scholarly journals Improvement of modelling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements

2020 ◽  
Author(s):  
Anna B. Harper ◽  
Karina E. Williams ◽  
Patrick C. McGuire ◽  
Maria Carolina Duran Rojas ◽  
Debbie Hemming ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Deciduous Forest ◽  
Soil Depth ◽  
Regional Climate ◽  
Moisture Stress ◽  
Plant Responses ◽  
Soil Moisture Stress ◽  
Forest Sites ◽  
The Impact

Abstract. Drought is predicted to increase in the future due to climate change, bringing with it a myriad of impacts on ecosystems. Plants respond to drier soils by reducing stomatal conductance, in order to conserve water and avoid hydraulic damage. Despite the importance of plant drought responses for the global carbon cycle and local/regional climate feedbacks, land surface models are unable to capture observed plant responses to soil moisture stress. We assessed the impact of soil moisture stress on simulated gross primary productivity (GPP) and latent energy flux (LE) in the Joint UK Land Environment Simulator (JULES) vn4.9 on seasonal and annual timescales, and evaluated ten different representations of stress in the model. For the default configuration, GPP was more realistic in temperate biome sites than in the tropics or high latitudes/cold region sites, while LE was best simulated in temperate and high latitude/cold sites. Errors not due to soil moisture stress, possibly linked to phenology, contributed to model biases for GPP in tropical savannah and deciduous forest sites. We found that three alternative approaches to calculating soil moisture stress produced more realistic results than the default parameterization for most biomes and climates. All of these involved increasing the number of soil layers from 4 to 14, and the soil depth from 3m to 10.8m. In addition, we found improvements when soil matric potential replaced volumetric water content in the stress equation, when the onset of stress was delayed, and when roots extended deeper into the soil. For LE, the biases were highest in the default configuration in temperate mixed forests, with overestimation occurring during most of the year. At these sites, reducing soil moisture stress (with the new parameterizations mentioned above) increased LE and made the simulation worse. Further evaluation into the reason for the high bias in LE at many of the sites would enable improvements in both carbon and energy fluxes with new parameterizations for soil moisture stress.

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 Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements

2021 ◽  
Vol 14 (6) ◽  
pp. 3269-3294
Author(s):  
Anna B. Harper ◽  
Karina E. Williams ◽  
Patrick C. McGuire ◽  
Maria Carolina Duran Rojas ◽  
Debbie Hemming ◽  
...  
Keyword(s):  
Soil Moisture ◽  
High Latitude ◽  
Land Surface ◽  
Soil Depth ◽  
Moisture Stress ◽  
Plant Responses ◽  
Soil Matric Potential ◽  
Matric Potential ◽  
Soil Moisture Stress ◽  
Soil Layers

Abstract. Drought is predicted to increase in the future due to climate change, bringing with it myriad impacts on ecosystems. Plants respond to drier soils by reducing stomatal conductance in order to conserve water and avoid hydraulic damage. Despite the importance of plant drought responses for the global carbon cycle and local and regional climate feedbacks, land surface models are unable to capture observed plant responses to soil moisture stress. We assessed the impact of soil moisture stress on simulated gross primary productivity (GPP) and latent energy flux (LE) in the Joint UK Land Environment Simulator (JULES) vn4.9 on seasonal and annual timescales and evaluated 10 different representations of soil moisture stress in the model. For the default configuration, GPP was more realistic in temperate biome sites than in the tropics or high-latitude (cold-region) sites, while LE was best simulated in temperate and high-latitude (cold) sites. Errors that were not due to soil moisture stress, possibly linked to phenology, contributed to model biases for GPP in tropical savanna and deciduous forest sites. We found that three alternative approaches to calculating soil moisture stress produced more realistic results than the default parameterization for most biomes and climates. All of these involved increasing the number of soil layers from 4 to 14 and the soil depth from 3.0 to 10.8 m. In addition, we found improvements when soil matric potential replaced volumetric water content in the stress equation (the “soil14_psi” experiments), when the critical threshold value for inducing soil moisture stress was reduced (“soil14_p0”), and when plants were able to access soil moisture in deeper soil layers (“soil14_dr*2”). For LE, the biases were highest in the default configuration in temperate mixed forests, with overestimation occurring during most of the year. At these sites, reducing soil moisture stress (with the new parameterizations mentioned above) increased LE and increased model biases but improved the simulated seasonal cycle and brought the monthly variance closer to the measured variance of LE. Further evaluation of the reason for the high bias in LE at many of the sites would enable improvements in both carbon and energy fluxes with new parameterizations for soil moisture stress. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES or as a general way to improve land surface carbon and water fluxes in other models. In addition, using soil matric potential presents the opportunity to include plant functional type-specific parameters to further improve modeled fluxes.

