scholarly journals Effects of bryophyte and lichen cover on permafrost soil temperature at large scale

2016 ◽  
Author(s):  
P. Porada ◽  
A. Ekici ◽  
C. Beer
Keyword(s):  
Thermal Properties ◽  
Soil Temperature ◽  
Land Surface ◽  
Dynamic Properties ◽  
Cooling Effect ◽  
Permafrost Soil ◽  
Surface Model ◽  
Study Region ◽  
Lichen Cover ◽  
Global Land

Abstract. Bryophyte and lichen cover on the forest floor at high latitudes exerts an insulating effect on the ground. In this way, the cover decreases mean annual soil temperature and can protect permafrost soil. Climate change, however, may change bryophyte and lichen cover, with effects on the permafrost state and related carbon balance. It is therefore crucial to predict how the bryophyte and lichen cover will react to environmental change at the global scale. To date, current global land surface models contain only empirical representations of the bryophyte and lichen cover, which makes it impractical to predict the future state and function of bryophytes and lichens. For this reason, we integrate a process-based model of bryophyte and lichen growth into the global land surface model JSBACH. We thereby take into account the dynamic nature of the thermal properties of the bryophyte and lichen cover and their relation to environmental factors. Subsequently, we compare simulations with and without bryophyte and lichen cover to quantify the insulating effect of the organisms on the soil. We find an average cooling effect of the bryophyte and lichen cover of 2.7 K on temperature in the topsoil for the study region under current climate. Locally, a cooling of up to 5.7 K may be reached. Moreover, we show that using a simple, empirical representation of the bryophyte and lichen cover without dynamic properties only results in an average cooling of around 0.5 K. This suggests that (a) bryophytes and lichens have a significant impact on soil temperature in high-latitude ecosystems and (b) a process-based description of their thermal properties is necessary for a realistic representation of the cooling effect. The advanced land surface scheme including a dynamic bryophyte and lichen model will be the basis for an improved future projection of land–atmosphere heat and carbon exchange.

scholarly journals Effects of bryophyte and lichen cover on permafrost soil temperature at large scale

2016 ◽  
Vol 10 (5) ◽  
pp. 2291-2315 ◽  
Author(s):  
Philipp Porada ◽  
Altug Ekici ◽  
Christian Beer
Keyword(s):  
Thermal Properties ◽  
Soil Temperature ◽  
Land Surface ◽  
Large Scale ◽  
Dynamic Properties ◽  
Cooling Effect ◽  
Permafrost Soil ◽  
Surface Model ◽  
Lichen Cover ◽  
Global Land

Abstract. Bryophyte and lichen cover on the forest floor at high latitudes exerts an insulating effect on the ground. In this way, the cover decreases mean annual soil temperature and can protect permafrost soil. Climate change, however, may change bryophyte and lichen cover, with effects on the permafrost state and related carbon balance. It is, therefore, crucial to predict how the bryophyte and lichen cover will react to environmental change at the global scale. To date, current global land surface models contain only empirical representations of the bryophyte and lichen cover, which makes it impractical to predict the future state and function of bryophytes and lichens. For this reason, we integrate a process-based model of bryophyte and lichen growth into the global land surface model JSBACH (Jena Scheme for Biosphere–Atmosphere Coupling in Hamburg). The model simulates bryophyte and lichen cover on upland sites. Wetlands are not included. We take into account the dynamic nature of the thermal properties of the bryophyte and lichen cover and their relation to environmental factors. Subsequently, we compare simulations with and without bryophyte and lichen cover to quantify the insulating effect of the organisms on the soil. We find an average cooling effect of the bryophyte and lichen cover of 2.7 K on temperature in the topsoil for the region north of 50° N under the current climate. Locally, a cooling of up to 5.7 K may be reached. Moreover, we show that using a simple, empirical representation of the bryophyte and lichen cover without dynamic properties only results in an average cooling of around 0.5 K. This suggests that (a) bryophytes and lichens have a significant impact on soil temperature in high-latitude ecosystems and (b) a process-based description of their thermal properties is necessary for a realistic representation of the cooling effect. The advanced land surface scheme, including a dynamic bryophyte and lichen model, will be the basis for an improved future projection of land–atmosphere heat and carbon exchange.

