Modeling the large-scale effects of surface moisture heterogeneity on wetland carbon fluxes in the West Siberian Lowland

Bohn, T. J.; Podest, E.; Schroeder, R.; Pinto, N.; McDonald, K. C.; Glagolev, M. V.; Filippov, Ilya; Maksyutov, Shamil; Heimann, Martin; Chen, Xiaodong; Lettenmaier, Dennis P.

doi:10.5194/bg-10-6559-2013

Cited by 48 publications

(55 citation statements)

References 69 publications

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“…Among the participating models (Table 2) were those of the WETCHIMP study Wania et al, 2013) that contributed CH 4 emissions estimates: CLM4Me (Riley et al, 2011), DLEM (Tian et al, 2010(Tian et al, , 2011a(Tian et al, , b, 2012, IAP-RAS (Mokhov et al, 2007;Eliseev et al, 2008), LPJ-Bern (Spahni et al, 2011, LPJWHyMe (Wania et al, 2009a(Wania et al, , b, 2010, LPJ-WSL (Hodson et al, 2011), ORCHIDEE (Ringeval et al, 2010), SDGVM (Hopcroft et al, 2011), and UW-VIC (denoted by "UW-VIC (GIEMS)"; Bohn et al, 2013). In addition, we analyzed several other models.…”

Section: Modelsmentioning

confidence: 99%

“…(b) Dominant land cover at 25 km derived from MODIS-MOD12Q1 500 m land cover classification (Friedl et al, 2010). each grid cell (e.g., Zhuang et al, 2004) to more sophisticated schemes that allow for sub-grid heterogeneity in the water table (e.g., Bohn et al, 2007Bohn et al, , 2013Ringeval et al, 2010;Riley et al, 2011;Kleinen et al, 2012;Stocker et al, 2014;Subin et al, 2014). Finally, peatland soils can be highly acidic and nutrient-poor, and much of the available carbon substrate can be recalcitrant (Clymo et al, 1984;Dorrepaal et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

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WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia

et al. 2015

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Abstract. Wetlands are the world's largest natural source of methane, a powerful greenhouse gas. The strong sensitivity of methane emissions to environmental factors such as soil temperature and moisture has led to concerns about potential positive feedbacks to climate change. This risk is particularly relevant at high latitudes, which have experienced pronounced warming and where thawing permafrost could potentially liberate large amounts of labile carbon over the next 100 years. However, global models disagree as to the magnitude and spatial distribution of emissions, due to uncertainties in wetland area and emissions per unit area and a scarcity of in situ observations. Recent intensive field campaigns across the West Siberian Lowland (WSL) make this an ideal region over which to assess the perPublished by Copernicus Publications on behalf of the European Geosciences Union. T. J. Bohn et al.: Intercomparison of wetland methane emissions modelsformance of large-scale process-based wetland models in a high-latitude environment. Here we present the results of a follow-up to the Wetland and Wetland CH 4 Intercomparison of Models Project (WETCHIMP), focused on the West Siberian Lowland (WETCHIMP-WSL). We assessed 21 models and 5 inversions over this domain in terms of total CH 4 emissions, simulated wetland areas, and CH 4 fluxes per unit wetland area and compared these results to an intensive in situ CH 4 flux data set, several wetland maps, and two satellite surface water products. We found that (a) despite the large scatter of individual estimates, 12-year mean estimates of annual total emissions over the WSL from forward models (5.34 ± 0.54 Tg CH 4 yr −1 ), inversions (6.06 ± 1.22 Tg CH 4 yr −1 ), and in situ observations (3.91 ± 1.29 Tg CH 4 yr −1 ) largely agreed; (b) forward models using surface water products alone to estimate wetland areas suffered from severe biases in CH 4 emissions; (c) the interannual time series of models that lacked either soil thermal physics appropriate to the high latitudes or realistic emissions from unsaturated peatlands tended to be dominated by a single environmental driver (inundation or air temperature), unlike those of inversions and more sophisticated forward models; (d) differences in biogeochemical schemes across models had relatively smaller influence over performance; and (e) multiyear or multidecade observational records are crucial for evaluating models' responses to long-term climate change.

