Research Item (44)
Idealized climate change simulations are used as benchmark experiments to facilitate the comparison of ensembles of climate models. In the Fifth Assessment Report of the IPCC the 1% per yearly compounded change in atmospheric CO2 concentration experiment was used to compare Earth System Models with full representations of the global carbon cycle (C⁴MIP). However this ``1% experiment'' was never intended for such a purpose and implies a rise in atmospheric CO2 concentration at double the rate of the instrumental record. Here we examine this choice by using an intermediate complexity climate model to compare the 1% experiment to an idealized CO2 pathway derived from a logistic function. The comparison shows that the logistic experiment has three key differences from the 1% experiment. (1) The Logistic experiment exhibits a transition of the land biosphere from a carbon sink to a carbon source, a feature absent from the 1% experiment. (2) The ocean uptake of carbon comes to dominate the carbon cycle as emissions decelerate, a feature that cannot be captured by the 1% experiment as emissions always accelerate in that experiment. (3) The permafrost carbon feedback to climate change in the 1% experiment is less than half the strength of the feedback seen in the logistic experiment. The logistic experiment also allows smooth transition to zero or negative emission states, allowing these states to be examined without sharp discontinuities in CO2 emissions. The protocol for the CMIP6 iteration of C⁴MIP again sets the 1% experiment as the benchmark experiment for model intercomparison, however clever use of the Tier 2 experiments may alleviate some of the limitations outlined here. Given the limitations of the 1% experiment as the benchmark experiment for carbon cycle intercomparisons, adding a logistic or similar idealized experiment to the protocol of the CMIP7 iteration of C⁴MIP is recommended.
We conducted a model-based assessment of changes in permafrost area and carbon storage for simulations driven by RCP4.5 and RCP8.5 projections between 2010 and 2299 for the northern permafrost region. All models simulating carbon represented soil with depth, a critical structural feature needed to represent the permafrost carbon-climate feedback, but that is not a universal feature of all climate models. Between 2010 and 2299, simulations indicated losses of permafrost between 3 and 5 million km2for the RCP4.5 climate and between 6 and 16 million km2for the RCP8.5 climate. For the RCP4.5 projection, cumulative change in soil carbon varied between 66-Pg C (1015-g carbon) loss to 70-Pg C gain. For the RCP8.5 projection, losses in soil carbon varied between 74 and 652 Pg C (mean loss, 341 Pg C). For the RCP4.5 projection, gains in vegetation carbon were largely responsible for the overall projected net gains in ecosystem carbon by 2299 (8- to 244-Pg C gains). In contrast, for the RCP8.5 projection, gains in vegetation carbon were not great enough to compensate for the losses of carbon projected by four of the five models; changes in ecosystem carbon ranged from a 641-Pg C loss to a 167-Pg C gain (mean, 208-Pg C loss). The models indicate that substantial net losses of ecosystem carbon would not occur until after 2100. This assessment suggests that effective mitigation efforts during the remainder of this century could attenuate the negative consequences of the permafrost carbon-climate feedback.
Virtually all Earth system models (ESM) show a near proportional relationship between cumulative emissions of CO2 and change in global mean temperature, a relationship which is independent of the emissions pathway taken to reach a cumulative emissions total. The relationship, which has been named the Transient Climate Response to Cumulative CO2 Emissions (TCRE), gives rise to the concept of a ‘carbon budget’. That is, a finite amount of carbon that can be burnt whilst remaining below some chosen global temperature change threshold, such as the 2.0 °C target set by the Paris Agreement. Here we show that the path-independence of TCRE arises from the partitioning ratio of anthropogenic carbon between the ocean and the atmosphere being almost the same as the partitioning ratio of enhanced radiative forcing between the ocean and space. That these ratios are so close in value is a coincidence unique to CO2. The simple model used here is underlain by many assumptions and simplifications but does reproduce key aspects of the climate system relevant to the path-independence of carbon budgets. Our results place TCRE and carbon budgets on firm physical foundations and therefore help validate the use of these metrics for climate policy.
Subsurface temperature profiles measured in boreholes are one of the important archives of paleoclimate data for reconstructing the climate of the past 2000 years. Subsurface temperatures are a function of past ground surface temperatures (GST), however GSTs are influenced both by changes in land-use and changes in regional climate. Thus the history of deforestation at borehole sampling locations represents a potential uncertainty in the reconstructed temperature history at the site. Here a fully coupled Earth system model is used estimate the magnitude of the subsurface temperature anomaly from deforestation events from a global perspective. The model simulations suggest that warming of the ground surface is the dominant response to deforestation, consistent with the limited field data that exist. The magnitude of the temperature anomaly varies by environment with a global average anomaly of 0.85 °C with a range of −0.48 °C to 1.78 °C. The warming originates from a reduction in the efficiency of turbulent energy flux to the atmosphere overcompensating an increase in albedo. Overall our simulations suggest that deforestation has a large impact on subsurface temperatures for centuries following deforestation and thus GST reconstructions should take into account previous deforestation events.
- Feb 2017
Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here, we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with MODIS satellite estimates (246 ± 6 g C m-2 yr-1), most models produced higher NPP (309 ± 12 g C m-2 yr-1) over the permafrost region during 2000–2009. By comparing the simulated gross primary productivity (GPP) with a flux-tower-based database, we found that although mean GPP among the models was only overestimated by 10% over 1982–2009, there was a two-fold discrepancy among models (380 to 800 g C m-2 yr-1), which mainly resulted from differences in simulated maximum monthly GPP (GPPmax). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area (SLA) and the maximum rate of carboxylation by the enzyme Rubisco at 25 °C (Vcmax_25), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO2 concentration. These results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPPmax as well as their sensitivity to climate change.