Evaluating the Simulated Seasonality of Soil Moisture with Earth Observation Data

2009 ◽  
Vol 10 (6) ◽  
pp. 1548-1560 ◽  
Author(s):  
Richard J. Ellis ◽  
Christopher M. Taylor ◽  
Graham P. Weedon ◽  
Nicola Gedney ◽  
Douglas B. Clark ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Leaf Area Index ◽  
Land Surface ◽  
Hydraulic Properties ◽  
Moisture Stress ◽  
Earth Observation ◽  
Soil Hydraulic Properties ◽  
Soil Moisture Stress ◽  
Area Index ◽  
Surface Scheme

Abstract A critical function of a land surface scheme, used in climate and weather prediction models, is to partition the energy from insolation into sensible and latent heat fluxes. Many use a soil moisture function to control the surface moisture fluxes through the transpiration. The validity and global distribution of the parameters used to calculate this soil moisture stress function are difficult to assess. This work presents a method to map soil moisture stress globally from an earth observation vegetation index and precipitation data, and it compares the resulting distributions with output from the Joint U.K. Land Environment Simulator (JULES) land surface scheme. A number of model runs with different soil and vegetation parameters are compared. These examine the sensitivity of the seasonality of soil moisture stress, within the model, to the parameterization of soil hydraulic properties and the seasonality of leaf area index in the vegetation. It is found that the seasonality of soil moisture within the model is more sensitive to the soil hydraulic properties than the leaf area index. The partitioning of throughfall into evaporation and runoff, in the model, is the dominant factor in determining the timing of soil moisture stress.

Extension of the regional climate model REMO by a 5-layer soil scheme

2020 ◽  
Author(s):  
Daniel Abel ◽  
Felix Pollinger ◽  
Katrin Ziegler ◽  
Heiko Paeth
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Soil Depth ◽  
Regional Climate ◽  
Capillary Rise ◽  
Rooting Depth ◽  
Climate Projections ◽  
Observation Data ◽  
Soil Hydrology ◽  
Spatiotemporal Resolution

<p>The EFRE-Project BigData@Geo, founded by the European Union, aims to create highly resolved climate projections for the model region of Lower Franconia in Bavaria, Germany. These projections are analyzed and made available to local stakeholders of agriculture, forestry, and viniculture as well as the public. As recent regional climate models are not dealing with the necessary spatiotemporal resolution the model REMO will be developed in the project‘s frame in cooperation with the Climate Service Center Germany (GERICS).</p><p>For these very high resolutions, besides improvements like the non-hydrostatic atmosphere, higher resolved static land surface parameters, and land use land cover changes, etc., realistic modeling of the soil hydrology becomes absolutely necessary. Therefore, REMO is extended by a 5-layer soil scheme which is a first step to overcome restrictions of the recently used soil hydrology scheme due to the included vertical water flow. Furthermore, the current work also aims to implement lateral water flows between grid cells because this is the only way to model the soil hydrology appropriate to the project‘s question.</p><p>The current model version of REMO includes a bucket scheme that treats the soil hydrology as a single layer. The soil depth is equal to the rooting depth and, thus, depends on the overlying vegetation class. Consequently, the whole soil moisture of the soil is available for transpiration. Evaporation only occurs if the soil moisture reaches at least 90 % of the field capacity.</p><p>The 5-layer scheme has 5 layers with increasing thicknesses for deeper layers. The maximum depth of the soil is at approximately 10 m or the depth of the bedrock. Due to the existence of water below the rooting zone and the processes of capillary rise and percolation more water becomes available for transpiration compared to the bucket scheme. Furthermore, evaporation only occurs if the uppermost layer contains soil moisture which is a more realistic process representation as well.</p><p>First results of the comparison of the two schemes and with observation data in the EURO-CORDEX region and a german subregion are presented. We also show some sensitivity studies of the current improvements to the parameterizations of the 5-layer scheme which are necessary for the goal of incorporation of the lateral flow.</p>

scholarly journals The impact of snow loss and soil moisture on convective precipitation over the Rocky Mountains under climate warming

