scholarly journals A stand-alone tree demography and landscape structure module for Earth system models: integration with global forest data

2014 ◽  
Vol 11 (2) ◽  
pp. 2343-2382 ◽  
Author(s):  
V. Haverd ◽  
B. Smith ◽  
L. P. Nieradzik ◽  
P. R. Briggs
Keyword(s):  
Land Surface ◽  
Second Generation ◽  
Land Surface Model ◽  
Woody Biomass ◽  
Surface Model ◽  
Earth System ◽  
Large Area ◽  
System Models ◽  
Biomass Turnover ◽  
Earth System Models

Abstract. Poorly constrained rates of biomass turnover are a key limitation of Earth system models (ESM). In light of this, we recently proposed a new approach encoded in a model called Populations-Order-Physiology (POP), for the simulation of woody ecosystem stand dynamics, demography and disturbance-mediated heterogeneity. POP is suitable for continental to global applications and designed for coupling to the terrestrial ecosystem component of any ESM. POP bridges the gap between first generation Dynamic Vegetation Models (DVMs) with simple large-area parameterisations of woody biomass (typically used in current ESMs) and complex second generation DVMs, that explicitly simulate demographic processes and landscape heterogeneity of forests. The key simplification in the POP approach, compared with second-generation DVMs, is to compute physiological processes such as assimilation at grid-scale (with CABLE or a similar land surface model), but to partition the grid-scale biomass increment among age classes defined at sub grid-scale, each subject to its own dynamics. POP was successfully demonstrated along a savanna transect in northern Australia, replicating the effects of strong rainfall and fire disturbance gradients on observed stand productivity and structure. Here, we extend the application of POP to a range of forest types around the globe, employing paired observations of stem biomass and density from forest inventory data to calibrate model parameters governing stand demography and biomass evolution. The calibrated POP model is then coupled to the CABLE land surface model and the combined model (CABLE-POP) is evaluated against leaf-stem allometry observations from forest stands ranging in age from 3 to 200 yr. Results indicate that simulated biomass pools conform well with observed allometry. We conclude that POP represents a preferable alternative to large-area parameterisations of woody biomass turnover, typically used in current ESMs.

scholarly journals A stand-alone tree demography and landscape structure module for Earth system models: integration with inventory data from temperate and boreal forests

2014 ◽  
Vol 11 (15) ◽  
pp. 4039-4055 ◽  
Author(s):  
V. Haverd ◽  
B. Smith ◽  
L. P. Nieradzik ◽  
P. R. Briggs
Keyword(s):  
Land Surface ◽  
Boreal Forests ◽  
Land Surface Model ◽  
Woody Biomass ◽  
Surface Model ◽  
Earth System ◽  
Inventory Data ◽  
Large Area ◽  
Biomass Turnover ◽  
Earth System Models

Abstract. Poorly constrained rates of biomass turnover are a key limitation of Earth system models (ESMs). In light of this, we recently proposed a new approach encoded in a model called Populations-Order-Physiology (POP), for the simulation of woody ecosystem stand dynamics, demography and disturbance-mediated heterogeneity. POP is suitable for continental to global applications and designed for coupling to the terrestrial ecosystem component of any ESM. POP bridges the gap between first-generation dynamic vegetation models (DVMs) with simple large-area parameterisations of woody biomass (typically used in current ESMs) and complex second-generation DVMs that explicitly simulate demographic processes and landscape heterogeneity of forests. The key simplification in the POP approach, compared with second-generation DVMs, is to compute physiological processes such as assimilation at grid-scale (with CABLE (Community Atmosphere Biosphere Land Exchange) or a similar land surface model), but to partition the grid-scale biomass increment among age classes defined at sub-grid-scale, each subject to its own dynamics. POP was successfully demonstrated along a savanna transect in northern Australia, replicating the effects of strong rainfall and fire disturbance gradients on observed stand productivity and structure. Here, we extend the application of POP to wide-ranging temporal and boreal forests, employing paired observations of stem biomass and density from forest inventory data to calibrate model parameters governing stand demography and biomass evolution. The calibrated POP model is then coupled to the CABLE land surface model, and the combined model (CABLE-POP) is evaluated against leaf–stem allometry observations from forest stands ranging in age from 3 to 200 year. Results indicate that simulated biomass pools conform well with observed allometry. We conclude that POP represents an ecologically plausible and efficient alternative to large-area parameterisations of woody biomass turnover, typically used in current ESMs.