Developing a triple tree-ring constraint for tree growth and physiology in a global land surface model

2021 ◽  
Author(s):  
Jonathan Barichivich ◽  
Philippe Peylin ◽  
Valérie Daux ◽  
Camille Risi ◽  
Jina Jeong ◽  
...  
Keyword(s):  
Tree Ring ◽  
Land Surface ◽  
Forest Ecosystems ◽  
Ring Width ◽  
Land Surface Model ◽  
Surface Model ◽  
Growth Variability ◽  
Tree Ring Data ◽  
Surface Models ◽  
Global Land

<p>Gradual anthropogenic warming and parallel changes in the major global biogeochemical cycles are slowly pushing forest ecosystems into novel growing conditions, with uncertain consequences for ecosystem dynamics and climate. Short-term forest responses (i.e., years to a decade) to global change factors are relatively well understood and skilfully simulated by land surface models (LSMs). However, confidence on model projections weaken towards longer time scales and to the future, mainly because the long-term responses (i.e., decade to century) of these models remain unconstrained. This issue limits confidence on climate model projections. Annually-resolved tree-ring records, extending back to pre-industrial conditions, have the potential to constrain model responses at interannual to centennial time scales. Here, we constrain the representation of tree growth and physiology in the ORCHIDEE global land surface model using the simulated interannual variability of tree-ring width and carbon (Δ<sup>13</sup>C) and oxygen (δ<sup>18</sup>O) stable isotopes in six sites in boreal and temperate Europe.  The model simulates Δ<sup>13</sup>C (r = 0.31-0.80) and δ<sup>18</sup>O (r = 0.36-0.74) variability better than tree-ring width variability (r < 0.55), with an overall skill similar to that of other state-of-the-art models such as MAIDENiso and LPX-Bern. These results show that growth variability is not well represented, and that the parameterization of leaf-level physiological responses to drought stress in the temperate region can be improved with tree-ring data. The representation of carbon storage and remobilization dynamics is critical to improve the realism of simulated growth variability, temporal carrying over and recovery of forest ecosystems after climate extremes. The simulated physiological response to rising CO2 over the 20th century is consistent with tree-ring data in the temperate region, despite an overestimation of seasonal drought stress and stomatal control on photosynthesis. Photosynthesis correlates directly with isotopic variability, but correlations with δ<sup>18</sup>O combine physiological effects and climate variability impacts on source water signatures. The integration of tree-ring data (i.e. the triple constraint: width, Δ<sup>13</sup>C and δ<sup>18</sup>O) and land surface models as demonstrated here should contribute towards reducing current uncertainties in forest carbon and water cycling.</p>

scholarly journals Using Cosmic-Ray Neutron Probes in Validating Satellite Soil Moisture Products and Land Surface Models

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1362 ◽  
Author(s):  
Mustafa Berk Duygu ◽  
Zuhal Akyürek
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Land Surface Model ◽  
Cosmic Ray ◽  
Surface Model ◽  
High Temporal Resolution ◽  
Land Surface Models ◽  
Statistical Measures ◽  
Surface Models ◽  
Global Land

Soil moisture content is one of the most important parameters of hydrological studies. Cosmic-ray neutron sensing is a promising proximal soil moisture sensing technique at intermediate scale and high temporal resolution. In this study, we validate satellite soil moisture products for the period of March 2015 and December 2018 by using several existing Cosmic Ray Neutron Probe (CRNP) stations of the COSMOS database and a CRNP station that was installed in the south part of Turkey in October 2016. Soil moisture values, which were inferred from the CRNP station in Turkey, are also validated using a time domain reflectometer (TDR) installed at the same location and soil water content values obtained from a land surface model (Noah LSM) at various depths (0.1 m, 0.3 m, 0.6 m and 1.0 m). The CRNP has a very good correlation with TDR where both measurements show consistent changes in soil moisture due to storm events. Satellite soil moisture products obtained from the Soil Moisture and Ocean Salinity (SMOS), the METOP-A/B Advanced Scatterometer (ASCAT), Soil Moisture Active Passive (SMAP), Advanced Microwave Scanning Radiometer 2 (AMSR2), Climate Change Initiative (CCI) and a global land surface model Global Land Data Assimilation System (GLDAS) are compared with the soil moisture values obtained from CRNP stations. Coefficient of determination ( r 2 ) and unbiased root mean square error (ubRMSE) are used as the statistical measures. Triple Collocation (TC) was also performed by considering soil moisture values obtained from different soil moisture products and the CRNPs. The validation results are mainly influenced by the location of the sensor and the soil moisture retrieval algorithm of satellite products. The SMAP surface product produces the highest correlations and lowest errors especially in semi-arid areas whereas the ASCAT product provides better results in vegetated areas. Both global and local land surface models’ outputs are highly compatible with the CRNP soil moisture values.

