Conditions for the Compost Bomb Instability

Author(s):  
Joe Clarke ◽  
Paul Ritchie ◽  
Peter Cox

<p>Under global warming, soil temperatures are expected to rise. This increases the specific rate of microbial respiration in the soils which in turn warms the soil, creating a positive feedback process. This leads to the possibility of an instability, known as the compost bomb, in which rapidly warming soils release their soil carbon as CO2 to the atmosphere, accelerating global warming. Models of the compost bomb have exhibited interesting dynamical phenomena: excitability, rate induced tipping and bifurcation induced tipping. We examine models with increasing degrees of sophistication, to help understand the conditions that give rise to the compost bomb. We clarify the role an insulating moss layer plays and demonstrate that it has a 'most dangerous' thickness. We also use JULES, a land surface model, to examine where a compost bomb might occur and what affect other processes such as hydrology might have on the compost bomb.</p>

2014 ◽  
Vol 18 (5) ◽  
pp. 1761-1783 ◽  
Author(s):  
O. Branch ◽  
K. Warrach-Sagi ◽  
V. Wulfmeyer ◽  
S. Cohen

Abstract. A 10 × 10 km irrigated biomass plantation was simulated in an arid region of Israel to simulate diurnal energy balances during the summer of 2012 (JJA). The goal is to examine daytime horizontal flux gradients between plantation and desert. Simulations were carried out within the coupled WRF-NOAH atmosphere/land surface model. MODIS land surface data was adjusted by prescribing tailored land surface and soil/plant parameters, and by adding a controllable sub-surface irrigation scheme to NOAH. Two model cases studies were compared – Impact and Control. Impact simulates the irrigated plantation. Control simulates the existing land surface, where the predominant land surface is bare desert soil. Central to the study is parameter validation against land surface observations from a desert site and from a 400 ha Simmondsia chinensis (jojoba) plantation. Control was validated with desert observations, and Impact with Jojoba observations. Model evapotranspiration was validated with two Penman–Monteith estimates based on the observations. Control simulates daytime desert conditions with a maximum deviation for surface 2 m air temperatures (T2) of 0.2 °C, vapour pressure deficit (VPD) of 0.25 hPa, wind speed (U) of 0.5 m s−1, surface radiation (Rn) of 25 W m−2, soil heat flux (G) of 30 W m−2 and 5 cm soil temperatures (ST5) of 1.5 °C. Impact simulates irrigated vegetation conditions with a maximum deviation for T2 of 1–1.5 °C, VPD of 0.5 hPa, U of 0.5 m s−1, Rn of 50 W m−5, G of 40 W m−2 and ST5 of 2 °C. Latent heat curves in Impact correspond closely with Penman–Monteith estimates, and magnitudes of 160 W m−2 over the plantation are usual. Sensible heat fluxes, are around 450 W m−2 and are at least 100–110 W m−2 higher than the surrounding desert. This surplus is driven by reduced albedo and high surface resistance, and demonstrates that high evaporation rates may not occur over Jojoba if irrigation is optimized. Furthermore, increased daytime T2 over plantations highlight the need for hourly as well as daily mean statistics. Daily mean statistics alone may imply an overall cooling effect due to surplus nocturnal cooling, when in fact a daytime warming effect is observed.


2021 ◽  
Author(s):  
Noah D. Smith ◽  
Sarah E. Chadburn ◽  
Eleanor J. Burke ◽  
Kjetil Schanke Aas ◽  
Inge H. J. Althuizen ◽  
...  

Abstract. Microtopography can be a key driver of heterogeneity in the ground thermal and hydrological regime of permafrost landscapes. In turn, this heterogeneity can influence plant communities, methane fluxes and the initiation of abrupt thaw processes. Here we have implemented a two-tile representation of microtopography in JULES (the Joint UK Land Environment Simulator), where tiles are representative of repeating patterns of elevation difference. We evaluate the model against available spatially resolved observations at four sites, gauge the importance of explicitly representing microtopography for modelling methane emissions and quantify the relative importance of model processes and the model’s sensitivity its parameters. Tiles are coupled by lateral flows of water, heat and redistribution of snow. A surface water store is added to represent ponding. The model is parametrised using characteristic dimensions of landscape features at sites. Simulations are performed of two Siberian polygon sites, Samoylov and Kytalyk, and two Scandinavian palsa sites, Stordalen and Iškoras. The model represents the observed differences between greater snow depth in hollows vs raised areas well. The model also improves soil moisture for hollows vs the non-tiled configuration (‘standard JULES’) though the raised tile remains drier than observed. For the two palsa sites, it is found that drainage needs to be impeded from the lower tile, representing the non-permafrost mire, to achieve the observed soil saturation. This demonstrates the need for the landscape-scale drainage to be correctly modelled. Causes of moisture heterogeneity between tiles are decreased runoff from the low tile, differences in snowmelt, and high to low-tile water flow. Unsaturated flows between tiles are negligible, suggesting the adequacy of simpler water-table based models of lateral flow in wetland environments. The modelled differences in snow depths and soil moistures between tiles result in the lower tile soil temperatures being warmer for palsa sites. When comparing the soil temperatures for July at 20 cm depth, the difference in temperature between tiles, or ‘temperature splitting’, is smaller than observed (3.2 vs 5.5 °C). The mean temperature of the two tiles remains approximately unchanged (+0.4 °C) vs standard JULES, and lower than observations. Polygons display small (0.2 °C) to zero temperature splitting, in agreement with observations. Consequently, methane fluxes are near identical (+0 to 9 %) to those for standard JULES for polygons, though can be greater than standard JULES for palsa sites (+10 to 49 %). Through a sensitivity analysis we identify the parameters resulting in the greatest uncertainty in modelled temperature. We find that at the sites tested, varying the parameters can result in the modelled July temperature splitting being at most 0.9 or 3 °C larger than observed for palsa or polygon sites respectively. Varying the palsa elevation between 0.5 and 3 m has little effect on modelled soil temperatures, showing that having only two tiles can still be a valid representation of sites with a large variability of palsa elevations. Lateral conductive fluxes, while small, reduce the temperature splitting by ~1 °C, and correspond to the order of observed lateral degradation rates in peat plateau regions, indicating possible application in an area-based thaw model.