Where are the peatlands? Comparing two global peatland maps through L-band brightness temperature simulations

2021 ◽  
Author(s):  
Michel Bechtold ◽  
Sarith P. Mahanama ◽  
Rolf H. Reichle ◽  
Randal D. Koster ◽  
Gabrielle J. M. De Lannoy
Keyword(s):  
Soil Moisture ◽  
Brightness Temperature ◽  
Land Surface ◽  
Land Surface Model ◽  
Open Loop ◽  
Surface Model ◽  
Earth System ◽  
System Models ◽  
L Band ◽  
Earth System Models

<p>Mapping the global peatland distribution is important for embedding peatland processes into Earth System Models. Peatland maps are typically compiled from nation-specific soil or ecosystem maps or based on machine learning tools trained on such data. Here, we evaluate the performance of a land surface model with two different peatland map inputs in providing critical land surface estimates (soil moisture, temperature) to a Radiative Transfer Model (RTM) for L-band brightness temperature (Tb). We hypothesize that an improved performance of the land surface model in Tb space indicates a better spatial peatland distribution input within the footprint of Tb observations (~40 km).</p><p>We employ the NASA Catchment Land Surface Model (CLSM) with a recently added module for peatland hydrology (PEATCLSM modules). We run this model at a 9-km EASEv2 resolution over the Northern Hemisphere for two soil maps that differ in their peatland distributions. The applied soil distributions are: (MAP1) a combination of the Harmonized World Soil Database and the State Soil Geographic Database, also used to generate the Soil Moisture Active Passive (SMAP) Level-4 soil moisture product, and (MAP2) a hybrid of HWSD-STATSGO and the ‘PEATMAP’ product, which is mainly compiled from national peatland maps. MAP2 indicates ~30 % more peatland area over the Northern Hemisphere. For both peat distributions, CLSM is run and parameters of the RTM are calibrated with 10 years of multi-angular L-band Tb observations from the Soil Moisture and Ocean Salinity SMOS mission. Afterwards, CLSM is run together with the calibrated RTM within a data assimilation system, with and without (open-loop) assimilating SMAP Tb observations, for the period 2015-2020. Our results demonstrate that Tb misfits (in both the open-loop and assimilation runs) are reduced in the areas with the largest differences in peat distribution, thus indicating a basic validity of assuming a peatland-like hydrological dynamics for the larger peat extent of MAP2. Results will be discussed in the context of how peatlands are defined in global peatland maps and the question of what is typically modeled as a peatland in Earth System Models. We propose the evaluation of future releases of peatland maps in Tb space as a tool to evaluate their suitability for implementation into Earth System Models.</p>

scholarly journals Use of various remote sensing land cover products for PFT mapping over Siberia

2013 ◽  
Vol 6 (1) ◽  
pp. 255-296
Author(s):  
C. Ottlé ◽  
J. Lescure ◽  
F. Maignan ◽  
B. Poulter ◽  
T. Wang ◽  
...  
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Land Surface ◽  
Land Cover Classification ◽  
Classification Systems ◽  
Tree Cover ◽  
Surface Model ◽  
Earth System ◽  
System Models ◽  
Earth System Models