2021 ◽  
Author(s):  
Brendan Wallace ◽  
Justin R. Minder
Keyword(s):  
Soil Moisture ◽  
Snow Cover ◽  
Rocky Mountains ◽  
Land Surface ◽  
Regional Climate ◽  
Warm Season ◽  
Surface Fluxes ◽  
Convective Precipitation ◽  
Precipitation Frequency ◽  
The Impact

AbstractWarm season moist diurnal convection can be particularly sensitive to changes in land surface characteristics such as snow cover and soil moisture. Over regions of mountainous terrain, climate change is expected to reduce snow cover along the low-elevation seasonal snowpack margin. These snow reductions alter surface albedo and soil moisture content, leading to changes in surface fluxes and alterations in mesoscale orographic circulations that act to transport moisture and provide ascent. A set of convection-permitting regional climate simulations centered on the Rocky Mountains of Colorado are conducted from April through July across a period of 12 years (2002–2013). These include a reanalysis forced control run (CTR), a pseudo global warming run (PGW), and an additional altered land surface run (DSURF) used to isolate the effects of the snow albedo and soil moisture changes on orographic convection. Over the mountains, daytime hourly precipitation accumulation (0900–1800 MST) decreased in PGW by an average of 4.2% while precipitation in DSURF increased by 12.5%. On days with weak synoptic forcing, the PGW response more closely follow the DSURF response with daytime hourly increases averaging 29.7% for PGW and 28.7% for DSURF. For PGW, hourly daytime precipitation intensity increases of up to 82% overcome reductions in precipitation frequency to produce higher accumulations. DSURF shows smaller increases in intensity of up to 23% and broad increases in daytime frequency indicating that surface changes act to moderate reductions in the frequency of convective precipitation. Reduced snow cover contributes to this convective response by increasing convective instability and boundary layer moisture and decreasing lifting condensation level over the high terrain. Alterations in orographic thermal circulations contribute to this response by converging moisture over the high terrain and enhancing mesoscale ascent.

scholarly journals Evaluation of Flux-PIHM, a physically-based land surface hydrologic model in an agricultural watershed

2021 ◽  
Author(s):  
Yuting Smeglin ◽  
Yuning Shi ◽  
Jason Kaye ◽  
Caitlin Hodges ◽  
Qicheng Tang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Deciduous Forest ◽  
Soil Column ◽  
Hydrologic Model ◽  
Agricultural Watershed ◽  
Sensible Heat ◽  
Spatially Distributed ◽  
The Impact ◽  
Shale Hills

An agricultural watershed, Cole Farm, was established as the newest of the three subcatchments in the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO) in 2017. The catchment contains mostly pasture and crops, with a small portion of deciduous forest. The observations in Cole Farm afford an opportunity to test the spatially distributed land surface hydrologic model, Flux-PIHM, in farmland for the first time. In this study, we calibrated the model to only discharge and groundwater level observations at Cole Farm, but it’s able to capture the variations and magnitudes of soil moisture, latent heat (LE) and sensible heat (H) fluxes. Modeled soil moisture on the ridge top matched the observations well, but modeled soil moisture in the mid-slope differed from observations likely due to the existence of fragipan in the soil column. Flux-PIHM reproduced the seasonality and diurnal variations of watershed-average evapotranspiration (ET), sensible heat flux (H), though modeled ET in summer is about 25% greater than tower ET. To study the impact of land cover on hydrology, we imposed two different LAI forcings to the model: spatially distributed versus uniform LAI. Spatially distributed LAI produced higher ET and lower soil moisture in the forested part of the watershed due to higher LAI of deciduous forest in comparison to crops and pasture. But the impact of different LAI forcings on discharge was small. We further compared the water budget simulated by Flux-PIHM in the agricultural watershed (Cole Farm) to a forested watershed (Shale Hills). Flux-PIHM simulated less discharge and higher transpiration and bare soil evaporation in the Cole Farm watershed relative to Shale Hills watershed. Our work shows that with a few key observations, Flux-PIHM can be calibrated to simulate agricultural watershed hydrology, but spatially distributed LAI and soils data are needed to capture the spatial variations in soil moisture and ET.

scholarly journals ISBA-MEB (SURFEX v8.1): model snow evaluation for local-scale forest sites

