ALBERT

Description: Desert dust perturbs climate by directly and indirectly interacting with incoming solar and outgoing long wave radiation, thereby changing precipitation and temperature, in addition to modifying ocean and land biogeochemistry. While we know that desert dust is sensitive to perturbations in climate and human land use, previous studies have been unable to determine whether humans were increasing or decreasing desert dust in the global average. Here we present observational estimates of desert dust based on paleodata proxies showing a doubling of desert dust during the 20th century over much, but not all the globe. Large uncertainties remain in estimates of desert dust variability over 20th century due to limited data. Using these observational estimates of desert dust change in combination with ocean, atmosphere and land models, we calculate the net radiative effect of these observed changes (top of atmosphere) over the 20th century to be −0.14 ± 0.11 W/m2 (1990–1999 vs. 1905–1914). The estimated radiative change due to dust is especially strong between the heavily loaded 1980–1989 and the less heavily loaded 1955–1964 time periods (−0.57 ± 0.46 W/m2), which model simulations suggest may have reduced the rate of temperature increase between these time periods by 0.11 °C. Model simulations also indicate strong regional shifts in precipitation and temperature from desert dust changes, causing 6 ppm (12 PgC) reduction in model carbon uptake by the terrestrial biosphere over the 20th century. Desert dust carries iron, an important micronutrient for ocean biogeochemistry that can modulate ocean carbon storage; here we show that dust deposition trends increase ocean productivity by an estimated 6% over the 20th century, drawing down an additional 4 ppm (8 PgC) of carbon dioxide into the oceans. Thus, perturbations to desert dust over the 20th century inferred from observations are potentially important for climate and biogeochemistry, and our understanding of these changes and their impacts should continue to be refined.

Description: We explore coupling to a configurable subsurface reactive transport code as a flexible and extensible approach to biogeochemistry in land surface models; our goal is to facilitate testing of alternative models and incorporation of new understanding. A reaction network with the CLM-CN decomposition, nitrification, denitrification, and plant uptake is used as an example. We implement the reactions in the open-source PFLOTRAN code, coupled with the Community Land Model (CLM), and test at Arctic, temperate, and tropical sites. To make the reaction network designed for use in explicit time stepping in CLM compatible with the implicit time stepping used in PFLOTRAN, the Monod substrate rate-limiting function with a residual concentration is used to represent the limitation of nitrogen availability on plant uptake and immobilization. To achieve accurate, efficient, and robust numerical solutions, care needs to be taken to use scaling, clipping, or log transformation to avoid negative concentrations during the Newton iterations. With a tight relative update tolerance to avoid false convergence, an accurate solution can be achieved with about 50 % more computing time than CLM in point mode site simulations using either the scaling or clipping methods. The log transformation method takes 60–100 % more computing time than CLM. The computing time increases slightly for clipping and scaling; it increases substantially for log transformation for half saturation decrease from 10−3 to 10−9 mol m−3, which normally results in decreasing nitrogen concentrations. The frequent occurrence of very low concentrations (e.g. below nanomolar) can increase the computing time for clipping or scaling by about 20 %; computing time can be doubled for log transformation. Caution needs to be taken in choosing the appropriate scaling factor because a small value caused by a negative update to a small concentration may diminish the update and result in false convergence even with very tight relative update tolerance. As some biogeochemical processes (e.g., methane and nitrous oxide production and consumption) involve very low half saturation and threshold concentrations, this work provides insights for addressing nonphysical negativity issues and facilitates the representation of a mechanistic biogeochemical description in earth system models to reduce climate prediction uncertainty.