Abstract. High-latitude ecosystems play an important role in the global carbon cycle and in regulating the climate system and are presently undergoing rapid environmental change. Accurate land cover datasets are required to both document these changes as well as to provide land-surface information for benchmarking and initializing earth system models. Earth system models also require specific land cover classification systems based on plant functional types, rather than species or ecosystems, and so post-processing of existing land cover data is often required. This study compares over Siberia, multiple land cover datasets against one another and with auxiliary data to identify key uncertainties that contribute to variability in Plant Functional Type (PFT) classifications that would introduce errors in earth system modeling. Land cover classification systems from GLC 2000, GlobCover 2005 and 2009, and MODIS collections 5 and 5.1 are first aggregated to a common legend, and then compared to high-resolution land cover classification systems, continuous vegetation fields (MODIS-VCF) and satellite-derived tree heights (to discriminate against sparse, shrub, and forest vegetation). The GlobCover dataset, with a lower threshold for tree cover and taller tree heights and a better spatial resolution, tends to have better distributions of tree cover compared to high-resolution data. It has therefore been chosen to build new PFTs maps for the ORCHIDEE land surface model at 1 km scale. Compared to the original PFT dataset, the new PFT maps based on GlobCover 2005 and an updated cross-walking approach mainly differ in the characterization of forests and degree of tree cover. The partition of grasslands and bare soils now appears more realistic compared with ground-truth data. This new vegetation map provides a framework for further development of new PFTs in the ORCHIDEE model like shrubs, lichens and mosses, to better represent the water and carbon cycles in northern latitudes. Updated land cover datasets are critical for improving and maintaining the relevance of earth system models for assessing climate and human impacts on biogeochemistry and biophysics. The new PFT map at 5 km scale is available for download from the PANGAEA website, at: doi:10.1594/PANGAEA.810709.

New Vegetation Radiative Transfer Schemes for Land Surface Models

2020 ◽  
Author(s):  
Tristan Quaife
Keyword(s):  
Radiative Transfer ◽  
Computational Efficiency ◽  
Land Surface ◽  
Multiple Scales ◽  
Transfer Problem ◽  
Building Blocks ◽  
Surface Model ◽  
Earth System ◽  
System Models ◽  
Earth System Models

<p>The land surface components of climate and Earth system models tend to utilise relatively simple representations of vegetation radiative transfer processes to determine key land surface properties such as albedo, land surface temperature and the absorption of sunlight for photosynthesis. This simplicity is driven, in large part, by a need for computational efficiency. However, a growing number of studies have pointed to the need for more complex radiative transfer in these models.</p><p>An almost ubiquitous assumption in such radiative transfer schemes is that a vegetation canopy can be represented by a plane-parallel, turbid medium – a perfectly flat box in which scattering elements (i.e. leaves, branches, trunks, etc.) are randomly distributed. Real canopies typically exhibit quite complex, non-random structures often involving the clumping of leaves and branches at multiple scales. Furthermore, the optical properties of canopies are typically assumed to be vertically and horizontally homogeneous which does not allow for realistic representation of, for example, forest stands with mixed species or understory vegetation.</p><p>This presentation examines recent developments that have the potential to overcome these and other deficiencies in land surface model radiative transfer schemes, whilst maintaining sufficient computational efficiency to make them viable for inclusion in climate and Earth system models. This is achieved by using the same solutions to the transfer problem as currently employed in climate models as the building blocks to construct canopies that can vary both vertically and horizontally. </p><p> </p>

Rethinking large scale river routing by leveraging a field-scale resolving land surface model

2020 ◽  
Author(s):  
Nathaniel Chaney ◽  
Noemi Vergopolan ◽  
Colby Fisher
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Land Surface Model ◽  
Added Value ◽  
Surface Model ◽  
Earth System ◽  
Field Scale ◽  
Routing Scheme ◽  
Earth System Models ◽  
River Routing

