo, the fraction of incoming solar radiation reflected by the land surface, is a key component of the Earth system. This study evaluates snow-free surface albedo simulations by the Community Atmosphere Biosphere Land Exchange (CABLEv1.4b) model with the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Satellite Pour L'Observation de la Terre (SPOT) albedo. We compare results from offline simulations over the Australian continent. The control simulation has prescribed background snow-free and vegetation-free soil albedo derived from MODIS whilst the experiments use a simple parameterisation based on soil moisture and colour, originally from the Biosphere Atmosphere Transfer Scheme (BATS), and adopted in the Common Land Model (CLM). The control simulation, with prescribed soil albedo, shows that CABLE simulates overall albedo over Australia reasonably well, with differences compared to MODIS and SPOT albedos within ±0.1. Application of the original BATS scheme, which uses an eight-class soil classification, resulted in large differences of up to −0.25 for the near-infrared (NIR) albedo over large parts of the desert regions of central Australia. The use of a recalibrated 20-class soil colour classification from the CLM, which includes a higher range for saturated and VIS (visible) and NIR soil albedos, reduced the underestimation of the NIR albedo. However, this soil colour mapping is tuned to CLM soil moisture, a quantity which is not necessarily transferrable between land surface models. We therefore recalibrated the soil color map using CABLE's climatological soil moisture, which further reduced the underestimation of the NIR albedo to within ±0.15 over most of the continent as compared to MODIS and SPOT albedos. Small areas of larger differences of up to −0.25 remained within the central arid parts of the continent during summer; however, the spatial extent of these large differences is substantially reduced as compared to the simulation using the default eight-class uncalibrated soil colour map. It is now possible to use CABLE coupled to atmospheric models to investigate soil-moisture–albedo feedbacks, an important enhancement of the model.

scholarly journals Translating aboveground cosmic-ray neutron intensity to high-frequency soil moisture profiles at sub-kilometer scale

2014 ◽  
Vol 18 (11) ◽  
pp. 4363-4379 ◽  
Author(s):  
R. Rosolem ◽  
T. Hoar ◽  
A. Arellano ◽  
J. L. Anderson ◽  
W. J. Shuttleworth ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
High Frequency ◽  
Mixed Forest ◽  
Land Surface Model ◽  
Cosmic Ray ◽  
Data Availability ◽  
Surface Model ◽  
Moisture Profiles ◽  
Semi Arid

Abstract. Above-ground cosmic-ray neutron measurements provide an opportunity to infer soil moisture at the sub-kilometer scale. Initial efforts to assimilate those measurements have shown promise. This study expands such analysis by investigating (1) how the information from aboveground cosmic-ray neutrons can constrain the soil moisture at distinct depths simulated by a land surface model, and (2) how changes in data availability (in terms of retrieval frequency) impact the dynamics of simulated soil moisture profiles. We employ ensemble data assimilation techniques in a "nearly-identical twin" experiment applied at semi-arid shrubland, rainfed agricultural field, and mixed forest biomes in the USA. The performance of the Noah land surface model is compared with and without assimilation of observations at hourly intervals, as well as every 2 days. Synthetic observations of aboveground cosmic-ray neutrons better constrain the soil moisture simulated by Noah in root-zone soil layers (0–100cm), despite the limited measurement depth of the sensor (estimated to be 12–20cm). The ability of Noah to reproduce a "true" soil moisture profile is remarkably good, regardless of the frequency of observations at the semi-arid site. However, soil moisture profiles are better constrained when assimilating synthetic cosmic-ray neutron observations hourly rather than every 2 days at the cropland and mixed forest sites. This indicates potential benefits for hydrometeorological modeling when soil moisture measurements are available at a relatively high frequency. Moreover, differences in summertime meteorological forcing between the semi-arid site and the other two sites may indicate a possible controlling factor to soil moisture dynamics in addition to differences in soil and vegetation properties.

scholarly journals Assimilation of near-surface cosmic-ray neutrons improves summertime soil moisture profile estimates at three distinct biomes in the USA

2014 ◽  
Vol 11 (5) ◽  
pp. 5515-5558 ◽  
Author(s):  
R. Rosolem ◽  
T. Hoar ◽  
A. Arellano ◽  
J. L. Anderson ◽  
W. J. Shuttleworth ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Mixed Forest ◽  
Land Surface Model ◽  
Cosmic Ray ◽  
Surface Model ◽  
Moisture Profile ◽  
The Usa ◽  
Moisture Profiles ◽  
Semi Arid