- Nov 2016
An emergent property of most Earth system models is a near linear relationship between cumulative emission of CO2 and change in global near surface temperature. This relationship, which has been named the transient climate response to cumulative CO2 emissions (TCRE), implies a finite budget of fossil fuel carbon that can be burnt over all time consistent with a chosen temperature change target. Carbon budgets are inversely proportional to the value of TCRE and are therefore sensitive to the uncertainty in TCRE. Here we have used a perturbed physics approach with an Earth system model of intermediate complexity to assess the uncertainty in the TCRE that arises from uncertainty in the rate of transient temperature change and the effect of this uncertainty on carbon cycle feedbacks. The experiments are conducted using an idealized 1% per year increase in CO2 concentration. Additionally we have emulated the temperature output of 23 Climate Model Intercomparison Project Phase Five (CMIP5) models. The experiment yields a mean value for TCRE of 1.72 K EgC⁻¹ with a 5th to 95th percentile range of 0.88 to 2.52 K EgC⁻¹. This range of uncertainty is consistent with the likely range from the fifth assessment report of the Intergovernmental Panel on Climate Change (0.8 to 2.5 K EgC⁻¹) but by construction underestimates the total uncertainty range of TCRE, as our experiments cannot account for the uncertainty from our models imperfect representation of the global carbon cycle. Transient temperature change uncertainty induces a 5th to 95th percentile range in the airborne fraction at the time of doubled atmospheric CO2 of 0.50 to 0.58. Overall the uncertainty in the value of TCRE remains considerable.
- Sep 2016
The sources contributing to the deglacial rise in atmospheric CO2 concentrations are unclear. Climate model simulations suggest thawing permafrost soils were the initial source, highlighting the vulnerability of modern permafrost carbon stores.
A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyse simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular focus on snow insulation effects in nine land surface models, and compare them with observations from 268 Russian stations. There are large cross-model differences in the simulated differences between near-surface soil and air temperatures (ΔT; 3 to 14 °C), in the sensitivity of soil-to-air temperature (0.13 to 0.96 °C °C−1), and in the relationship between ΔT and snow depth. The observed relationship between ΔT and snow depth can be used as a metric to evaluate the effects of each model's representation of snow insulation, hence guide improvements to the model's conceptual structure and process parameterisations. Models with better performance apply multilayer snow schemes and consider complex snow processes. Some models show poor performance in representing snow insulation due to underestimation of snow depth and/or overestimation of snow conductivity. Generally, models identified as most acceptable with respect to snow insulation simulate reasonable areas of near-surface permafrost (13.19 to 15.77 million km2). However, there is not a simple relationship between the sophistication of the snow insulation in the acceptable models and the simulated area of Northern Hemisphere near-surface permafrost, because several other factors, such as soil depth used in the models, the treatment of soil organic matter content, hydrology and vegetation cover, also affect the simulated permafrost distribution.
The global carbon cycle is sensitive to changes in global temperature and atmospheric CO2 concentration, with increased temperature tending to reduce the efficiency of carbon sinks and increased CO2 enhancing the efficiency of carbon sinks. The emission of non-CO2 greenhouse gases warms the Earth but does not induce the CO2 fertilization effect or increase the partial-pressure gradient between the atmosphere and the surface ocean. Here we present idealized climate model experiments that explore the indirect interaction between non-CO2 forcing and the carbon cycle. The experiments suggest that this interaction enhances the warming effect of the non-CO2 forcing by up to 25% after 150 years and that much of the warming caused by these agents lingers for over 100 years after the dissipation of the non-CO2 forcing. Overall, our results suggest that the longer emissions of non-CO2 forcing agents persists the greater effect these agents will have on global climate.
A significant portion of the large amount of carbon (C) currently stored in soils of the permafrost region in the Northern Hemisphere has the potential to be emitted as the greenhouse gases CO2 and CH4 under a warmer climate. In this study we evaluated the variability in the sensitivity of permafrost and C in recent decades among land surface model simulations over the permafrost region between 1960 and 2009. The 15 model simulations all predict a loss of near-surface permafrost (within 3m) area over the region, but there are large differences in the magnitude of the simulated rates of loss among the models (0.2 to 58.8×103km2yr-1). Sensitivity simulations indicated that changes in air temperature largely explained changes in permafrost area, although interactions among changes in other environmental variables also played a role. All of the models indicate that both vegetation and soil C storage together have increased by 156 to 954TgCyr-1 between 1960 and 2009 over the permafrost region even though model analyses indicate that warming alone would decrease soil C storage. Increases in gross primary production (GPP) largely explain the simulated increases in vegetation and soil C. The sensitivity of GPP to increases in atmospheric CO2 was the dominant cause of increases in GPP across the models, but comparison of simulated GPP trends across the 1982-2009 period with that of a global GPP data set indicates that all of the models overestimate the trend in GPP. Disturbance also appears to be an important factor affecting C storage, as models that consider disturbance had lower increases in C storage than models that did not consider disturbance. To improve the modeling of C in the permafrost region, there is the need for the modeling community to standardize structural representation of permafrost and carbon dynamics among models that are used to evaluate the permafrost C feedback and for the modeling and observational communities to jointly develop data sets and methodologies to more effectively benchmark models.
Recent research has demonstrated that global mean surface air warming is approximately proportional to cumulative CO2 emissions. This proportional relationship has received considerable attention, as it allows one to calculate the cumulative CO2 emissions ('carbon budget') compatible with temperature targets and is a useful measure for model inter-comparison. Here we use an Earth system model to explore whether this relationship persists during periods of net negative CO2 emissions. Negative CO2 emissions are required in the majority of emissions scenarios limiting global warming to 2 °C above pre-industrial, with emissions becoming net negative in the second half of this century in several scenarios. We find that for model simulations with a symmetric 1% per year increase and decrease in atmospheric CO2, the temperature change (ΔT) versus cumulative CO2 emissions (CE) relationship is nonlinear during periods of net negative emissions, owing to the lagged response of the deep ocean to previously increasing atmospheric CO2. When corrected for this lagged response, or if the CO2 decline is applied after the system has equilibrated with the previous CO2 increase, the ΔT versus CE relationship is close to linear during periods of net negative CO2 emissions. A proportionality constant—the transient climate response to cumulative carbon emissions (TCRE)− can therefore be calculated for both positive and net negative CO2 emission periods. We find that in simulations with a symmetric 1% per year increase and decrease in atmospheric CO2 the TCRE is larger on the upward than on the downward CO2 trajectory, suggesting that positive CO2 emissions are more effective at warming than negative emissions are at subsequently cooling. We also find that the cooling effectiveness of negative CO2 emissions decreases if applied at higher atmospheric CO2 concentrations.
