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Abstract The Eurasian Arctic drainage constitutes over ten percent of the global land area, and stores a substantial fraction of the terrestrial carbon pool in its soils and boreal forests. Specifically, boreal forests in this region constitute an estimated carbon sink of 0.5 Pg/y. However, assessments of carbon storage and fluxes in this region, and their role in climate change, vary considerably due to large uncertainties in the extent of wetlands, which both store carbon as peat and emit carbon as methane. Accurate estimates of wetland extent have been confounded by insufficient resolution of satellite imagery and poor coverage of in situ observations. In this study we refine these estimates of wetland extent, carbon storage, and methane emissions using a system of linked large-scale models of hydrology, terrestrial carbon dynamics, and methane emissions. Large- scale hydrology comes from the Variable Infiltration Capacity (VIC) hydrological model, which includes an updated lake/wetland parameterization that estimates the water table depth as a function of both lake level and wetland soil moisture. Fast ecosystem processes such as photosynthesis and respiration are simulated via the Biosphere Energy- Transfer Hydrology (BETHY) terrestrial carbon model. Methane emissions in areas of open water or saturated soil are simulated with the Walter- Heimann (WHM) methane model. We validate this modeling system with respect to in situ observations of soil moisture and temperature, and fluxes of CO 2 and methane at flux towers at Fyodorovskoe, Russia, over the period 1998-1999. Figure 1: VIC overview and the VIC lake and wetland algorithm schematic. Land Surface Hydrology Model • Variable Infiltration Capacity (VIC) Model (Liang et al. 1994) • water and energy balance closure • macroscale • spatially-distributed • land cover classification sub-grid variability • recent additions for cold land processes (Cherkauer et al. 2003) • implemented in arctic regions by Bowling et al. (2000) and Bowling et al. (2003) • lake energy balance component builds on work of Hostetler and Bartlien (1990) and Hostetler (1991) •lake/wetland model (Bowling, 2002) handles changes in lake extent Model Framework • based on framework of Joint Simulation of Biosphere Atmosphere Coupling (JSBACH) at Max Planck Institute, Hamburg • represents feedbacks between the physical climate system and land surface processes • modular framework: allows components of land surface model to be run offline (this project) or online • fast vegetation processes: BETHY • slow vegetation processes: LPJ • combination of land surface, photosynthesis and plant respiration schemes (VIC+BETHY) forms the basic coupled model; LPJ describes slow changes in the distribution of vegetation Methane Model • Walter and Heimann (2000) with modifications described in Walter et al (2001a ) • soil methane production, and transport of methane by diffusion, ebullition, and through plants modeled explicitly • methane production occurs in the anoxic soil: bottom of the soil column to the water table • methane production rate controlled by soil temperature and NPP • time evolution of soil temperature will come from VIC Figure 3: Methane model of Walter et al (2001a). The model is forced by soil temperature and water table depth (which will come from the extended VIC model) and NPP (which will come from the BETHY and LPJ models). In Walter et al (20001a; b) global wetland extent was prescribed, however in this work it will be predicted by the VIC lake and wetlands model. REFERENCES Bowling, L.C., D.P. Lettenmaier and B.V. Matheussen, 2000. Hydroclimatology of the Arctic drainage basin, in The freshwater budget of the Arctic ocean, E.L. Lewis et al. (eds), Kluwer Academic Publishers, The Netherlands, 57- 90. Bowling, L.C., D.P. Lettenmaier, B. Nijssen, L.P. Graham, D.B. Clark, M. El Maayar, R. Essery, S. Goers, Y.M. Gusev, F. Habets, B. van den Hurk, J. Jin, D. Kahan, D. Lohmann, X. Ma, S. Mahanama, D. Mocko, O. Nasonova, G. Niu, P. Samuelsson, A.B. Shmakin, K. Takata, D. Verseghy, P. Viterbo, Y. Xia, Y. Xue and Z. Yang, 2003. Simulation of high