Abstract. Aboveground cosmic-ray neutron measurements provide an opportunity to infer soil moisture at the sub-kilometer scale. Initial efforts to assimilate those measurements have shown promise. This study expands such analysis by investigating (1) how the information from aboveground cosmic-ray neutrons can constrain the soil moisture at distinct depths simulated by a land surface model, and (2) how changes in data availability (in terms of retrieval frequency) impact the dynamics of simulated soil moisture profiles. We employ ensemble data assimilation techniques in a "nearly-identical twin" experiment applied at semi-arid shrubland, rainfed agricultural field, and mixed forest biomes in the USA The performance of the Noah land surface model is compared without and with assimilation of observations at hourly intervals and every 2 days Synthetic observations of aboveground cosmic-ray neutrons better constrain the soil moisture simulated by Noah in root zone soil layers (0–100 cm) despite the limited measurement depth of the sensor (estimated to be 12–20 cm). The ability of Noah to reproduce a "true" soil moisture profile is remarkably good regardless of the frequency of observations at the semi-arid site. However, soil moisture profiles are better constrained when assimilating synthetic cosmic-ray neutrons observations hourly rather than every 2 days at the cropland and mixed forest sites. This indicates potential benefits for hydrometeorological modeling when soil moisture measurements are available at relatively high frequency. Moreover, differences in summertime meteorological forcing between the semi-arid site and the other two sites may indicate a possible controlling factor to soil moisture dynamics in addition to differences in soil and vegetation properties.

Evaluation of Reanalysis Soil Moisture Simulations Using Updated Chinese Soil Moisture Observations

2005 ◽  
Vol 6 (2) ◽  
pp. 180-193 ◽  
Author(s):  
Haibin Li ◽  
Alan Robock ◽  
Suxia Liu ◽  
Xingguo Mo ◽  
Pedro Viterbo
Keyword(s):  
Soil Moisture ◽  
Interannual Variability ◽  
Land Surface ◽  
Soil Layer ◽  
Land Surface Model ◽  
Cold Season ◽  
Temporal Scale ◽  
Department Of Energy ◽  
Surface Model ◽  
Deep Soil

Abstract Using 19 yr of Chinese soil moisture data from 1981 to 1999, the authors evaluate soil moisture in three reanalysis outputs: the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40); the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis 1 (R-1); and the NCEP–Department of Energy (DOE) reanalysis 2 (R-2) over China. R-2 shows improved interannual variability and better seasonal patterns of soil moisture than R-1 as the result of the incorporation of observed precipitation, but not for all stations. ERA-40 produces a better mean value of soil moisture for most Chinese stations and good interannual variability. Limited observations in the spring indicate a spring soil moisture peak for most of the stations. ERA-40 generally reproduced this event, while R-1 or R-2 generally did not capture this feature, either because the soil was already saturated or the deep soil layer was too thick and damped such a response. ERA-40 and R-1 have a temporal time scale comparable to observations, but R-2 has a memory of nearly 5 months for the growing season, about twice the temporal scale of the observations. The cold season tends to prolong soil moisture memory by about 3 months for R-2 and 1 month for ERA-40. The unrealistic long temporal scale of R-2 can be attributed to the deep layer of the land surface model, which is too thick and dominates the soil moisture variability. R-1 has the same land surface scheme as R-2, but shows a temporal scale close to observations, which is actually because of soil moisture nudging to a fixed climatology. This new long time series of observed soil moisture will prove valuable for other studies of climate change, remote sensing, and model evaluation.

scholarly journals CAS-LSM Datasets for the CMIP6 Land Surface Snow and Soil Moisture Model Intercomparison Project

2021 ◽  
Author(s):  
Binghao Jia ◽  
Longhuan Wang ◽  
Yan Wang ◽  
Ruichao Li ◽  
Xin Luo ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Grid Point ◽  
Global Ocean ◽  
Surface Model ◽  
Past Century ◽  
Model Intercomparison ◽  
Soil Moisture Model ◽  
Surface Snow ◽  
Intercomparison Project

AbstractThe datasets of the five Land-offline Model Intercomparison Project (LMIP) experiments using the Chinese Academy of Sciences Land Surface Model (CAS-LSM) of CAS Flexible Global-Ocean-Atmosphere-Land System Model Grid-point version 3 (CAS FGOALS-g3) are presented in this study. These experiments were forced by five global meteorological forcing datasets, which contributed to the framework of the Land Surface Snow and Soil Moisture Model Intercomparison Project (LS3MIP) of CMIP6. These datasets have been released on the Earth System Grid Federation node. In this paper, the basic descriptions of the CAS-LSM and the five LMIP experiments are shown. The performance of the soil moisture, snow, and land-atmosphere energy fluxes was preliminarily validated using satellite-based observations. Results show that their mean states, spatial patterns, and seasonal variations can be reproduced well by the five LMIP simulations. It suggests that these datasets can be used to investigate the evolutionary mechanisms of the global water and energy cycles during the past century.