The soils of the northern hemispheric permafrost region are estimated to contain 1100 to 1500 Pg of carbon. A substantial fraction of this carbon has been frozen and therefore protected from microbial decay for millennia. As anthropogenic climate warming progresses much of this permafrost is expected to thaw. Here we conduct perturbed model experiments on a climate model of intermediate complexity, with an improved permafrost carbon module, to estimate with formal uncertainty bounds the release of carbon from permafrost soils by the year 2100 and 2300 CE. We estimate that by year 2100 the permafrost region may release between 56 (13 to 118) Pg C under Representative Concentration Pathway (RCP) 2.6 and 102 (27 to 199) Pg C under RCP 8.5, with substantially more to be released under each scenario by the year 2300. Our analysis suggests that the two parameters that contribute most to the uncertainty in the release of carbon from permafrost soils are the size of the non-passive fraction of the permafrost carbon pool and the equilibrium climate sensitivity. A subset of 25 model variants are integrated 8000 years into the future under continued RCP forcing. Under the moderate RCP 4.5 forcing a remnant near-surface permafrost region persists in the high Arctic, eventually developing a new permafrost carbon pool. Overall our simulations suggest that the permafrost carbon cycle feedback to climate change will make a significant contribution to climate change over the next centuries and millennia, releasing a quantity of carbon 3 to 54 % of the cumulative anthropogenic total.
A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyze simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular focus on snow insulation effects in nine land surface models and compare them with observations from 268 Russian stations. There are large across-model differences as expressed by simulated differences between near-surface soil and air temperatures, (ΔT), of 3 to 14 K, in the gradients between soil and air temperatures (0.13 to 0.96 °C/°C), and in the relationship between ΔT and snow depth. The observed relationship between ΔT and snow depth can be used as a metric to evaluate the effects of each model's representation of snow insulation, and hence guide improvements to the model’s conceptual structure and process parameterizations. Models with better performance apply multi-layer snow schemes and consider complex snow processes. Some models show poor performance in representing snow insulation due to underestimation of snow depth and/or overestimation of snow conductivity. Generally, models identified as most acceptable with respect to snow insulation simulate reasonable areas of near-surface permafrost (12–16 million km2). However, there is not a simple relationship between the quality of the snow insulation in the acceptable models and the simulated area of Northern Hemisphere near-surface permafrost, likely because several other factors such as differences in the treatment of soil organic matter, soil hydrology, surface energy calculations, and vegetation also provide important controls on simulated permafrost distribution.
- Jan 2016
Soil temperature (Ts/change is a key indicator of the dynamics of permafrost. On seasonal and interannual timescales, the variability of Ts determines the activelayer depth, which regulates hydrological soil properties and biogeochemical processes. On the multi-decadal scale, increasing Ts 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 Ts in permafrost regions. There is a large spread of Ts 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 Ts with increasing depth. Air temperature (Ta/and longwave downward radiation (LWDR) are the main drivers of Ts 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 Ts trends, while trends of Ta only explain 5 % of the differences in Ts trends. Uncertain climate forcing contributes a larger uncertainty in Ts 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 of 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 Ts at 1 m depth across the models (R D-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 Ts at 1 m is estimated to be of-2.80 ± 0.67 million km2 °C⁻¹. Finally, by using two long-term LWDR data sets and relationships between trends of LWDR and Ts across models, we infer an observation-constrained total boreal near-surface permafrost area decrease comprising between 39 ± 14 × 103 and 75 ± 14 × 103 km2 yr⁻¹ from 1960 to 2000. This corresponds to 9-18 % degradation of the current permafrost area.
The soils of the Northern Hemisphere permafrost region are estimated to contain 1100 to 1500 Pg of carbon (Pg C). A substantial fraction of this carbon has been frozen and therefore protected from microbial decay for millennia. As anthropogenic climate warming progresses much of this permafrost is expected to thaw. Here we conduct perturbed physics experiments on a climate model of intermediate complexity, with an improved permafrost carbon module, to estimate with formal uncertainty bounds the release of carbon from permafrost soils by year 2100 and 2300. We estimate that by 2100 the permafrost region may release between 56 (13 to 118) Pg C under Representative Concentration Pathway (RCP) 2.6 and 102 (27 to 199) Pg C under RCP 8.5, with substantially more to be released under each scenario by year 2300. A subset of 25 model variants were projected 8000 years into the future under continued RCP 4.5 and 8.5 forcing. Under the high forcing scenario the permafrost carbon pool decays away over several thousand years. Under the moderate scenario forcing a remnant near-surface permafrost region persists in the high Arctic which develops a large permafrost carbon pool, leading to global recovery of the pool beginning in mid third millennium of the common era (CE). Overall our simulations suggest that the permafrost carbon cycle feedback to climate change will make a significant but not cataclysmic contribution to climate change over the next centuries and millennia.