latitude processes in the Torne-Kalix basin: PILPS Phase 2(e) 1: Experiment description and summary intercomparisons, Global and Planetary Change, 38, 1-30. Cherkauer, K. A., L. C. Bowling and D. P. Lettenmaier, 2003. Variable Infiltration Capacity (VIC) Cold Land Process Model Updates, Global and Planetary Change, 38, 151-159, 2003. De Grandi, G., F. Achard, D. Mollicone, and Y. Rauste, 2003. The GBFM radar mosaic of the Eurasian taiga: A groundwork for the bio-physical characterization of an ecosystem with relevance to global change studies, Proc. IGARSS 2003, Toulouse, France. Golubev, V.S., N.A. Speranskaya, and K.V. Tsytsenko, 2003. Total evaporation within the Volga River Basin and its variability, Russian Meteorol. Hydrol ., 7, 89- 99. Hostetler, S.W. and P.J. Bartlein, 1990. Simulation of lake evaporation with application to modeling lake level variations of Harney-Malheur Lake, Oregon, Water Res. Res., 26, 2603-2612. Hostetler, S.W., 1991. Simulation of lake ice and its effects on the late-Pleistocene evaporation rate of Lake Lahontan, Climate Dynamics 6, 43-48. Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges, 1994. A Simple hydrologically-based model of land surface water and energy fluxes for GSMs, J. Geophys. Res., 99, 14,415-14,428. Schlosser, C.A., A. Robock, K.Y. Vinnikov, N.A. Speranskaya, and Y. Xue, 1997. 18-Year land-surface hydrology model simulations for a midlatitude grassland catchment in Valdai, Russia. Mon. Weather Rev. , 125, 3279-3296. Schlosser, C.A., A.G. Slater, A. Robock, A. J. Pitman, K. Y. Vinnikov, A. Henderson-Sellers, N. A. Speranskaya, K. Mitchell, and the PILPS 2(d) contributors, 2000: Simulations of a boreal grassland hydrology at Valdai, Russia: PILPS Phase 2(d). Mon. Weather Rev, 128, 301-321. Vinnikov, K.Y., A. Robock, N.A. Speranskaya, and C.A. Schlosser, 1996. Scales of temporal and spatial variability of midlatitude soil moisture. J. Geophys. Res., 101, 7163-7174. Walter, B. P., and M. Heimann, 2000. A process-based, climate-sensitive model to derive methane emissions from natural wetlands: Application to five wetland sites, sensitivity to model parameters, and climate, Global Northern Eurasian wetlands and the carbon cycle: Model estimates of carbon storage and methane emissions Theodore J. Bohn Theodore J. Bohn 1 1 , KrishnaVeni Sathulur , KrishnaVeni Sathulur 2 2 , Erika Podest , Erika Podest 3 3 , Dennis P. Lettenmaier , Dennis P. Lettenmaier 1 1 , Laura C. Bowling , Laura C. Bowling 2 2 , Kyle McDonald , Kyle McDonald 3 3 1 1 University of Washington, Seattle, Washington, USA; University of Washington, Seattle, Washington, USA; 2 2 Purdue University, Lafayette, Indiana, USA; Purdue University, Lafayette, Indiana, USA; 3 3 JPL-NASA, Pasadena, California, USA JPL-NASA, Pasadena, California, USA American Geophysical Union Fall Meeting, San Francisco, CA, USA, Dec 10-15 2006 American Geophysical Union Fall Meeting, San Francisco, CA, USA, Dec 10-15 2006 1. Modeling Approach igure 2: Model framework used in this study. Conclusions / Future Work While this is a work in progress, we can make the following conclusions: •Although further refinement is needed, we can make reasonable predictions of carbon fluxes in forests and bogs. •Using NEE alone to validate a carbon budget can be somewhat imprecise, because it is the difference between two terms with large variances. Simultaneous measurements of several flux terms (e.g NEE, NPP, R h , DOC export, etc.) are essential for constraining errors in carbon budgets. Future Work: •Continue development of the parameterization of spatial variation of the water table in VIC •Finish the linking of VIC, BETHY, LPJ, and the Walter-Heimann methane model •Add simulations of DOC leaching and aquatic NPP •Validate these models against historical observations •Validate landcover classifications against in situ observations •Use climate model outputs to drive predictions of future lake/wetland extent and carbon cycling in Northern Eurasia over the next century NEESPI Domain Fyodorovskoe Flux Towers Site Annual Flux (g C/m 2 y) Old Fore st Towe r NPP 1356 R h 898 Net CO 2 to atm. (R h - NPP) -459 Net CH 4 to atm. - 1.25 Bog Towe r NPP 710 R