Description: Stocks of soil organic carbon represent a large component of the carbon cycle that may participate in climate change feedbacks, particularly on decadal and century scales. For Earth system models (ESMs), the ability to accurately represent the global distribution of existing soil carbon stocks is a prerequisite for predicting future carbon-climate feedbacks. We compared soil carbon predictions from 16 ESMs to empirical data from the Harmonized World Soil Database (HWSD) and Northern Circumpolar Soil Carbon Database (NCSCD). Model estimates of global soil carbon stocks ranged from 510 to 3050 Pg C, compared to an estimate of 890–1660 Pg C from the HWSD. Model predictions for the high latitudes fell between 60 and 800 Pg C, compared to 380–620 Pg C from the NCSCD and 290 Pg C from the HWSD. This 5.3-fold variation in global soil carbon across models compared to a 3.4-fold variation in net primary productivity (NPP) and a 3.8-fold variation in global soil carbon turnover times. The spatial distribution of soil carbon predicted by the ESMs was not well correlated with the HWSD (Pearson's correlations 〈 0.4, RMSE 9.4 to 22.8 kg C m−2), although model-data agreement generally improved at the biome scale. There was poor agreement between the HWSD and NCSCD datasets in northern latitudes (Pearson's correlation = 0.33), indicating uncertainty in empirical estimates of soil carbon. We found that a reduced complexity model dependent on NPP and soil temperature explained most of the spatial variation in soil carbon predicted by most ESMs (R2 values between 0.73 and 0.93). This result suggests that differences in soil carbon predictions between ESMs are driven primarily by differences in predicted NPP and the parameterization of soil carbon responses to NPP and temperature not by structural differences between the models. Future work should focus on accurately representing these driving variables and modifying model structure to include additional processes.

Description: Fire is an integral Earth System process that interacts with climate in multiple ways. Here we assessed the parametrization of fires in the Community Land Model (CLM-CN) and improved the ability of the model to reproduce contemporary global patterns of burned areas and fire emissions. In addition to wildfires we extended CLM-CN to account for fires related to deforestation. We compared contemporary fire carbon emissions predicted by the model to satellite based estimates in terms of magnitude, spatial extent as well as interannual and seasonal variability. Longterm trends during the 20th century were compared with historical estimates. Overall we found the best agreement between simulation and observations for the fire parametrization based on the work by Arora and Boer (2005). We obtain substantial improvement when we explicitly considered human caused ignition and fire suppression as a function of population density. Simulated fire carbon emissions ranged between 2.0 and 2.4 Pg C/year for the period 1997–2004. Regionally the simulations had a low bias over Africa and a high bias over South America when compared to satellite based products. The net terrestrial carbon source due to land use change for the 1990s was 1.2 Pg C/year with 11% stemming from deforestation fires. During 2000–2004 this flux decreased to 0.85 Pg C/year with a similar relative contribution from deforestation fires. Between 1900 and 1960 we simulated a slight downward trend in global fire emissions, which is explained by reduced fuels as a consequence of wood harvesting and partly by increasing fire suppression. The model predicted an upward trend in the last three decades of the 20th century caused by climate variations and large burning events associated with ENSO induced drought conditions.

Description: Stocks of soil organic carbon represent a large component of the carbon cycle that may participate in climate change feedbacks, particularly on decadal and centennial timescales. For Earth system models (ESMs), the ability to accurately represent the global distribution of existing soil carbon stocks is a prerequisite for accurately predicting future carbon–climate feedbacks. We compared soil carbon simulations from 11 model centers to empirical data from the Harmonized World Soil Database (HWSD) and the Northern Circumpolar Soil Carbon Database (NCSCD). Model estimates of global soil carbon stocks ranged from 510 to 3040 Pg C, compared to an estimate of 1260 Pg C (with a 95% confidence interval of 890–1660 Pg C) from the HWSD. Model simulations for the high northern latitudes fell between 60 and 820 Pg C, compared to 500 Pg C (with a 95% confidence interval of 380–620 Pg C) for the NCSCD and 290 Pg C for the HWSD. Global soil carbon varied 5.9 fold across models in response to a 2.6-fold variation in global net primary productivity (NPP) and a 3.6-fold variation in global soil carbon turnover times. Model–data agreement was moderate at the biome level (R2 values ranged from 0.38 to 0.97 with a mean of 0.75); however, the spatial distribution of soil carbon simulated by the ESMs at the 1° scale was not well correlated with the HWSD (Pearson correlation coefficients less than 0.4 and root mean square errors from 9.4 to 20.8 kg C m−2). In northern latitudes where the two data sets overlapped, agreement between the HWSD and the NCSCD was poor (Pearson correlation coefficient 0.33), indicating uncertainty in empirical estimates of soil carbon. We found that a reduced complexity model dependent on NPP and soil temperature explained much of the 1° spatial variation in soil carbon within most ESMs (R2 values between 0.62 and 0.93 for 9 of 11 model centers). However, the same reduced complexity model only explained 10% of the spatial variation in HWSD soil carbon when driven by observations of NPP and temperature, implying that other drivers or processes may be more important in explaining observed soil carbon distributions. The reduced complexity model also showed that differences in simulated soil carbon across ESMs were driven by differences in simulated NPP and the parameterization of soil heterotrophic respiration (inter-model R2 = 0.93), not by structural differences between the models. Overall, our results suggest that despite fair global-scale agreement with observational data and moderate agreement at the biome scale, most ESMs cannot reproduce grid-scale variation in soil carbon and may be missing key processes. Future work should focus on improving the simulation of driving variables for soil carbon stocks and modifying model structures to include additional processes.