The near proportionality between cumulative CO2 emissions and change in near surface temperature can be used to define a carbon budget: a finite quantity of carbon that can be burned associated with a chosen 'safe' temperature change threshold. Here we evaluate the sensitivity of this carbon budget to permafrost carbon dynamics and changes in non-CO2 forcings. The carbon budget for 2.0 of warming is reduced from 1320 Pg C when considering only forcing from CO2 to 810 Pg C when considering permafrost carbon feedbacks as well as other anthropogenic contributions to climate change. We also examined net carbon budgets following an overshoot of and return to a warming target. That is, the net cumulative CO2 emissions at the point in time a warming target is restored following artificial removal of CO2 from the atmosphere to cool the climate back to a chosen temperature target. These overshoot net carbon budgets are consistently smaller than the conventional carbon budgets. Overall carbon budgets persist as a robust and simple conceptual framework to relate the principle cause of climate change to the impacts of climate change.
The transient climate response to cumulative CO2 emissions (TCRE) is a metric of climate change that directly relates the primary cause of climate change (cumulative CO2 emissions) to global mean temperature change. The metric was developed once researchers noticed that the cumulative CO2 versus temperature change curve was nearly linear for almost all Earth system model output. Here, recent literature on the origin, limits, and value of TCRE is reviewed. TCRE appears to emerge from the diminishing radiative forcing per unit mass of atmospheric CO2 being compensated by diminishing efficiency of ocean heat uptake and the modulation of airborne fraction of carbon by ocean processes. The best estimate of the value of TCRE is between 0.8 to 2.5 K EgC−1. Overall, TCRE has been shown to be a conceptually simple and robust metric of climate warming with many applications in formulating climate policy.
We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation–Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2–33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9–112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of −14 to −19 Pg C • C −1 on a 100 year time scale. For CH 4 emissions, our approach assumes a fixed saturated area and that increases in CH 4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH 4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10–18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming.
A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO 2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960–2009 at 0.5 • resolution, which is a scale common among many global carbon and climate model simulations. Model performance benchmarks were drawn from comparisons against both observed CO 2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. Published by Copernicus Publications on behalf of the European Geosciences Union. 4386 M. A. Rawlins et al.: CO 2 Exchange Across Northern Eurasia The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m −2 yr −2 , equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960–1969 vs. 2000–2009), with a weakening CO 2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO 2 sink strength. The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land-atmosphere CO 2 exchange. These advances will require collection of new field data on vegetation and soil dynamics, the development of benchmarking data sets from measurements and remote-sensing observations, and investments in future model development and intercomparison studies.
A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960–2009 at 0.5° resolution, which is a scale common among many global carbon and climate model simulations. Model performance benchmarks were drawn from comparisons against both observed CO2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m−2 yr−2, equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960–1969 vs. 2000–2009), with a weakening CO2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO2 sink strength. The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land-atmosphere CO2 exchange. These advances will require collection of new field data on vegetation and soil dynamics, the development of benchmarking data sets from measurements and remote-sensing observations, and investments in future model development and intercomparison studies.
Soil temperature (Ts) change is a key indicator of the dynamics of permafrost. On seasonal and inter-annual time scales, the variability of Ts determines the active layer depth, which regulates hydrological soil properties and biogeochemical processes. On the multi-decadal scale, increasing Ts 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 Ts in permafrost regions. There is a large spread of Ts 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 Ts with increasing depth. Air temperature (Ta) and longwave downward radiation (LWDR) are the main drivers of Ts 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 Ts trends, while trends of Ta only explain 5% of the differences in Ts trends. Uncertain climate forcing contributes a larger uncertainty in Ts trends (0.021 ± 0.008 °C yr−1, mean ± SD) than the uncertainty of model structure (0.012 ± 0.001 °C yr−1), diagnosed from the range of 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 Ts at 1 m depth across the models (R = −0.85, P = 0.003), but not with the initial total near-surface permafrost area (R = −0.30, P = 0.438). The sensitivity of the total boreal near-surface permafrost area to Ts at 1 m, is estimated to be of −2.80 ± 0.67 million km2 °C−1. Finally, by using two long-term LWDR datasets and relationships between trends of LWDR and Ts across models, we infer an observation-constrained total boreal near-surface permafrost area decrease comprised between 39 ± 14 × 103 and 75 ± 14 × 103 km2 yr−1 from 1960 to 2000. This corresponds to 9–18% degradation of the current permafrost area.
We perform a land surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP) varies between 6 modern stand-alone land surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic). We also examine the variability in simulated permafrost area and distribution introduced by 5 different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes). There is good agreement (99–135 x 104 km2) between the two diagnostic methods based on air temperature which are also consistent with the best current observation-based estimate of actual permafrost area (101 x 104 km2). However the uncertainty (1–128 x 104 km2) using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index), while permafrost distribution using air temperature based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification and snow cover. Models are particularly poor at simulating permafrost distribution using definition that soil temperature remains at or below 0°C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in permafrost distribution can be made for the Tibetan Plateau.
The transient climate response to cumulative CO2 emissions (TCRE) is a useful metric of climate warming that directly relates the cause of climate change (cumulative carbon emissions) to the most used index of climate change (global mean near-surface temperature change). In this paper, analytical reasoning is used to investigate why TCRE is near constant over a range of cumulative emissions up to 2000 Pg of carbon. In addition, a climate model of intermediate complexity, forced with a constant flux of CO2 emissions, is used to explore the effect of terrestrial carbon cycle feedback strength on TCRE. The analysis reveals that TCRE emerges from the diminishing radiative forcing from CO2 per unit mass being compensated for by the diminishing ability of the ocean to take up heat and carbon. The relationship is maintained as long as the ocean uptake of carbon, which is simulated to be a function of the CO2 emissions rate, dominates changes in the airborne fraction of carbon. Strong terrestrial carbon cycle feedbacks have a dependence on the rate of carbon emission and, when present, lead to TRCE becoming rate dependent. Despite these feedbacks, TCRE remains roughly constant over the range of the representative concentration pathways and therefore maintains its primary utility as a metric of climate change.