h 844 Net CO 2 to atm. (R h - NPP) 134 Net CH 4 to atm. 0.43 3 Figures 2.c.1 and 2.c.2 show simulated, observed, and inferred 5-day average carbon fluxes for the two sites, respectively. Since the flux towers measure only net CO 2 flux from the atmosphere (net ecosystem exchange, or NEE), we inferred the actual respiration and NPP by assuming that night-time NEE is representative of the average soil respiration rate throughout the day, and subtracting this from day-time NEE to obtain NPP. Simulated and results agree with observations in the general shape of the seasonal cycle. Several patterns are evident at the two sites: first, observed NEE exhibits considerable scatter during the growing season, despite having been aggregated to 5-day averages. Both our inferred respiration and NPP exhibit this scatter, but examination of the original half-hourly record shows that night-time NEE is considerably more variable than day-time NEE, implying that our inferring daily respiration from night- time NEE may be subject to large errors. These fluctuations may arise from advection via turbulent fluxes (Alexander Oltchev, pers. comm.), or alternatively they might occur in response to precipitation events, in which infiltrating water forces accumulated CO 2 out of soil pore spaces (Eric Wood, pers. comm.). Second, BETHY appears to be under-simulating respiration at the forest site and over-simulating respiration at the bog site (this is more clearly expressed in scatter plots 2.c.3 and 2.c.4, for the forest and bog sites, respectively). This may be a matter of incorrect vegetation or soil parameters. - - 2.d.1: Annual Carbon Fluxes 2. Model Validation: Fyodorovskoe Flux Towers Located in the Central Forest Biosphere Reserve in Russia’s upper Volga basin, the Fyodorovskoe flux towers have been in operation since 1998. Meteorological and eddy flux variables have been recorded at both bog and forest sites. Here we present the results of point tests in which observed meteorological forcings over the period 1998-1999 (with a 3-year spin-up) drove both VIC and a stand-alone version of BETHY. VIC’s daily estimates of soil temperature and water table position, and BETHY’s daily estimates of net primary productivity (NPP), were used as inputs to the Walter-Heimann methane model (WHM). The results are shown below. a. Soil Temperature Figures 2.a.1 and 2.a.2 show simulated and observed soil temperature at 15, 50, and 100 cm depths, for the forest and bog sites, respectively. The results agree quite well with observations at shallower depths, but at deeper depths VIC appears to have a larger seasonal cycle than the observed temperatures. This may result from inaccurate soil parameters; we are still optimizing the calibration here. Annual total fluxes were estimated for each site, as shown in table 2.d.1. If we neglect the export of DOC leached from the soil, we can assess whether the systems are sinks or sources of atmospheric carbon. Our simulations indicate that the old forest site is a net sink of both atmospheric CO 2 (459 g C/m 2 y) and methane (1250 mg C/m 2 y), while the bog site is a net source for both CO 2 (134 g C/m 2 y) and methane (433 mg C/m 2 y). The CO 2 fluxes run counter to our expectations, but are consistent with BETHY’s under-simulating respiration at the forest site and over-simulating respiration at the bog site. However, the methane fluxes, calculated by WHM, are consistent with our expectation that the shallow water table during the growing season can lead to stronger methane emissions. Figures 2.b.1 and 2.b.2 show water table position and methane emissions for the two sites. While both sites have relatively shallow water tables, the bog site’s water table remains shallow for a greater portion of the beginning and end of the growing season, resulting in larger spikes in the methane emissions curve. b. Water Table and Methane c. CO 2 Flux components d. Annual Carbon Fluxes 2.a.1. 2.a.2. 2.b.1. 2.b.2. 2.c.3. 2.c.4. 2.c.2. 2.c.1. Depth (cm) Depth (cm)
Transcript
Page 1: Abstract The Eurasian Arctic drainage constitutes over ten percent of the global land area, and stores a substantial fraction of the terrestrial carbon.