<p>Over the past decade there has been important progress towards modeling the water, energy, and carbon cycles at field scales (10-100 meter) over continental extents. One such approach, named HydroBlocks, accomplishes this task while maintaining computational efficiency via sub-grid hydrologic response units (HRUs); these HRUs are defined via cluster analysis of available field-scale environmental datasets (e.g., elevation). However, until now, there has yet to be complementary advances in river routing schemes that are able to fully harness HydroBlocks’ approach to sub-grid heterogeneity, thus limiting the added value of field-scale resolving land surface models (e.g., riparian zone dynamics, irrigation from surface water, and interactive floodplains). In this presentation, we will introduce a novel large scale river routing scheme that leverages the modeled field-scale heterogeneity in HydroBlocks through more realistic sub-grid stream network topologies, reach-based river routing, and the simulation of floodplain dynamics.</p><p>The primary features of the novel river routing scheme include: 1) each macroscale grid cell is assigned its own river network delineated from field-scale DEMs; 2) similar sub-grid reaches (e.g., Shreve order) are grouped/clustered to ensure computational tractability; 3) the fine-scale inlet/outlet reaches of the macroscale grid cells are linked to assemble the continental river networks; 4) river dynamics are solved at the reach-level via an implicit solution of the Kinematic wave with floodplain dynamics; 5) two way connectivity is established between each cell’s sub-grid HRUs and the river network. The resulting routing scheme is able to effectively represent sub-100 meter-delineated stream networks within Earth system models with relatively minor increases in computation with respect to existing approaches. To illustrate the scheme’s novelty when coupled to the HydroBlocks land surface model, we will present simulation results over the Yellowstone river in the United States between 2002 and 2018. We will show the added value of the scheme when compared to existing approaches with regards to floodplain dynamics, water management, and riparian corridors. Furthermore, we will present results regarding the scheme’s computational tractability to ensure the feasibility of its use within Earth system models. Finally, we will discuss the potential of this approach to enhance flood and drought monitoring tools, numerical weather prediction, and climate models.</p>

Leveraging clustering and geostatistics to improve the modeling of sub-grid land-atmosphere interactions in Earth system models

2021 ◽  
Author(s):  
Nathaniel Chaney ◽  
Laura Torres-Rojas ◽  
Jason Simon
Keyword(s):  
Correlation Length ◽  
Land Surface ◽  
Spatial Organization ◽  
Sensible Heat Flux ◽  
Surface Fluxes ◽  
Surface Model ◽  
Earth System ◽  
Time Step ◽  
System Models ◽  
Earth System Models

<p>Multi-scale spatial heterogeneity over the land surface (meter to km scales) can play a pivotal role in the development of clouds and precipitation. To model this process within Earth system models (ESMs; ~100 km spatial resolution), sub-grid reduced-order modeling approaches are used. More specifically, state-of-the-art ESMs sub-divide the land surface of each grid cell into representative clusters (e.g., forest, lakes, and grasslands) that are learned a-priori from available high-resolution satellite remote sensing data (e.g., STRM, Landsat and Sentinel-2) via clustering. However, until recently, these clusters have remained spatially agnostic making it infeasible to infer spatial statistics of the modeled sub-grid heterogeneity over land that are required by the atmospheric model to ensure proper development of simulated convection (e.g., spatial correlation length of surface evaporation). This presentation will introduce an approach that leverages the precomputed cluster positions in space to construct an effective and efficient approach to assemble the experimental semivariogram from the sub-grid clusters within ESMs. As a proof of concept, we will show results by applying the novel method on sub-grid model output from the HydroBlocks land surface model over a 100 km domain centered at the Southern Great Plains site in Oklahoma, United States. Furthermore, to illustrate the added-value that the experimental semivariograms will have towards improving the modeling of land-atmosphere interactions, we will illustrate the results from large-eddy simulations over the domain that show how differences in correlation length of surface fluxes can have, at times, a dramatic impact on the development of clouds and convection in the atmosphere. When implemented in ESMs, this new approach will make it possible to infer the modeled sub-grid spatial organization of the surface fluxes (e.g., sensible heat flux) per time step with negligible increases in computation expense.</p>

scholarly journals A New Global Storage‐Area‐Depth Data Set for Modeling Reservoirs in Land Surface and Earth System Models

2018 ◽  
Vol 54 (12) ◽  
Author(s):  
Wondmagegn Yigzaw ◽  
Hong‐Yi Li ◽  
Yonas Demissie ◽  
Mohamad I. Hejazi ◽  
L. Ruby Leung ◽  
...  
Keyword(s):  
Land Surface ◽  
Earth System ◽  
Data Set ◽  
System Models ◽  
Depth Data ◽  
Storage Area ◽  
Earth System Models