scholarly journals Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

2017 ◽  
Author(s):  
Clément Albergel ◽  
Simon Munier ◽  
Delphine Jennifer Leroux ◽  
Hélène Dewaele ◽  
David Fairbairn ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Gross Primary Production ◽  
Mediterranean Area ◽  
Surface Model ◽  
Strong Impact ◽  
Control Variables ◽  
Area Index ◽  
Model Control ◽  
Global Land

Abstract. In this study, a global Land Data Assimilation system (LDAS-Monde) is tested over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. LDAS-Monde is able to ingest information from satellite-derived surface Soil Moisture (SM) and Leaf Area Index (LAI) observations to constrain the Interactions between Soil, Biosphere, and Atmosphere (ISBA) land surface model (LSM) coupled with the CNRM (Centre National de Recherches Météorologiques) version of the Total Runoff Integrating Pathways (ISBA-CTRIP) continental hydrological system. It makes use of the CO2-responsive version of ISBA which models leaf-scale physiological processes and plant growth. Transfer of water and heat in the soil rely on a multilayer diffusion scheme. Surface SM and LAI observations are assimilated using a simplified extended Kalman filter (SEKF), which uses finite differences from perturbed simulations to generate flow-dependence between the observations and the model control variables. The latter include LAI and seven layers of soil (from 1 cm to 100 cm depth). A sensitivity test of the Jacobians over 2000–2012 exhibits effects related to both depth and season. It also suggests that observations of both LAI and surface SM have an impact on the different control variables. From the assimilation of surface SM, the LDAS is more effective in modifying soil-moisture from the top layers of soil as model sensitivity to surface SM decreases with depth and has almost no impact from 60 cm downwards. From the assimilation of LAI, a strong impact on LAI itself is found. The LAI assimilation impact is more pronounced in SM layers that contain the highest fraction of roots (from 10 cm to 60 cm). The assimilation is more efficient in summer and autumn than in winter and spring. Assimilation impact shows that the LDAS works well constraining the model to the observations and that stronger corrections are applied to LAI than to SM. The assimilation impact's evaluation is successfully carried out using (i) agricultural statistics over France, (ii) river discharge observations, (iii) satellite-derived estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM) project and (iv) spatially gridded observations based estimates of up-scaled gross primary production and evapotranspiration from the FLUXNET network. Comparisons with those four datasets highlight neutral to highly positive improvement.

scholarly journals The Met Office Unified Model Global Atmosphere 4.0 and JULES Global Land 4.0 configurations

2014 ◽  
Vol 7 (1) ◽  
pp. 361-386 ◽  
Author(s):  
D. N. Walters ◽  
K. D. Williams ◽  
I. A. Boutle ◽  
A. C. Bushell ◽  
J. M. Edwards ◽  
...  
Keyword(s):  
Land Surface ◽  
Weather Prediction ◽  
Regional Climate ◽  
Land Surface Model ◽  
Unified Model ◽  
Surface Model ◽  
Development Cycle ◽  
Global Land ◽  
Overall Performance ◽  
Ongoing Development

Abstract. We describe Global Atmosphere 4.0 (GA4.0) and Global Land 4.0 (GL4.0): configurations of the Met Office Unified Model and JULES (Joint UK Land Environment Simulator) community land surface model developed for use in global and regional climate research and weather prediction activities. GA4.0 and GL4.0 are based on the previous GA3.0 and GL3.0 configurations, with the inclusion of developments made by the Met Office and its collaborators during its annual development cycle. This paper provides a comprehensive technical and scientific description of GA4.0 and GL4.0 as well as details of how these differ from their predecessors. We also present the results of some initial evaluations of their performance. Overall, performance is comparable with that of GA3.0/GL3.0; the updated configurations include improvements to the science of several parametrisation schemes, however, and will form a baseline for further ongoing development.