AbstractThe Eurasian Arctic drainage constitutes over ten percent of the global land area, and stores

a substantial fraction of the terrestrial carbon pool in its soils and boreal forests. Specifically, boreal forests in this region constitute an estimated carbon sink of 0.5 Pg/y. However, assessments of carbon storage and fluxes in this region, and their role in climate change, vary considerably due to large uncertainties in the extent of wetlands, which both store carbon as peat and emit carbon as methane. Accurate estimates of wetland extent have been confounded by insufficient resolution of satellite imagery and poor coverage of in situ observations.

In this study we refine these estimates of wetland extent, carbon storage, and methane emissions using a system of linked large-scale models of hydrology, terrestrial carbon dynamics, and methane emissions. Large-scale hydrology comes from the Variable Infiltration Capacity (VIC) hydrological model, which includes an updated lake/wetland parameterization that estimates the water table depth as a function of both lake level and wetland soil moisture. Fast ecosystem processes such as photosynthesis and respiration are simulated via the Biosphere Energy-Transfer Hydrology (BETHY) terrestrial carbon model. Methane emissions in areas of open water or saturated soil are simulated with the Walter-Heimann (WHM) methane model. We validate this modeling system with respect to in situ observations of soil moisture and temperature, and fluxes of CO2 and methane at flux towers at Fyodorovskoe, Russia, over the period 1998-1999.

Figure 1: VIC overview and the VIC lake and wetland algorithm schematic.

Land Surface Hydrology Model • Variable Infiltration Capacity (VIC) Model (Liang et al. 1994) • water and energy balance closure• macroscale• spatially-distributed• land cover classification sub-grid variability• recent additions for cold land processes (Cherkauer et al. 2003)• implemented in arctic regions by Bowling et al. (2000) and Bowling et al. (2003)• lake energy balance component builds on work of Hostetler and Bartlien (1990) and Hostetler (1991)•lake/wetland model (Bowling, 2002) handles changes in lake extent

Model Framework• based on framework of Joint Simulation of Biosphere Atmosphere Coupling (JSBACH) at Max Planck Institute, Hamburg• represents feedbacks between the physical climate system and land surface processes • modular framework: allows components of land surface model to be run offline (this project) or online• fast vegetation processes: BETHY• slow vegetation processes: LPJ• combination of land surface, photosynthesis and plant respiration schemes (VIC+BETHY) forms the basic coupled model; LPJ describes slow changes in the distribution of vegetation

Methane Model • Walter and Heimann (2000) with modifications described in Walter et al (2001a )• soil methane production, and transport of methane by diffusion, ebullition, and through plants modeled explicitly • methane production occurs in the anoxic soil: bottom of the soil column to the water table • methane production rate controlled by soil temperature and NPP • time evolution of soil temperature will come from VIC

Figure 3: Methane model of Walter et al (2001a). The model is forced by soil temperature and water table depth (which will come from the extended VIC model) and NPP (which will come from the BETHY and LPJ models). In Walter et al (20001a; b) global wetland extent was prescribed, however in this work it will be predicted by the VIC lake and wetlands model.