scholarly journals Influence of Land Cover and Soil Moisture on the Horizontal Distribution of Sensible and Latent Heat Fluxes in Southeast Kansas during IHOP_2002 and CASES-97

2007 ◽  
Vol 8 (1) ◽  
pp. 68-87 ◽  
Author(s):  
Margaret A. LeMone ◽  
Fei Chen ◽  
Joseph G. Alfieri ◽  
Mukul Tewari ◽  
Bart Geerts ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Latent Heat ◽  
Land Surface ◽  
Field Experiments ◽  
Time Of Day ◽  
Horizontal Distribution ◽  
Heat Fluxes ◽  
Surface Model ◽  
Green Vegetation ◽  
The Impact

Abstract Analyses of daytime fair-weather aircraft and surface-flux tower data from the May–June 2002 International H2O Project (IHOP_2002) and the April–May 1997 Cooperative Atmosphere Surface Exchange Study (CASES-97) are used to document the role of vegetation, soil moisture, and terrain in determining the horizontal variability of latent heat LE and sensible heat H along a 46-km flight track in southeast Kansas. Combining the two field experiments clearly reveals the strong influence of vegetation cover, with H maxima over sparse/dormant vegetation, and H minima over green vegetation; and, to a lesser extent, LE maxima over green vegetation, and LE minima over sparse/dormant vegetation. If the small number of cases is producing the correct trend, other effects of vegetation and the impact of soil moisture emerge through examining the slope ΔxyLE/ΔxyH for the best-fit straight line for plots of time-averaged LE as a function of time-averaged H over the area. Based on the surface energy balance, H + LE = Rnet − Gsfc, where Rnet is the net radiation and Gsfc is the flux into the soil; Rnet − Gsfc ∼ constant over the area implies an approximately −1 slope. Right after rainfall, H and LE vary too little horizontally to define a slope. After sufficient drying to produce enough horizontal variation to define a slope, a steep (∼−2) slope emerges. The slope becomes shallower and better defined with time as H and LE horizontal variability increases. Similarly, the slope becomes more negative with moister soils. In addition, the slope can change with time of day due to phase differences in H and LE. These trends are based on land surface model (LSM) runs and observations collected under nearly clear skies; the vegetation is unstressed for the days examined. LSM runs suggest terrain may also play a role, but observational support is weak.

scholarly journals Exploring the Sensitivity of Photosynthesis and Stomatal Resistance Parameters in a Land Surface Model

2017 ◽  
Vol 18 (3) ◽  
pp. 897-915 ◽  
Author(s):  
Jennifer L. Jefferson ◽  
Reed M. Maxwell ◽  
Paul G. Constantine
Keyword(s):  
Land Surface ◽  
Stomatal Resistance ◽  
Hydrologic Model ◽  
Surface Model ◽  
Land Surface Models ◽  
Common Land Model ◽  
Surface Models ◽  
Input Parameters ◽  
Rate Of Photosynthesis ◽  
Quantities Of Interest

Abstract Land surface models, like the Common Land Model component of the ParFlow integrated hydrologic model (PF-CLM), are used to estimate transpiration from vegetated surfaces. Transpiration rates quantify how much water moves from the subsurface through the plant and into the atmosphere. This rate is controlled by the stomatal resistance term in land surface models. The Ball–Berry stomatal resistance parameterization relies, in part, on the rate of photosynthesis, and together these equations require the specification of 20 input parameters. Here, the active subspace method is applied to 2100 year-long PF-CLM simulations, forced by atmospheric data from California, Colorado, and Oklahoma, to identify which input parameters are important and how they relate to three quantities of interest: transpiration, stomatal resistance from the sunlit portion of the canopy, and stomatal resistance from the shaded portion. The slope (mp) and intercept (bp) parameters associated with the Ball–Berry parameterization are consistently important for all locations, along with five parameters associated with ribulose bisphosphate carboxylase/oxygenase (RuBisCO)- and light-limited rates of photosynthesis [CO2 Michaelis–Menten constant at 25°C (kc25), maximum ratio of oxygenation to carboxylation (ocr), quantum efficiency at 25°C (qe25), maximum rate of carboxylation at 25°C (vcmx25), and multiplier in the denominator of the equation used to compute the light-limited rate of photosynthesis (wj1)]. The importance of these input parameters, quantified by the active variable weight, and the relationship between the input parameters and quantities of interest vary seasonally and diurnally. Input parameter values influence transpiration rates most during midday, summertime hours when fluxes are large. This research informs model users about which photosynthesis and stomatal resistance parameters should be more carefully selected. Quantifying sensitivities associated with the stomatal resistance term is necessary to better understand transpiration estimates from land surface models.

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