2009 ◽  
Vol 137 (7) ◽  
pp. 2263-2285 ◽  
Author(s):  
Xingang Fan

Soil temperature is a major variable in land surface models, representing soil energy status, storage, and transfer. It serves as an important factor indicating the underlying surface heating condition for weather and climate forecasts. This study utilizes the Weather Research and Forecasting (WRF) model to study the impacts of changes to the surface heating condition, derived from soil temperature observations, on regional weather simulations. Large cold biases are found in the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis project (ERA-40) soil temperatures as compared to observations. At the same time, a warm bias is found in the lower boundary assumption adopted by the Noah land surface model. In six heavy rain cases studied herein, observed soil temperatures are used to initialize the land surface model and to provide a lower boundary condition at the bottom of the model soil layer. By analyzing the impacts from the incorporation of observed soil temperatures, the following major conclusions are drawn: 1) A consistent increase in the ground heat flux is found during the day, when the observed soil temperatures are used to correct the cold bias present in ERA-40. Soil temperature changes introduced at the initial time maintain positive values but gradually decrease in magnitude with time. Sensible and latent heat fluxes and the moisture flux experience an increase during the first 6 h. 2) An increase in soil temperature impacts the air temperature through surface exchange, and near-surface moisture through evaporation. During the first two days, an increase in air temperature is seen across the region from the surface up to about 800 hPa (∼1450 m). The maximum near-surface air temperature increase is found to be, averaged over all cases, 0.5 K on the first day and 0.3 K on the second day. 3) The strength of the low-level jet is affected by the changes described above and also by the consequent changes in horizontal gradients of pressure and thermal fields. Thus, the three-dimensional circulation is affected, in addition to changes seen in the humidity and thermal fields and the locations and intensities of precipitating systems. 4) Overall results indicate that the incorporation of observed soil temperatures introduces a persistent soil heating condition that is favorable to convective development and, consequently, improves the simulation of precipitation.


2013 ◽  
Vol 26 (15) ◽  
pp. 5608-5623 ◽  
Author(s):  
Andrew G. Slater ◽  
David M. Lawrence

Abstract Permafrost is a characteristic aspect of the terrestrial Arctic and the fate of near-surface permafrost over the next century is likely to exert strong controls on Arctic hydrology and biogeochemistry. Using output from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), the authors assess its ability to simulate present-day and future permafrost. Permafrost extent diagnosed directly from each climate model's soil temperature is a function of the modeled surface climate as well as the ability of the land surface model to represent permafrost physics. For each CMIP5 model these two effects are separated by using indirect estimators of permafrost driven by climatic indices and compared to permafrost extent directly diagnosed via soil temperatures. Several robust conclusions can be drawn from this analysis. Significant air temperature and snow depth biases exist in some model's climates, which degrade both directly and indirectly diagnosed permafrost conditions. The range of directly calculated present-day (1986–2005) permafrost area is extremely large (~4–25 × 106 km2). Several land models contain structural weaknesses that limit their skill in simulating cold region subsurface processes. The sensitivity of future permafrost extent to temperature change over the present-day observed permafrost region averages (1.67 ± 0.7) × 106 km2 °C−1 but is a function of the spatial and temporal distribution of climate change. Because of sizable differences in future climates for the representative concentration pathway (RCP) emission scenarios, a wide variety of future permafrost states is predicted by 2100. Conservatively, the models suggest that for RCP4.5, permafrost will retreat from the present-day discontinuous zone. Under RCP8.5, sustainable permafrost will be most probable only in the Canadian Archipelago, Russian Arctic coast, and east Siberian uplands.


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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