REFERENCESBowling, L.C., D.P. Lettenmaier and B.V. Matheussen, 2000. Hydroclimatology of the Arctic drainage basin, in The freshwater budget of the Arctic ocean, E.L. Lewis et al. (eds), Kluwer Academic Publishers, The Netherlands, 57- 90. Bowling, L.C., D.P. Lettenmaier, B. Nijssen, L.P. Graham, D.B. Clark, M. El Maayar, R. Essery, S. Goers, Y.M. Gusev, F. Habets, B. van den Hurk, J. Jin, D. Kahan, D. Lohmann, X. Ma, S. Mahanama, D. Mocko, O. Nasonova, G. Niu, P. Samuelsson, A.B. Shmakin, K. Takata, D. Verseghy, P. Viterbo, Y. Xia, Y. Xue and Z. Yang, 2003. Simulation of high latitude processes in the Torne-Kalix basin: PILPS Phase 2(e) 1: Experiment description and summary intercomparisons, Global and Planetary Change, 38, 1-30. Cherkauer, K. A., L. C. Bowling and D. P. Lettenmaier, 2003. Variable Infiltration Capacity (VIC) Cold Land Process Model Updates, Global and Planetary Change, 38, 151-159, 2003. De Grandi, G., F. Achard, D. Mollicone, and Y. Rauste, 2003. The GBFM radar mosaic of the Eurasian taiga: A groundwork for the bio-physical characterization of an ecosystem with relevance to global change studies, Proc. IGARSS 2003, Toulouse, France.Golubev, V.S., N.A. Speranskaya, and K.V. Tsytsenko, 2003. Total evaporation within the Volga River Basin and its variability, Russian Meteorol. Hydrol., 7, 89-99. Hostetler, S.W. and P.J. Bartlein, 1990. Simulation of lake evaporation with application to modeling lake level variations of Harney-Malheur Lake, Oregon, Water Res. Res., 26, 2603-2612.Hostetler, S.W., 1991. Simulation of lake ice and its effects on the late-Pleistocene evaporation rate of Lake Lahontan, Climate Dynamics 6, 43-48.Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges, 1994. A Simple hydrologically-based model of land surface water and energy fluxes for GSMs, J. Geophys. Res., 99, 14,415-14,428.Schlosser, C.A., A. Robock, K.Y. Vinnikov, N.A. Speranskaya, and Y. Xue, 1997. 18-Year land-surface hydrology model simulations for a midlatitude grassland catchment in Valdai, Russia. Mon. Weather Rev., 125, 3279-3296.Schlosser, C.A., A.G. Slater, A. Robock, A. J. Pitman, K. Y. Vinnikov, A. Henderson-Sellers, N. A. Speranskaya, K. Mitchell, and the PILPS 2(d) contributors, 2000: Simulations of a boreal grassland hydrology at Valdai, Russia: PILPS Phase 2(d). Mon. Weather Rev, 128, 301-321. Vinnikov, K.Y., A. Robock, N.A. Speranskaya, and C.A. Schlosser, 1996. Scales of temporal and spatial variability of midlatitude soil moisture. J. Geophys. Res., 101, 7163-7174. Walter, B. P., and M. Heimann, 2000. A process-based, climate-sensitive model to derive methane emissions from natural wetlands: Application to five wetland sites, sensitivity to model parameters, and climate, Global Biogeocheical. Cycles 14, 745–765.Walter, B.P., M. Heimann, and E. Matthews, 2001a Modeling modern methane emissions from natural wetlands 1. Model description and results, J. Geophys. Res. 106, 34,189 34,206Walter, B.P., M. Heimann, and E. Matthews, 2001b Modeling modern methane emissions from natural wetlands 2. Interannual variations 1982-93, J. Geophys. Res. 106, 34,207 34,219.

Northern Eurasian wetlands and the carbon cycle: Model estimates of carbon storage and methane emissions

Theodore J. BohnTheodore J. Bohn11, KrishnaVeni Sathulur, KrishnaVeni Sathulur22, Erika Podest, Erika Podest33, Dennis P. Lettenmaier, Dennis P. Lettenmaier11, Laura C. Bowling, Laura C. Bowling22, Kyle McDonald, Kyle McDonald33

11University of Washington, Seattle, Washington, USA; University of Washington, Seattle, Washington, USA; 22Purdue University, Lafayette, Indiana, USA; Purdue University, Lafayette, Indiana, USA; 33JPL-NASA, Pasadena, California, USAJPL-NASA, Pasadena, California, USA

American Geophysical Union Fall Meeting, San Francisco, CA, USA, Dec 10-15 2006American Geophysical Union Fall Meeting, San Francisco, CA, USA, Dec 10-15 2006

1. Modeling Approach

Figure 2: Model framework used in this study.

Conclusions / Future WorkWhile this is a work in progress, we can make the following conclusions:•Although further refinement is needed, we can make reasonable predictions of carbon fluxes in forests and bogs.•Using NEE alone to validate a carbon budget can be somewhat imprecise, because it is the difference between two terms with large variances. Simultaneous measurements of several flux terms (e.g NEE, NPP, Rh, DOC export, etc.) are essential for constraining errors in carbon budgets.