Description: Fire is an integral Earth System process that interacts with climate in multiple ways. Here we assessed the parametrization of fires in the Community Land Model (CLM-CN) and improved the ability of the model to reproduce contemporary global patterns of burned areas and fire emissions. In addition to wildfires we extended CLM-CN to account for fires related to deforestation. We compared contemporary fire carbon emissions predicted by the model to satellite-based estimates in terms of magnitude and spatial extent as well as interannual and seasonal variability. Long-term trends during the 20th century were compared with historical estimates. Overall we found the best agreement between simulation and observations for the fire parametrization based on the work by Arora and Boer (2005). We obtained substantial improvement when we explicitly considered human caused ignition and fire suppression as a function of population density. Simulated fire carbon emissions ranged between 2.0 and 2.4 Pg C/year for the period 1997–2004. Regionally the simulations had a low bias over Africa and a high bias over South America when compared to satellite-based products. The net terrestrial carbon source due to land use change for the 1990s was 1.2 Pg C/year with 11% stemming from deforestation fires. During 2000–2004 this flux decreased to 0.85 Pg C/year with a similar relative contribution from deforestation fires. Between 1900 and 1960 we predicted a slight downward trend in global fire emissions caused by reduced fuels as a consequence of wood harvesting and also by increases in fire suppression. The model predicted an upward trend during the last three decades of the 20th century as a result of climate variations and large burning events associated with ENSO-induced drought conditions.

Description: Desert dust perturbs climate by interacting with incoming solar and outgoing long wave radiation, thereby changing precipitation and temperature, in addition to modifying ocean and land biogeochemistry. While we know that desert dust is sensitive to perturbations in climate and human land use, previous studies have been unable to determine whether humans were in the net increasing or decreasing desert dust. Here we present observational estimates of desert dust based on paleodata proxies showing a doubling of desert dust during the 20th century over much, but not all the globe. Large uncertainties remain in estimates of desert dust variability over 20th century due to limited data. Using these observational estimates of desert dust change in combination with ocean, atmosphere and land models, we calculate the net radiative effect of these observed changes (top of atmosphere) over the 20th century to be −0.14±0.11 W/m2 (1990–1999 vs. 1905–1914). The estimated radiative change due to aerosols is especially strong between the dusty 1980–1989 and the less dusty 1955–1964 time periods (−0.57±0.46 W/m2), which model simulations suggest may have reduced the rate of temperature increase between these time periods by 0.11 °C. Model simulations also indicate strong regional shifts in precipitation and temperature from the desert dust changes, causing 6 ppm (12 Pg C) reduction in model carbon uptake by the terrestrial biosphere over the 20th century. Desert dust carries iron, an important micronutrient for ocean biogeochemistry that can modulate ocean carbon storage; here we show that dust deposition trends increase ocean productivity by an estimated 6% over the 20th century, drawing down an additional 4 ppm (8 Pg C) of carbon dioxide into the oceans. Thus, perturbations to desert dust over the 20th century inferred from observations are potentially important for climate and biogeochemistry, and our understanding of these changes and their impacts should continue to be refined.