2020 ◽  
Vol 13 (12) ◽  
pp. 6523-6545
Author(s):  
Adrien Napoly ◽  
Aaron Boone ◽  
Théo Welfringer
Keyword(s):  
Land Surface ◽  
Positive Impact ◽  
Soil Depth ◽  
Large Degree ◽  
Heat Fluxes ◽  
Close Coupling ◽  
Forest Sites ◽  
Ground Heat Flux ◽  
Soil Temperatures ◽  
The Impact

Abstract. Accurate modeling of the effect of snow cover on the surface energy and mass fluxes is required from land surface models. The Interactions between Soil–Biosphere–Atmosphere (ISBA) model uses a composite soil–vegetation approach that has limitations when representing snow and soil phase change processes in areas of high vegetation cover since it does not explicitly represent the snowpack lying on the ground below the canopy. In particular, previous studies using ISBA have pointed out that the snowpack ablation tends to occur to early in the season in forest regions in the Northern Hemisphere. The multi-energy balance (MEB) version of ISBA has been developed recently, to a large degree, to address this issue. A vegetation layer, which is distinct from the soil, has been added to ISBA and new processes are now explicitly represented, such as snow interception and an understory litter layer. To evaluate the behavior of this new scheme in a cold forested region, long-term offline simulations have been performed for the three BERMS forest sites located in Saskatchewan, Canada. It is shown that the new scheme leads to an improved energy budget representation, especially in terms of the ground and sensible heat fluxes, with decreases in root-mean-square error (RMSE) of 77 % and 18 %, respectively. A positive impact for soil temperatures, consistent with the improvement of the ground heat flux, is obtained, particularly in terms of bias, which is reduced from −6.2 to −0.1 K at a 10 cm soil depth on average for the three sites and 12 studied years. The impact of using MEB on the snowpack simulation is a better agreement with observations during the snow season, especially concerning the last day of snow in the season: errors are on the order of 1 d averaged over the three sites and all of the years using MEB, which represents a reduction in error of 20 d compared to the composite scheme. The analysis shows that this improvement is mostly caused by the ability of MEB to represent a snowpack that nearly completely covers the soil below the canopy and that decouples the soil from the atmosphere, while keeping a close coupling between the vegetation and the atmosphere.

scholarly journals ISBA-MEB (SURFEX v8.1): model snow evaluation for local-scale forest sites

2020 ◽  
Author(s):  
Adrien Napoly ◽  
Aaron Boone ◽  
Théo Welfringer
Keyword(s):  
Energy Budget ◽  
Land Surface ◽  
Positive Impact ◽  
Soil Depth ◽  
Large Degree ◽  
Heat Fluxes ◽  
Close Coupling ◽  
Forest Sites ◽  
Soil Temperatures ◽  
The Impact

Abstract. An accurate modelling of the effect of snow cover on the surface energy and mass fluxes is required from land surface models. The Interactions between Soil–Biosphere–Atmosphere (ISBA) model adopts a default configuration using a composite soil-vegetation energy budget approach which is shown to have certain limitations for representing snow and soil phase change processes in areas of high vegetation cover since it does not explicitly represent the snow pack lying on the ground below the canopy. In particular, previous studies using ISBA have pointed out that the snowpack ablation tends to occur to early in the season in forest regions in the northern hemisphere. The multi-energy balance (MEB) version of ISBA has been developed recently, to a large degree, to address this issue. A vegetation layer, which is distinct from the soil, has been added to ISBA and new processes are now explicitly represented such as snow interception and an under-story litter layer. To evaluate the behavior of this new scheme in a cold forested region, long-term offline simulations have been performed for the three Berms forest sites located in Saskatchewan, Canada. It is shown that the new scheme leads to an improved energy budget representation, especially in terms of the ground and sensible heat fluxes, with decreases in RMSE of 77 and 18 %, respectively. A consistent positive impact for soil temperatures is obtained, particularly in terms of bias which is reduced from −6.2 to −0.1 K at a 10 cm soil depth on average for the three sites and 12 studied years. The impact of using MEB on the snowpack simulation is in a better agreement with observations during the snow season, especially in terms of the time of ablation: errors are on the order of 1 day averaged over the 3 sites and all of the years using MEB, which represents a reduction in error of 20 days compared to the composite scheme. The analysis shows that this improvement is mostly cause by the ability of MEB to represent a snowpack that nearly completely covers the soil below the canopy decouples the soil from the atmosphere while keeping a close coupling between the vegetation and the atmosphere.