Temperature-index models are popular tools for glacier melt-modeling due to their minimal data requirements and generally favorable performance. We examine the effects of temperature forcing provenance and extrapolation on the performance of one such model applied to a small glacier in the Saint Elias Mountains of northwestern Canada. The model is forced with air temperatures recorded (a) on two glaciers, (b) at two nearby ice-free locations, and (c) by two low-elevation valley stations. We extrapolate these temperatures using constant lapse rates and assess model performance by comparing measured and modeled cumulative summer ablation at a network of stakes over five melt seasons. When the model is calibrated individually for each temperature forcing and lapse rate, the variation in model performance is modest relative to inter-annual variations associated with melt-season conditions and calibration data quality. Despite <30% variation in estimated summer ablation arising from the combined influences of temperature forcing and lapse rate, the resulting variations in estimated annual mass balance can be significant (>100% in some cases). While model parameters calibrated in this way suffer from error compensation and exhibit equifinality, the lapse rates associated with minimum model error exhibit inter-annual variation that can be related to prevailing meteorological conditions. When the model is instead calibrated at the point scale without employing a lapse rate, and the resulting parameters are paired with an arbitrary temperature forcing, lapse rates associated with minimum model error vary widely between forcing types and years. Low-elevation stations distal from the study site sometimes outperform the calibration station, but the prescribed lapse rate becomes critical in this case. With either calibration method, lapse rates that minimize model error for the valley stations are generally steeper than the measured environmental lapse rates.
If anthropogenic CO2 emissions were to suddenly cease, the evolution of the atmospheric CO2 concentration would depend on the magnitude and sign of natural carbon sources and sinks. Experiments using Earth system models indicate that the overall carbon sinks dominate, such that upon the cessation of anthropogenic emissions, atmospheric CO2 levels decrease over time. However, these models have typically neglected the permafrost carbon pool, which has the potential to introduce an additional terrestrial source of carbon to the atmosphere. Here, the authors use the University of Victoria Earth System Climate Model (UVic ESCM), which has recently been expanded to include permafrost carbon stocks and exchanges with the atmosphere. In a scenario of zeroed CO2 and sulfate aerosol emissions, whether the warming induced by specified constant concentrations of non-CO2 greenhouse gases could slow the CO2 decline following zero emissions or even reverse this trend and cause CO2 to increase over time is assessed. It is found that a radiative forcing from non-CO2 gases of approximately 0.6 W m-2 results in a near balance of CO2 emissions from the terrestrial biosphere and uptake of CO2 by the oceans, resulting in near-constant atmospheric CO2 concentrations for at least a century after emissions are eliminated. At higher values of non-CO2 radiative forcing, CO2 concentrations increase over time, regardless of when emissions cease during the twenty-first century. Given that the present-day radiative forcing from non-CO2 greenhouse gases is about 0.95 W m-2, the results suggest that if all CO2 and aerosols emissions were eliminated without also decreasing non-CO2 greenhouse gas emissions CO2 levels would increase over time, resulting in a small increase in climate warming associated with this positive permafrost-carbon feedback.
- Oct 2013
 Most climate modeling studies of future climate have focused on the effects of carbon emissions in the present century or the long-term fate of anthropogenically emitted carbon. However, after carbon emissions cease, there may be a desire to return to a “safe” CO2 concentration within this millennium. Realistically, this implies artificially removing CO2 from the atmosphere. In this study, experiments are conducted using the University of Victoria Earth system-climate model forced with novel future scenarios to explore the reversibility of climate warming as a response to a gradual return to preindustrial radiative forcing. Due to hysteresis in the permafrost carbon pool, the quantity of carbon that must be removed from the atmosphere is larger than the quantity that was originally emitted (115–180% of original emissions). In all the reversibility simulations with a moderate climate sensitivity, a climate resembling that of the Holocene can be restored by 3000 CE.
If anthropogenic CO2 emissions were to suddenly cease, the evolution of atmospheric CO2 concentration would depend on the magnitude and sign of natural carbon sources and sinks. Previous experiments using Earth system models have indicated that overall carbon sinks dominate, such that upon cessation of anthropogenic emissions atmospheric CO2 levels begin to drop. However, these models have typically neglected the permafrost carbon pool. Here an iterative method is used with the permafrost carbon version of the University of Victoria Earth System Climate Model to determine whether atmospheric CO2 increases or decreases after cessation of anthropogenic CO2 emissions (given a constant, post cessation, concentration of non-CO2 greenhouse gasses). It is found that non-CO2 greenhouse gas concentrations with a radiative forcing of approximately 0.6 Wm-2 (relative to pre-industrial forcing) induces a near balance in CO2 emissions from the terrestrial biosphere and uptake of CO2 by the oceans, no matter when emissions cease during the 21st century. The present-day radiative forcing from non-CO2 greenhouse gasses ( 0.95Wm-2) is above the level required to balance the atmospheric carbon pool. Simulations indefinitely maintaining present-day levels of non-CO2 greenhouse gas forcing after carbon emissions cease result in an 11- 22 ppmv further increase in atmospheric CO2 concentration over a period of 300-400 years. These model experiments suggest that if anthropogenic CO2 emissions were to cease tomorrow, that CO2 would continue to build up in the atmosphere. However, CO2 concentrations are simulated to increase slowly after the cessation of anthropogenic CO2 emissions and therefore the consequences of being in such a regime are relatively mild.