Adjoint retrieval of prognostic land surface model variables for an NWP model: Assimilation of ground surface temperature

2010 ◽  
Vol 2 (2) ◽  
Author(s):  
Diandong Ren
Keyword(s):  
Soil Moisture ◽  
Soil Temperature ◽  
Land Surface ◽  
Surface Soil ◽  
Land Surface Model ◽  
Initial Guess ◽  
Surface Model ◽  
Soil Moisture Condition ◽  
Wide Range ◽  
Surface Soil Temperature

AbstractBased on a 2-layer land surface model, a rather general variational data assimilation framework for estimating model state variables is developed. The method minimizes the error of surface soil temperature predictions subject to constraints imposed by the prediction model. Retrieval experiments for soil prognostic variables are performed and the results verified against model simulated data as well as real observations for the Oklahoma Atmospheric Surface layer Instrumentation System (OASIS). The optimization scheme is robust with respect to a wide range of initial guess errors in surface soil temperature (as large as 30 K) and deep soil moisture (within the range between wilting point and saturation). When assimilating OASIS data, the scheme can reduce the initial guess error by more than 90%, while for Observing Simulation System Experiments (OSSEs), the initial guess error is usually reduced by over four orders of magnitude.Using synthetic data, the robustness of the retrieval scheme as related to information content of the data and the physical meaning of the adjoint variables and their use in sensitivity studies are investigated. Through sensitivity analysis, it is confirmed that the vegetation coverage and growth condition determine whether or not the optimally estimated initial soil moisture condition leads to an optimal estimation of the surface fluxes. This reconciles two recent studies.With the real data experiments, it is shown that observations during the daytime period are the most effective for the retrieval. Longer assimilation windows result in more accurate initial condition retrieval, underlining the importance of information quantity, especially for schemes assimilating noisy observations.

Estimates of the Earth surface influence on the accuracy of numerical prediction of air temperature in Belarus using the WRF model

2021 ◽  
Vol 4 ◽  
pp. 50-68
Author(s):  
S.А. Lysenko ◽  
◽  
P.О. Zaiko ◽  
Keyword(s):  
Land Use ◽  
Air Temperature ◽  
Numerical Weather Prediction ◽  
Land Surface ◽  
Lead Time ◽  
Weather Prediction ◽  
Wrf Model ◽  
Surface Model ◽  
Numerical Weather ◽  
Global Land

The spatial structure of land use and biophysical characteristics of land surface (albedo, leaf index, and vegetation cover) are updated using the GLASS (Global Land Surface Satellite) and GLC2019 (Global Land Cover, 2019) modern satellite databases for mesoscale numerical weather prediction with the WRF model for the territory of Belarus. The series of WRF-based numerical experiments was performed to verify the influence of the updated characteristics on the forecast quality for some difficult to predict winter cases. The model was initialized by the GFS (Global Forecast System, NCEP) global numerical weather prediction model. It is shown that the use of high-resolution land use data in the WRF and the consideration of the new albedo and leaf index distribution over the territory of Belarus can reduce the root-mean-square error (RMSE) of short-range (to 48 hours) forecasts of surface air temperature by 16–33% as compared to the GFS. The RMSE of the temperature forecast for the weather stations in Belarus for a forecast lead time of 12, 24, 36, and 48 hours decreased on average by 0.40°С (19%), 0.35°С (10%), 0.68°С (23%), and 0.56°С (15%), respectively. The most significant decrease in RMSE of the numerical forecast of temperature (up to 2.1 °С) was obtained for the daytime (for a lead time of 12 and 36 hours), when positive feedbacks between albedo and temperature of the land surface are manifested most. Keywords: numerical weather prediction, WRF, digital land surface model, albedo, leaf area index, forecast model validation

scholarly journals How Does the Rate of Photovoltaic Installations and Coupled Batteries Affect Regional Energy Balancing and Self-Consumption of Residential Buildings?

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2738
Author(s):  
Andrea Reimuth ◽  
Veronika Locherer ◽  
Martin Danner ◽  
Wolfram Mauser
Keyword(s):  
Land Surface ◽  
Residential Buildings ◽  
Land Surface Model ◽  
Surface Model ◽  
Energy Balancing ◽  
Residential Energy ◽  
Study Region ◽  
Regional Energy ◽  
Pv Systems ◽  
Set Up

