Integrating tropical peatland hydrology into a global land surface model (PEATCLSM)

Author(s):  
Sebastian Apers ◽  
Michel Bechtold ◽  
Andy J. Baird ◽  
Alexander R. Cobb ◽  
Greta Dargie ◽  
...  

<p>Tropical peatlands have a specific hydrology that regulates their internal processes and functioning. External disturbances such as drainage, land cover and land use changes, and climate change could disrupt the peat-specific hydrology and convert the immense peatland carbon stocks into strong greenhouse gas (GHG) emitting sources. The need for (more) accurate monitoring of GHG emissions has led to the development of complex biogeochemical models, which highly depend on proper representation of peat-specific land surface hydrology. However, the latter is often inadequately accounted for in global Earth system modeling frameworks.</p><p>In this research, we leverage the PEATCLSM modules recently developed for the Catchment land surface model (CLSM) of the NASA Goddard Earth Observing System framework (Bechtold et al., 2019). These modules were evaluated for northern peatlands, hereafter referred to as PEATCLSM<sub>N</sub>. Here, we present an extended version of PEATCLSM for tropical peatlands with literature-based parameter sets for natural (PEATCLSM<sub>T,Natural</sub>) and drained (PEATCLSM<sub>T,Drained</sub>) tropical peatlands. A suite of modeling experiments was conducted to compare the performance of PEATCLSM<sub>T,Natural</sub>, PEATCLSM<sub>T,Drained</sub>, PEATCLSM<sub>N</sub>, and the currently operational CLSM version that includes peat parameters but no peat-specific model structure (CLSM<sub>O</sub>). Simulations over major tropical peatland regions in Southeast Asia, the Congo Basin, and South and Central America were evaluated with a comprehensive and self-compiled dataset of groundwater table depth (WTD) and evapotranspiration (ET). Preliminary results show that the simulated WTD from CLSM<sub>O</sub> exhibits too much temporal variability and large biases, either positive or negative. The temporal correlation coefficient between simulated and observed WTD for both PEATCLSM<sub>T,Natural</sub> (over undeveloped peatlands only) and PEATCLSM<sub>T,Drained</sub> (over drained peatlands only) is similar to that of PEATCLSM<sub>N</sub>. However, both tropical versions reduce the average absolute bias to a few centimeters. Performance differences across the major tropical peatland regions are discussed.</p><p>Reference: Bechtold, M., De Lannoy, G. J. M., Koster, R. D., Reichle, R. H., Mahanama, S. P., Bleuten, W., et al. (2019). PEAT‐CLSM: A specific treatment of peatland hydrology in the NASA Catchment Land Surface Model.<em> Journal of Advances in Modeling Earth Systems, 11(7),</em> 2130-2162. doi: 10.1029/2018MS001574</p>

2019 ◽  
Vol 11 (7) ◽  
pp. 2130-2162 ◽  
Author(s):  
M. Bechtold ◽  
G. J. M. De Lannoy ◽  
R. D. Koster ◽  
R. H. Reichle ◽  
S. P. Mahanama ◽  
...  

2021 ◽  
Author(s):  
Sebastian Apers ◽  
Gabrielle J.M. De Lannoy ◽  
Andrew James Baird ◽  
Alexander R Cobb ◽  
Greta Dargie ◽  
...  

2020 ◽  
Author(s):  
Michel Bechtold ◽  
Gabrielle De Lannoy ◽  
Rolf H Reichle ◽  
Dirk Roose ◽  
Nicole Balliston ◽  
...  

<p>Groundwater table depth and peat moisture, exert a first order control on a range of biogeochemical and -physical peatland processes, and the susceptibility to peat fires. Therefore, one of the first critical measures to identify “peatlands under pressure” is the change of hydrological conditions, e.g. due to changing climatic conditions or direct “hydraulic” human influence. In this presentation, we introduce a new opportunity for the global-scale monitoring of moisture conditions in peatlands. We assimilate L-band brightness temperature (Tb) data from the Soil Moisture Ocean Salinity (SMOS) into the Catchment land surface model (CLSM) to improve the simulation of Northern peatland hydrology from 2010 through 2019. We compare four simulation experiments: two open loop and two data assimilation simulations, either using the default CLSM or a recently-developed peatland-specific adaptation of it (PEATCLSM, Bechtold et al. 2019). The assimilation system uses a spatially distributed ensemble Kalman filter to update soil moisture and groundwater table depth. The simulation experiments are evaluated against an in-situ dataset of groundwater table depth in about 20 natural and semi-natural peatlands that are large enough to be dominant in the corresponding 81-km<sup>2</sup> model grid cells. For PEATCLSM, Tb data assimilation increases the temporal Pearson correlation (R) and anomaly correlation (aR) between simulated and measured groundwater table from 0.53 and 0.38 (open-loop) to 0.58 and 0.45 (analysis), respectively. Time series comparison at monitoring sites demonstrates how the assimilation effectively corrects for remaining deficiencies in model physics and/or errors of the global meteorological data forcing the model. The generally lower coefficients of 0.30 (R) and 0.09 (aR) for the default CLSM also improve after Tb data assimilation to values of 0.39 (R) and 0.28 (aR). However, even with Tb data assimilation, the skill of CLSM remains inferior to that of PEATCLSM. The more realistic model physics of PEATCLSM are also supported by a reduction of the Tb misfits (observed Tb – forecasted Tb) over 94 % of the Northern peatland area. The temporal variance of Tb misfits is reduced by 20 % on average and is largest over the large peatland areas of the Western Siberian (25 %) and Hudson Bay Lowlands (40 %). This study demonstrates, for the first time, an improved estimation of the peatland hydrological dynamics by the assimilation of SMOS L-band brightness data into a global land surface model and suggests a new route of research focusing on the incorporation of additional satellite observations into peatland-specific modeling schemes.</p><p>Bechtold, M., De Lannoy, G.J M., Koster, R.D., Reichle, R.H., et al. (2019). PEAT-CLSM: A Specific Treatment of Peatland Hydrology in the NASA Catchment Land Surface Model. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 11 (7), 2130-2162. doi: 10.1029/2018MS001574.</p>


2020 ◽  
pp. 052
Author(s):  
Jean-Christophe Calvet ◽  
Jean-Louis Champeaux

Cet article présente les différentes étapes des développements réalisés au CNRM des années 1990 à nos jours pour spatialiser à diverses échelles les simulations du modèle Isba des surfaces terrestres. Une attention particulière est portée sur l'intégration, dans le modèle, de données satellitaires permettant de caractériser la végétation. Deux façons complémentaires d'introduire de l'information géographique dans Isba sont présentées : cartographie de paramètres statiques et intégration au fil de l'eau dans le modèle de variables observables depuis l'espace. This paper presents successive steps in developments made at CNRM from the 1990s to the present-day in order to spatialize the simulations of the Isba land surface model at various scales. The focus is on the integration in the model of satellite data informative about vegetation. Two complementary ways to integrate geographic information in Isba are presented: mapping of static model parameters and sequential assimilation of variables observable from space.


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