- Apr 2013
Understandably, most climate modelling studies of future climate have focused on the affects of carbon emissions in the present century or the long-term fate of anthropogenically emitted carbon. These studies make an assumption: that once net anthropogenic carbon emissions cease, that humanity will make no further effort to intervene in atmospheric composition. There is a case to be made, however, that there will be a desire to return to a "safe" atmospheric concentration of CO2. Realistically this implies synthetically removing CO2 from the atmosphere and storing it is some geologically stable form. For this study experiments were conducted using the University of Victoria Earth System Climate Model (UVic ESCM) forced with novel future atmospheric trace-gas concentration pathways to explore a gradual return to pre-industrial radiative forcing. The concentration pathways follow each RCP (2.6, 4.5, 6.0, and 8.5) exactly until the peak CO2 concentration of that RCP is reached, at which point atmospheric CO2 is reduced at the same rate it increased until the 1850 concentration of CO2 is reached. Non-CO2 greenhouse gas forcing follows the prescribed RCP path until the year of peak CO2, then is subsequently linearly reduced to pre-industrial forcing. Pasture and crop areas are also gradually reduced to their pre-industrial extent. Under the middle two concentration pathways (4.5 and 6.0) a climate resembling the 20th century climate can be restored by the 25th century, although surface temperature remains above the pre-industrial temperature until at least the 30th century. Due to carbon-cycle feedbacks the quantity of carbon that must be removed from the atmosphere is larger than the quantity that was originally emitted. For concentration pathways 2.6, 4.5, and 6.0 the sequestered CO2 is 115-190% of the original cumulative carbon emissions. These results suggest that even with monumental effort to remove CO2 from the atmosphere, humanity will be living with the consequences of fossil fuel emissions for a very long time.
Permafrost soils contain an estimated 1,700a €‰Pg of carbon, almost twice the present atmospheric carbon pool. As permafrost soils thaw owing to climate warming, respiration of organic matter within these soils will transfer carbon to the atmosphere, potentially leading to a positive feedback. Models in which the carbon cycle is uncoupled from the atmosphere, together with one-dimensional models, suggest that permafrost soils could release 7-138a €‰Pg carbon by 2100 (refsa,). Here, we use a coupled global climate model to quantify the magnitude of the warming generated by the feedback between permafrost carbon release and climate. According to our simulations, permafrost soils will release between 68 and 508a €‰Pg carbon by 2100. We show that the additional surface warming generated by the feedback between permafrost carbon and climate is independent of the pathway of anthropogenic emissions followed in the twenty-first century. We estimate that this feedback could result in an additional warming of 0.13-1.69a €‰°C by 2300. We further show that the upper bound for the strength of the feedback is reached under the less intensive emissions pathways. We suggest that permafrost carbon release could lead to significant warming, even under less intensive emissions trajectories.
- Apr 2012
The permafrost soils of the northern high latitudes are estimated to contain 1700 Pg of carbon, most of it sequestered below the active layer in perennially frozen soils. This pool of carbon has been incorporated into the UVic Earth System Climate Model (ESCM) by prescribing historically permanently frozen soil layers with a uniform permafrost carbon density in the top 3.35 m of soil. When these layers thaw the permafrost carbon within them is transferred to the active soil carbon pool and the carbon is subjected to heterotrophic soil respiration. The UVic ESCM is forced under four emissions pathways diagnosed from representative concentration pathways 2.6, 4.5, 6.0, and 8.5. An uncertainty envelope for the likely strength of the permafrost carbon-climate feedback is established by varying permafrost carbon density between 16 and 26 kg m-3 and varying the equilibrium climate sensitivity (to a doubling of CO2) of the model between 2 and 4.5 °C. The strength of the permafrost carbon-climate feedback is estimated to be 0.25 (0.1 to 0.7) °C (relative to control runs with no permafrost carbon) by the end of the 21st century regardless of emission scenario followed. By the end of the 23rd century the strength of the feedback diverges by emission pathway. Notably the upper bound of the feedback strength (in terms of additional warming) is highest for the two emission pathways with the lowest cumulative anthropogenic CO2 emissions. This counterintuitive result is linked to the lower radiative efficiency of a unit of CO2 at higher atmospheric CO2 concentrations. That is, the CO2 released by the permafrost has a greater ability to warm the Earth under scenarios where there is less CO2 already in the atmosphere. If these model simulations are accurate humanity may have already set into motion a positive climate system feedback beyond our ability to mitigate with reductions in carbon emissions.
- Feb 2012
- American Association for the Advancement of Science 2012 Annual Meeting
Northern high latitudes sequester an estimated 1700 Gt of carbon held in perennially frozen ground. Much of this permafrost soil will warm and thaw as a consequence of anthropogenic climate warming, liberating the previously sequestered carbon and allowing this material to undergo decay. Here the permafrost carbon feedback is incorporated into the UVic Earth System Climate Model (ESCM), a model of intermediate complexity that presently includes a fully coupled terrestrial and oceanic carbon-cycle in addition to soil freeze-thaw physics. Sequestered permafrost carbon is prescribed into the top 3m of perennially frozen soils. Carbon in the active layer of permafrost soils is created and administered by the existing soil carbon and vegetation model components. When a soil layer thaws for the first time the permafrost carbon within the layer is moved from the sequestered carbon pool to the active soil carbon pool and the formerly sequester carbon is allowed to decay via heterotrophic respiration. The modified UVic ESCM is spun-up to preindustrial conditions and model runs are performed with and without permafrost carbon. The model is forced with Representative Concentration Pathways (RCPs) 2.6, 4.5, 6.0, and 8.5. Fossil fuel emission pathways to achieve each RCP are back-diagnosed from the simulated coupled carbon-cycle. Under each RCP allowable emissions with and without permafrost carbon diverge in the first quarter of the 21st century. Despite the wide range in atmospheric CO2 concentration and corresponding surface temperature changes between the RCPs, total carbon released from the permafrost during the 21st century ranges only from 160 Gt C (RCP 2.6) to 250 Gt C (RCP 8.5). Forced with RCP 2.6 release of permafrost carbon is halted by the mid 22nd century after 43% of the original stock of permafrost carbon is released into the active soil carbon pool. Forced with RCPs 4.5 and 6.0 release of permafrost carbon continues until the end of the simulated period in 2300 CE, decades after CO2 concentrations in the atmosphere have stabilized. Forced with RCP 8.5 nearly the entire original pool of carbon sequestered in the permafrost is respired by the mid 23rd century. These results indicate that failing to include permafrost carbon in coupled carbon-cycle simulations will result in significant over estimation of the allowable carbon emissions to achieve each RCP.