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Section: Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia

et al. 2015

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“…Hereafter, the term "boreal regions" is used for the sum of the three sub-regions BONA, BOEU, and BOAS in Fig. 1 Kalnay et al (1996) Bohn et al (2013) Surface shortwave and longwave downward radiation were internally calculated.…”

Section: Models and Simulationsmentioning

confidence: 99%

Simulated high-latitude soil thermal dynamics during the past 4 decades

et al. 2016

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Abstract. Soil temperature (T s ) change is a key indicator of the dynamics of permafrost. On seasonal and interannual timescales, the variability of T s determines the activelayer depth, which regulates hydrological soil properties and biogeochemical processes. On the multi-decadal scale, increasing T s not only drives permafrost thaw/retreat but can also trigger and accelerate the decomposition of soil organic carbon. The magnitude of permafrost carbon feedbacks is thus closely linked to the rate of change of soil thermal regimes. In this study, we used nine process-based ecosystem models with permafrost processes, all forced by different observation-based climate forcing during the period 1960-2000, to characterize the warming rate of T s in permafrost regions. There is a large spread of T s trends at 20 cm depth across the models, with trend values ranging from 0.010 ± 0.003 to 0.031 ± 0.005 • C yr −1 . Most models show smaller increase in T s with increasing depth. Air temperature (T a ) and longwave downward radiation (LWDR) are the main drivers of T s trends, but their relative contributions differ amongst the models. Different trends of LWDR used in the forcing of models can explain 61 % of their differences in T s trends, while trends of T a only explain 5 % of the differences in T s trends. Uncertain climate forcing contributes a larger uncertainty in T s trends (0.021 ± 0.008 • C yr −1 , mean ± standard deviation) than the uncertainty of model structure (0.012 ± 0.001 • C yr −1 ), diagnosed from the range Published by Copernicus Publications on behalf of the European Geosciences Union. S. Peng et al.: Simulated high-latitude soil thermal dynamics during the past 4 decadesof response between different models, normalized to the same forcing. In addition, the loss rate of near-surface permafrost area, defined as total area where the maximum seasonal active-layer thickness (ALT) is less than 3 m loss rate, is found to be significantly correlated with the magnitude of the trends of T s at 1 m depth across the models (R = −0.85, P = 0.003), but not with the initial total nearsurface permafrost area (R = −0.30, P = 0.438). The sensitivity of the total boreal near-surface permafrost area to T s at 1 m is estimated to be of −2.80 ± 0.67 million km 2 • C −1 . Finally, by using two long-term LWDR data sets and relationships between trends of LWDR and T s across models, we infer an observation-constrained total boreal near-surface permafrost area decrease comprising between 39 ± 14 × 10 3 and 75 ± 14 × 10 3 km 2 yr −1 from 1960 to 2000. This corresponds to 9-18 % degradation of the current permafrost area.

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“…Other ecohydrological models couple hydrology and carbon cycles in peatlands, but differ with respect to their hydrological schemes and the way they treat (or ignore) topography (Dimitrov et al, 2011). Some models, such as Biome-BGC (Bond-Lamberty et al, 2007), and Wetland-DNDC (Zhang et al, 2002) only simulate vertical soil water flow, neglecting lateral flow components (Dimitrov et al, 2011) within peatlands. Wania et al (2010) describe a model of wetland hydrology and biogeochemistry (LPJ-WHyMe), but do not include consideration of microtopography or lateral flows.…”

Section: Introductionmentioning

confidence: 99%

Representing northern peatland microtopography and hydrology within the Community Land Model

et al. 2015

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Abstract. Predictive understanding of northern peatland hydrology is a necessary precursor to understanding the fate of massive carbon stores in these systems under the influence of present and future climate change. Current models have begun to address microtopographic controls on peatland hydrology, but none have included a prognostic calculation of peatland water table depth for a vegetated wetland, independent of prescribed regional water tables. We introduce here a new configuration of the Community Land Model (CLM) which includes a fully prognostic water table calculation for a vegetated peatland. Our structural and process changes to CLM focus on modifications needed to represent the hydrologic cycle of bogs environment with perched water tables, as well as distinct hydrologic dynamics and vegetation communities of the raised hummock and sunken hollow microtopography characteristic of peatland bogs. The modified model was parameterized and independently evaluated against observations from an ombrotrophic raised-dome bog in northern Minnesota (S1-Bog), the site for the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE). Simulated water table levels compared well with site-level observations. The new model predicts hydrologic changes in response to planned warming at the SPRUCE site. At present, standing water is commonly observed in bog hollows after large rainfall events during the growing season, but simulations suggest a sharp decrease in water table levels due to increased evapotranspiration under the most extreme warming level, nearly eliminating the occurrence of standing water in the growing season. Simulated soil energy balance was strongly influenced by reduced winter snowpack under warming simulations, with the warming influence on soil temperature partly offset by the loss of insulating snowpack in early and late winter. The new model provides improved predictive capacity for seasonal hydrological dynamics in northern peatlands, and provides a useful foundation for investigation of northern peatland carbon exchange.

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Modeling the large-scale effects of surface moisture heterogeneity on wetland carbon fluxes in the West Siberian Lowland

Cited by 48 publications

References 69 publications

WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia

WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia

Simulated high-latitude soil thermal dynamics during the past 4 decades

Representing northern peatland microtopography and hydrology within the Community Land Model

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