The strong expansion of residential rooftop photovoltaic (PV) and battery storage systems of recent years is expected to rise further. However, it is not yet clear to which degree buildings will be equipped with decentral energy producers. This study seeks to quantify the effects of different PV and battery installation rates on the residential residual loads and grid balancing flows. A land surface model with an integrated residential energy component is applied, which maintains spatial peculiarities and allows a building-specific set-up of PV systems, batteries, and consumption loads. The study area covers 3163 residential buildings located in a municipality in the south of Germany. The obtained results show minor impacts on the residual loads for a PV installation rate of less than 10%. PV installation rates of one third of all residential buildings of the study region lead to the highest spatial balancing via the grid. The rise in self-consumption when utilizing batteries leads to declined grid balancing between the buildings. For high PV installation rates, regional balancing diminishes, whereas energy excesses rise to 60%. They can be decreased up to 10% by the utilization of battery systems. Therefore, we recommend subsidy programs adjusted to the respective PV installation rates.

scholarly journals Multiple stable states of tree cover in a global land surface model due to a fire-vegetation feedback

2016 ◽  
Vol 43 (12) ◽  
pp. 6324-6331 ◽  
Author(s):  
G. Lasslop ◽  
V. Brovkin ◽  
C. H. Reick ◽  
S. Bathiany ◽  
S. Kloster
Keyword(s):  
Land Surface ◽  
Land Surface Model ◽  
Tree Cover ◽  
Surface Model ◽  
Stable States ◽  
Vegetation Feedback ◽  
Global Land ◽  
Multiple Stable States

scholarly journals Towards a Long-Term Reanalysis of Land Surface Variables over Western Africa: LDAS-Monde Applied over Burkina Faso from 2001 to 2018

2019 ◽  
Vol 11 (6) ◽  
pp. 735 ◽  
Author(s):  
Moustapha Tall ◽  
Clément Albergel ◽  
Bertrand Bonan ◽  
Yongjun Zheng ◽  
Françoise Guichard ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Burkina Faso ◽  
Land Surface ◽  
Gross Primary Production ◽  
Added Value ◽  
Surface Model ◽  
Strong Impact ◽  
Area Index ◽  
Soil Layers ◽  
Global Land

This study focuses on the ability of the global Land Data Assimilation System, LDAS-Monde, to improve the representation of land surface variables (LSVs) over Burkina-Faso through the joint assimilation of satellite derived surface soil moisture (SSM) and leaf area index (LAI) from January 2001 to June 2018. The LDAS-Monde offline system is forced by the latest European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis ERA5 as well as ERA-Interim former reanalysis, leading to reanalyses of LSVs at 0.25° × 0.25° and 0.50° × 0.50° spatial resolution, respectively. Within LDAS-Monde, SSM and LAI observations from the Copernicus Global Land Service (CGLS) are assimilated with a simplified extended Kalman filter (SEKF) using the CO2-responsive version of the ISBA (Interactions between Soil, Biosphere, and Atmosphere) land surface model (LSM). First, it is shown that ERA5 better represents precipitation and incoming solar radiation than ERA-Interim former reanalysis from ECMWF based on in situ data. Results of four experiments are then compared: Open-loop simulation (i.e., no assimilation) and analysis (i.e., joint assimilation of SSM and LAI) forced by either ERA5 or ERA-Interim. After jointly assimilating SSM and LAI, it is noticed that the assimilation is able to impact soil moisture in the first top soil layers (the first 20 cm), and also in deeper soil layers (from 20 cm to 60 cm and below), as reflected by the structure of the SEKF Jacobians. The added value of using ERA5 reanalysis over ERA-Interim when used in LDAS-Monde is highlighted. The assimilation is able to improve the simulation of both SSM and LAI: The analyses add skill to both configurations, indicating the healthy behavior of LDAS-Monde. For LAI in particular, the southern region of the domain (dominated by a Sudan-Guinean climate) highlights a strong impact of the assimilation compared to the other two sub-regions of Burkina-Faso (dominated by Sahelian and Sudan-Sahelian climates). In the southern part of the domain, differences between the model and the observations are the largest, prior to any assimilation. These differences are linked to the model failing to represent the behavior of some specific vegetation species, which are known to put on leaves before the first rains of the season. The LDAS-Monde analysis is very efficient at compensating for this model weakness. Evapotranspiration estimates from the Global Land Evaporation Amsterdam Model (GLEAM) project as well as upscaled carbon uptake from the FLUXCOM project and sun-induced fluorescence from the Global Ozone Monitoring Experiment-2 (GOME-2) are used in the evaluation process, again demonstrating improvements in the representation of evapotranspiration and gross primary production after assimilation.

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