- Dec 2011
Regional hydrology and eustatic sea-level are expected to change as a consequence of climate warming. Accurate projection of these changes requires glacier melt-models with high parameter transferability in space and time. We have assessed the parameter transferability and sensitivity of a suite of glacier melt-models for two glaciers 10 km apart in the dry subarctic environment of the St. Elias Mountains, Yukon, Canada. The melt models range in complexity from a classical temperature-index model to a simplified energy balance model. Two experiments are conducted: (1) the models are tuned to the output of a full energy balance model forced under idealized conditions to assess the sensitivity of model parameters to variations in glacier geometric attributes, surface conditions, and meteorological conditions; (2) the models are tuned to real ablation stake data from our two study glaciers over two melt seasons, and the parameter transferability between the two sites and the two melt seasons is evaluated. The parameters of the temperature-index models demonstrate high sensitivity to glacier aspect, mean surface elevation, albedo, wind speed, mean annual temperature, and temperature lapse rate. The simplified energy balance model is sensitive to snow albedo. The simplified energy balance model more often than not (in seven of twelve tests) produces the highest model transferability. In the remaining five tests the classical temperature-index model produces the highest transferability twice, and a temperature-index model, where the degree-day factor is a function of potential shortwave radiation, produces the highest transferability three times. The full energy balance model when forced with real data inputs produces higher model parameter transferability than the empirical melt models in nine out of twelve tests. These results suggest that caution should be observed when extending the use of melt models beyond the locations where they were developed and tested.
Efforts to project the long-term melt of moun-tain glaciers and ice-caps require that melt models devel-oped and calibrated for well studied locations be transferable over large regions. Here we assess the sensitivity and trans-ferability of parameters within several commonly used melt models for two proximal sites in a dry subarctic environment of northwestern Canada. The models range in complexity from a classical degree-day model to a simplified energy-balance model. Parameter sensitivity is first evaluated by tuning the melt models to the output of an energy balance model forced with idealized inputs. This exercise allows us to explore parameter sensitivity both to glacier geometric at-tributes and surface characteristics, as well as to meteorolog-ical conditions. We then investigate the effect of model tun-ing with different statistics, including a weighted coefficient of determination (wR 2), the Nash-Sutcliffe efficiency crite-rion (E), mean absolute error (MAE) and root mean squared error (RMSE). Finally we examine model parameter trans-ferability between two neighbouring glaciers over two melt seasons using mass balance data collected in the St. Elias Mountains of the southwest Yukon. The temperature-index model parameters appear generally sensitive to glacier as-pect, mean surface elevation, albedo, wind speed, mean an-nual temperature and temperature lapse rate. The simplified energy balance model parameters are sensitive primarily to snow albedo. Model tuning with E, MAE and RMSE pro-duces similar, or in some cases identical, parameter values. In twelve tests of spatial and/or temporal parameter transfer-ability, the results with the lowest RMSE values with respect to ablation stake measurements were achieved twice with a Correspondence to: G. E. Flowers (email@example.com) classical temperature-index (degree-day) model, three times with a temperature-index model in which the melt parame-ter is a function of potential radiation, and seven times with a simplified energy-balance model. A full energy-balance model produced better results than the other models in nine of twelve cases, though the tuning of this model differs from that of the others.
Modeling melt from glaciers is crucial to assessing regional hydrology and eustatic sea level rise. The transferability of such models in space and time has been widely assumed but rarely tested. To investigate melt model transferability, a distributed energy-balance melt model (DEBM) is applied to two small glaciers of opposing aspects that are 10 km apart in the Donjek Range of the St. Elias Mountains, Yukon Territory, Canada. An analysis is conducted in four stages to assess the transferability of the DEBM in space and time: 1) locally derived model parameter values and meteorological forcing variables are used to assess model skill; 2) model parameter values are transferred between glacier sites and between years of study; 3) measured meteorological forcing variables are transferred between glaciers using locally derived parameter values; 4) both model pa-rameter values and measured meteorological forcing variables are transferred from one glacier site to the other, treating the second glacier site as an extension of the first. The model parameters are transferable in time to within a ,10% uncertainty in the calculated surface ablation over most or all of a melt season. Transferring model parameters or meteorological forcing variables in space creates large errors in modeled ablation. If select quantities (ice albedo, initial snow depth, and summer snowfall) are retained at their locally measured values, model transferability can be improved to achieve #15% uncertainty in the calculated surface ablation.
- Dec 2010
Accurate modeling of melt from mountain glaciers and ice-caps is needed to project changes in regional hydrology and contributions to eustatic sea-level-rise. Transferability of melt models in space and time has been widely assumed but rarely tested. To gain a better understanding of regional-scale model transferability, numerical experiments were conducted for two small mountain glaciers of opposing aspect and 10 km apart in the Canadian St. Elias Mountains. The transferability of model parameters was examined for four melt models: the classical degree-day model, an enhanced temperature-index model including potential direct solar radiation, a simplified energy-balance model, and a full energy-balance model. The full energy balance model consistently demonstrates the highest transferability of the models considered, producing approximately half the error in estimated ablation. Three further experiments were conducted to examine the conditions under which the full energy balance model produces the highest transferability: (1) model parameter values are transferred between glacier sites and between years of study; (2) measured meteorological driving variables, including accumulation, are transferred between glaciers, using locally derived parameter values; (3) both model parameter values and meteorological variables are transferred from one glacier site to the other. We find that the model parameters are transferable in time to within
Transferability of glacier melt models is necessary for reliable projections of melt over large glacierized regions and over long time-scales. The transferability of such models has been examined for individual model types, but inter-comparison has been hindered by the diversity of validation statistics used to quantify transferability. We apply four common types of melt models – the classical degree-day model, an enhanced temperature-index model, a simplified energy-balance model and a full energy-balance model – to two glaciers in the same small mountain range. The transferability of each model is examined in space and over two melt seasons. We find that the full energy balance model is consistently the most transferable, with deviations in estimated glacier-wide surface ablation of ≤ 35% when the model is forced with parameters derived from the other glacier and/or melt season. The other three models have deviations in glacier-wide surface ablation of ≥ 100% under the same forcings. In addition, we find that there is no simple relationship between model complexity and model transferability.