Future Work:•Continue development of the parameterization of spatial variation of the water table in VIC•Finish the linking of VIC, BETHY, LPJ, and the Walter-Heimann methane model•Add simulations of DOC leaching and aquatic NPP•Validate these models against historical observations•Validate landcover classifications against in situ observations•Use climate model outputs to drive predictions of future lake/wetland extent and carbon cycling in Northern Eurasia over the next century

NEESPI Domain

Fyodorovskoe Flux Towers

Site Annual Flux (g C/m2y)

Old Forest Tower

NPP 1356

Rh 898

Net CO2 to atm. (Rh - NPP) -459

Net CH4 to atm. -1.25

Bog Tower

NPP 710

Rh 844

Net CO2 to atm. (Rh - NPP) 134

Net CH4 to atm. 0.433

Figures 2.c.1 and 2.c.2 show simulated, observed, and inferred 5-day average carbon fluxes for the two sites, respectively. Since the flux towers measure only net CO2 flux from the atmosphere (net ecosystem exchange, or NEE), we inferred the actual respiration and NPP by assuming that night-time NEE is representative of the average soil respiration rate throughout the day, and subtracting this from day-time NEE to obtain NPP. Simulated and results agree with observations in the general shape of the seasonal cycle. Several patterns are evident at the two sites: first, observed NEE exhibits considerable scatter during the growing season, despite having been aggregated to 5-day averages. Both our inferred respiration and NPP exhibit this scatter, but examination of the original half-hourly record shows that night-time NEE is considerably more variable than day-time NEE, implying that our inferring daily respiration from night-time NEE may be subject to large errors. These fluctuations may arise from advection via turbulent fluxes (Alexander Oltchev, pers. comm.), or alternatively they might occur in response to precipitation events, in which infiltrating water forces accumulated CO2 out of soil pore spaces (Eric Wood, pers. comm.). Second, BETHY appears to be under-simulating respiration at the forest site and over-simulating respiration at the bog site (this is more clearly expressed in scatter plots 2.c.3 and 2.c.4, for the forest and bog sites, respectively). This may be a matter of incorrect vegetation or soil parameters.

- -

2.d.1: Annual Carbon Fluxes

2. Model Validation: Fyodorovskoe Flux Towers

Located in the Central Forest Biosphere Reserve in Russia’s upper Volga basin, the Fyodorovskoe flux towers have been in operation since 1998. Meteorological and eddy flux variables have been recorded at both bog and forest sites. Here we present the results of point tests in which observed meteorological forcings over the period 1998-1999 (with a 3-year spin-up) drove both VIC and a stand-alone version of BETHY. VIC’s daily estimates of soil temperature and water table position, and BETHY’s daily estimates of net primary productivity (NPP), were used as inputs to the Walter-Heimann methane model (WHM). The results are shown below.

a. Soil TemperatureFigures 2.a.1 and 2.a.2 show simulated and observed soil temperature at 15, 50, and 100 cm depths, for the forest and bog sites, respectively. The results agree quite well with observations at shallower depths, but at deeper depths VIC appears to have a larger seasonal cycle than the observed temperatures. This may result from inaccurate soil parameters; we are still optimizing the calibration here.

Annual total fluxes were estimated for each site, as shown in table 2.d.1. If we neglect the export of DOC leached from the soil, we can assess whether the systems are sinks or sources of atmospheric carbon. Our simulations indicate that the old forest site is a net sink of both atmospheric CO2 (459 g C/m2y) and methane (1250 mg C/m2y), while the bog site is a net source for both CO2 (134 g C/m2y) and methane (433 mg C/m2y). The CO2 fluxes run counter to our expectations, but are consistent with BETHY’s under-simulating respiration at the forest site and over-simulating respiration at the bog site. However, the methane fluxes, calculated by WHM, are consistent with our expectation that the shallow water table during the growing season can lead to stronger methane emissions.

Figures 2.b.1 and 2.b.2 show water table position and methane emissions for the two sites. While both sites have relatively shallow water tables, the bog site’s water table remains shallow for a greater portion of the beginning and end of the growing season, resulting in larger spikes in the methane emissions curve.

b. Water Table and Methane

c. CO2 Flux components

d. Annual Carbon Fluxes

2.a.1. 2.a.2.

2.b.1. 2.b.2.

2.c.3. 2.c.4.

2.c.2.2.c.1.

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Dep

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