Hydrological impact of the new ECMWF multi-layer snow scheme

2021 ◽  
Author(s):  
Gabriele Arduini ◽  
Ervin Zsoter ◽  
Hannah Cloke ◽  
Elisabeth Stephens ◽  
Christel Prudhomme
Keyword(s):  
Land Surface ◽  
River Discharge ◽  
Hydrological Cycle ◽  
Land Surface Model ◽  
Single Layer ◽  
Observation Time ◽  
Surface Model ◽  
Earth System ◽  
Hydrological Impact ◽  
Energy And Momentum

<p>Snow processes, with the water stored in the snowpack and released as snowmelt, are very important components of the water balance, in particular in high latitude and mountain regions. The evolution of the snow cover and the timing of the snow melt can have major impact on river discharge. Land surface models are used in Earth System models to compute exchanges of water, energy and momentum between the atmosphere and the surface underneath, and also to compute other components of the hydrological cycle. In order to improve the snow representation, a new multi-layer snow scheme is under development in the HTESSEL land surface model of the European Centre for Medium‐Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS), to replace the current single-layer snow scheme used in HTESSEL. The new scheme has already been shown to improve snow and 2‐metre temperature, while in this study, the wider hydrological impact is evaluated and documented.</p><p>The analysis is done in the reanalysis context by comparing two ERA5-forced offline HTESSEL experiments. The runoff output of HTESSEL is coupled to the CaMa-Flood hydrodynamic model in order to derive river discharge. The analysis is done globally for the period between 1980-2018. The evaluation was carried out using over 1000 discharge observation time-series with varying catchment size. The hydrological response of the multi-layer snow scheme is generally positive, but in some areas the improvement is not clear and can even be negative with deteriorated signal in river discharge. Further investigation is needed to understand the complex hydrological impact of the new snow scheme, making sure it contributes to an improved description of all hydrological components of the Earth System.</p>

scholarly journals A Budyko framework for estimating how spatial heterogeneity and lateral moisture redistribution affect average evapotranspiration rates as seen from the atmosphere

2017 ◽  
Vol 21 (1) ◽  
pp. 217-233 ◽  
Author(s):  
Elham Rouholahnejad Freund ◽  
James W. Kirchner
Keyword(s):  
Spatial Heterogeneity ◽  
Land Surface ◽  
Potential Evapotranspiration ◽  
Aridity Index ◽  
Grid Cell ◽  
Earth System ◽  
Grid Cells ◽  
Closure Relation ◽  
System Models ◽  
Earth System Models

Abstract. Most Earth system models are based on grid-averaged soil columns that do not communicate with one another, and that average over considerable sub-grid heterogeneity in land surface properties, precipitation (P), and potential evapotranspiration (PET). These models also typically ignore topographically driven lateral redistribution of water (either as groundwater or surface flows), both within and between model grid cells. Here, we present a first attempt to quantify the effects of spatial heterogeneity and lateral redistribution on grid-cell-averaged evapotranspiration (ET) as seen from the atmosphere over heterogeneous landscapes. Our approach uses Budyko curves, as a simple model of ET as a function of atmospheric forcing by P and PET. From these Budyko curves, we derive a simple sub-grid closure relation that quantifies how spatial heterogeneity affects average ET as seen from the atmosphere. We show that averaging over sub-grid heterogeneity in P and PET, as typical Earth system models do, leads to overestimations of average ET. For a sample high-relief grid cell in the Himalayas, this overestimation bias is shown to be roughly 12 %; for adjacent lower-relief grid cells, it is substantially smaller. We use a similar approach to derive sub-grid closure relations that quantify how lateral redistribution of water could alter average ET as seen from the atmosphere. We derive expressions for the maximum possible effect of lateral redistribution on average ET, and the amount of lateral redistribution required to achieve this effect, using only estimates of P and PET in possible source and recipient locations as inputs. We show that where the aridity index P/PET increases with altitude, gravitationally driven lateral redistribution will increase average ET (and models that overlook lateral redistribution will underestimate average ET). Conversely, where the aridity index P/PET decreases with altitude, gravitationally driven lateral redistribution will decrease average ET. The effects of both sub-grid heterogeneity and lateral redistribution will be most pronounced where P is inversely correlated with PET across the landscape. Our analysis provides first-order estimates of the magnitudes of these sub-grid effects, as a guide for more detailed modeling and analysis.

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