Heat fluxes in the continental subsurface were estimated from general circulation model (GCM) simulations of the climate of the last millennium and compared to those obtained from subsurface geothermal data. Since GCMs have bottom boundary conditions (BBCs) that are less than 10 m deep and thus may be thermodynamically restricted in the continental subsurface, we used an idealized land surface model (LSM) with a very deep BBC to estimate the potential for realistic subsurface heat storage in the absence of bottom boundary constraints. Results indicate that there is good agreement between observed fluxes and GCM simulated fluxes for the 1780-1980 period when the GCM simulated temperatures are coupled to the LSM with deep BBC. These results emphasize the importance of placing a deep BBC in GCM soil components for the proper simulation of the overall continental heat budget. In addition, the agreement between the LSM surface fluxes and the borehole temperature reconstructed fluxes lends additional support to the overall quality of the GCM (ECHO-G) paleoclimatic simulations.
Recent studies utilizing simple glacier melt models to project the melt component of mountain glacier mass-balance into the 21st century have produced an order of magnitude spread in projected sea level contribution, demonstrating the need for further refinement of these models. Energy balance models are generally recognized to have the strongest physical basis among melt models; despite this, distributed energy balance models are difficult to implement over large regions due to their reliance on site-specific data. In this study the spatial transferability of a distributed energy-balance melt model is evaluated by studying two small mountain glaciers of opposing aspect 10 km apart in the Donjek Range of the southwest Yukon Territory, Canada. Parallel meteorological and mass balance measurements were made on both glaciers in 2007-2009. The energy balance model features a subsurface heat flux component and a time-evolving aerodynamic surface roughness length parameterization, allowing the energy balance to be closed without tuning the model to ablation data. Transferability of the model is evaluated by substitution of the meteorological observations used to drive the model and the model parameters themselves. The model is run four times for each glacier: (1) using local meteorological observations and model parameters tuned to observed local values, (2) substituting meteorological observations from the other site, (3) substituting parameter values from the other site, and (4) substituting both parameter values and meteorological observations from the other site. Conditions under which energy balance models can be extended over large areas of complex terrain will allow for more confident projections of melt that are sensitive to the unique effect global change has on individual energy balance components.
Heat fluxes in the continental subsurface were estimated from general circulation model (GCM) simulations of the climate of the last millennium and compared to those obtained from subsurface geothermal data. Since GCMs have bottom boundary conditions (BBCs) that are less than 10 m deep and thus may be thermodynamically restricted in the continental subsurface, we used an idealized land surface model (LSM) with a very deep BBC to estimate the potential for realistic subsurface heat storage in the absence of bottom boundary constraints. Results indicate that there is good agreement between observed fluxes and GCM simulated fluxes for the 1780-1980 period when the GCM simulated temperatures are coupled to the LMS with deep BBC. These results emphasize the importance of placing a deep BBC in GCM soil components for the proper simulation of the overall continental heat budget. In addition, the agreement between the LSM surface fluxes and the borehole temperature reconstructed fluxes lends additional support to the overall quality of the GCM (ECHO-G) paleoclimatic simulations. Simulations to 2100 show a divergence between the LSM simulated subsurface heat content and the heat gain in the ECHO-G soil model, with the placement of the BBCs surpassing the thermodynamical effect of the choice of emission scenario as the most important factor determining heat absorption in the simulated subsurface.
1] Shallow bottom boundary conditions (BBCs) in the soil components of general circulation models (GCMs) impose artificial limits on subsurface heat storage. To assess this problem we estimate the subsurface heat content from two future climate simulations and compare to that obtained from an offline soil model (FDLSM) driven by GCM skin temperatures. FDLSM is then used as an offline substitute for the subsurface of the GCM ECHO-G. With a 600-m BBC and driven by ECHO-G future temperatures, the FDLSM subsurface absorbs 6.2 (7.5) times more heat than the ECHO-G soil model (10 m deep) under the Intergovernmental Panel on Climate Change (IPCC) A2 (B2) emission scenario. This suggests that shallow BBCs in GCM simulations may underestimate the heat stored in the subsurface, particularly for northern high latitudes. This effect could be relevant in assessing the energy balance and climate change in the next century. Citation: MacDougall,
- Jan 2008
Recent studies indicate that shallow bottom boundary conditions (BBCs) used in state-of-the-art GCMs impose an artificial limit to the amount of heat that can be absorbed by the subsurface. Since this is an important issue for determining the energy partitioning among climate model subsystems. To better quantify this effect, the energy accumulation from the ECHO-g soil model is compared to the energy accumulation in a finite difference land- surface model (FDLSM) driven by the ECHO-g based IPCC A2 and B2 future climate simulation. The FDLSM is run with a BBC at the same depth as the ECHO-g soil model (10m) to verify that the soil models are thermodynamically equivalent. A run with a deep, causally detached BBC is also carried out. Results show that the deep FDLSM run captures several times more energy than the ECHO-g soil model for the time period 1991- 2100 CE. The spatial distribution of the FDLSM enhanced heat storage is described. These results suggest that shallow BBCs in GCMs prevent large amounts of heat from being stored in the subsurface and that this effect could be relevant in simulations of future climate change.