scholarly journals The Continental-Scale Soil-Moisture Precipitation Feedback in Europe with Parameterized and Explicit Convection

2021 ◽  
pp. 1-56
Author(s):  
David Leutwyler ◽  
Adel Imamovic ◽  
Christoph Schär
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Summer Precipitation ◽  
Positive Sign ◽  
Precipitation Frequency ◽  
Continental Scale ◽  
The Impact ◽  
Precipitation Events

AbstractSoil moisture atmosphere interactions are key elements of the regional climate system. There is a well-founded hope that a more accurate representation of the soil moisture-precipitation feedback would improve the simulation of summer precipitation on daily to seasonal, to climate time scales. However, uncertainties have persistently remained as the simulated feedback is strongly sensitive to the model representation of deep convection. Here we assess the feedback representation using a GPU-accelerated version of the regional climate model COSMO. We simulate and compare the impact of continental-scale springtime soil-moisture anomalies on summer precipitation at convection-resolving (2.2 km) and convection-parameterizing resolution (12 km). We conduct re-analysis-driven simulations of 10 summer seasons (1999-2008) in continental Europe. While both simulations qualitatively agree on a positive sign of soil moisture-induced precipitation, they strongly differ in precipitation frequency: When convection is parameterized, wetter soil predominantly leads to more frequent precipitation events, and when convection is treated explicitly, they primarily become more intense. The results indicate that the sensitivity to soil moisture is stronger with parameterized convection, suggesting that the land surface-atmosphere coupling may be overestimated. In addition, the feedback’s sensitivity in complex terrain is assessed for soil perturbations of different horizontal scales. The convection-resolving simulations confirm a negative feedback for sub-continental soil moisture anomalies, which manifests itself in a local decrease of wet-hour frequency. However, the intensity feedback reinforces precipitation events at the same time (positive feedback). The two processes are represented differently in simulations with explicit and parameterized convection, explaining much of the difference between the two simulations.

scholarly journals Global isoprene emissions estimated using MEGAN, ECMWF analyses and a detailed canopy environment model

2007 ◽  
Vol 7 (6) ◽  
pp. 15373-15407 ◽  
Author(s):  
J.-F. Müller ◽  
T. Stavrakou ◽  
S. Wallens ◽  
I. De Smedt ◽  
M. Van Roozendael ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Transport Model ◽  
Flux Measurement ◽  
Moisture Stress ◽  
Wet Season ◽  
Visible Radiation ◽  
Soil Moisture Stress ◽  
Environment Model ◽  
The Impact ◽  
Global Emissions

Abstract. The global emissions of isoprene are calculated at 0.5° resolution for each year between 1995 and 2006, based on the MEGAN (Model of Emissions of Gases and Aerosols from Nature) version 2 model (Guenther et al., 2006) and a detailed multi-layer canopy environment model for the calculation of leaf temperature and visible radiation fluxes. The calculation is driven by meteorological fields – air temperature, cloud cover, downward solar irradiance, windspeed, volumetric soil moisture in 4 soil layers – provided by analyses of the European Centre for Medium-Range Weather Forecasts (ECMWF). The estimated annual global isoprene emission ranges between 374 Tg (in 1996) and 449 Tg (in 1998 and 2005), for an average of ca. 410 Tg/year over the whole period, i.e. about 30% less than the standard MEGAN estimate (Guenther et al., 2006). This difference is due, to a large extent, to the impact of the soil moisture stress factor, which is found here to decrease the global emissions by more than 20%. In qualitative agreement with past studies, high annual emissions are found to be generally associated with El Niño events. The emission inventory is evaluated against flux measurement campaigns at Harvard forest (Massachussets) and Tapajós in Amazonia, showing that the model can capture quite well the short-term variability of emissions, but that it fails to reproduce the observed seasonal variation at the tropical rainforest site, with largely overestimated wet season fluxes. The comparison of the HCHO vertical columns calculated by a chemistry and transport model (CTM) with HCHO distributions retrieved from space provides useful insights on tropical isoprene emissions. For example, the relatively low emissions calculated over Western Amazonia (compared to the corresponding estimates in the inventory of Guenther et al., 1995) are validated by the excellent agreement found between the CTM and HCHO data over this region. The parameterized impact of the soil moisture stress on isoprene emissions is found to reduce the model/data bias over Australia, but it leads to underestimated emissions near the end of the dry season over subtropical Africa.

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