Sources of uncertainty in modeled land carbon storage within and across three MIPs: Diagnosis with three new techniques

This is the final version. Available from the American Meteorological Society via the DOI in this recordTerrestrial carbon cycle models have incorporated increasingly more processes as a means to achieve more-realistic representations of ecosystem carbon cycling. Despite this, there are large across-model variations in the simulation and projection of carbon cycling. Several model intercomparison projects (MIPs), for example, the fifth phase of the Coupled Model Intercomparison Project (CMIP5) (historical simulations), Trends in Net Land-Atmosphere Carbon Exchange (TRENDY), and Multiscale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), have sought to understand intermodel differences. In this study, the authors developed a suite of new techniques to conduct post-MIP analysis to gain insights into uncertainty sources across 25 models in the three MIPs. First, terrestrial carbon storage dynamics were characterized by a three-dimensional (3D) model output space with coordinates of carbon residence time, net primary productivity (NPP), and carbon storage potential. The latter represents the potential of an ecosystem to lose or gain carbon. This space can be used to measure how and why model output differs. Models with a nitrogen cycle generally exhibit lower annual NPP in comparison with other models, and mostly negative carbon storage potential. Second, a transient traceability framework was used to decompose any given carbon cycle model into traceable components and identify the sources of model differences. The carbon residence time (or NPP) was traced to baseline carbon residence time (or baseline NPP related to the maximum carbon input), environmental scalars, and climate forcing. Third, by applying a variance decomposition method, the authors show that the intermodel differences in carbon storage can be mainly attributed to the baseline carbon residence time and baseline NPP (>90% in the three MIPs). The three techniques developed in this study offer a novel approach to gain more insight from existing MIPs and can point out directions for future MIPs. Since this study is conducted at the global scale for an overview on intermodel differences, future studies should focus more on regional analysis to identify the sources of uncertainties and improve models at the specified mechanism level.This paper is financially supported by the Research and Development Special Fund for Public Welfare Industry of the Ministry of Water Research in China (201501028). JBF and CRS were supported in part by NASA’s Carbon Cycle Science program. JBF was also supported in part by NASA’s Terrestrial Ecology and Carbon Monitoring System programs. JT acknowledges RCN funded project EVA (229771) and BCCR-BIGCHANGE

Sources of uncertainty in modeled land carbon storage within and across three MIPs: Diagnosis with three new techniques

This is the final version. Available from the American Meteorological Society via the DOI in this recordTerrestrial carbon cycle models have incorporated increasingly more processes as a means to achieve more-realistic representations of ecosystem carbon cycling. Despite this, there are large across-model variations in the simulation and projection of carbon cycling. Several model intercomparison projects (MIPs), for example, the fifth phase of the Coupled Model Intercomparison Project (CMIP5) (historical simulations), Trends in Net Land-Atmosphere Carbon Exchange (TRENDY), and Multiscale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), have sought to understand intermodel differences. In this study, the authors developed a suite of new techniques to conduct post-MIP analysis to gain insights into uncertainty sources across 25 models in the three MIPs. First, terrestrial carbon storage dynamics were characterized by a three-dimensional (3D) model output space with coordinates of carbon residence time, net primary productivity (NPP), and carbon storage potential. The latter represents the potential of an ecosystem to lose or gain carbon. This space can be used to measure how and why model output differs. Models with a nitrogen cycle generally exhibit lower annual NPP in comparison with other models, and mostly negative carbon storage potential. Second, a transient traceability framework was used to decompose any given carbon cycle model into traceable components and identify the sources of model differences. The carbon residence time (or NPP) was traced to baseline carbon residence time (or baseline NPP related to the maximum carbon input), environmental scalars, and climate forcing. Third, by applying a variance decomposition method, the authors show that the intermodel differences in carbon storage can be mainly attributed to the baseline carbon residence time and baseline NPP (>90% in the three MIPs). The three techniques developed in this study offer a novel approach to gain more insight from existing MIPs and can point out directions for future MIPs. Since this study is conducted at the global scale for an overview on intermodel differences, future studies should focus more on regional analysis to identify the sources of uncertainties and improve models at the specified mechanism level.This paper is financially supported by the Research and Development Special Fund for Public Welfare Industry of the Ministry of Water Research in China (201501028). JBF and CRS were supported in part by NASA’s Carbon Cycle Science program. JBF was also supported in part by NASA’s Terrestrial Ecology and Carbon Monitoring System programs. JT acknowledges RCN funded project EVA (229771) and BCCR-BIGCHANGE

North American carbon dioxide sources and sinks: magnitude, attribution, and uncertainty

North America is both a source and sink of atmospheric carbon dioxide (CO2). Continental sources - such as fossil-fuel combustion in the US and deforestation in Mexico - and sinks - including most ecosystems, and particularly secondary forests - add and remove CO2 from the atmosphere, respectively. Photosynthesis converts CO2 into carbon as biomass, which is stored in vegetation, soils, and wood products. However, ecosystem sinks compensate for only similar to 35% of the continent's fossil-fuel-based CO2 emissions; North America therefore represents a net CO2 source. Estimating the magnitude of ecosystem sinks, even though the calculation is confounded by uncertainty as a result of individual inventory- and model-based alternatives, has improved through the use of a combined approach. Front Ecol Environ 2012; 10(10): 512-519, doi:10.1890/12006

Effect of anthropogenic sulphate aerosol in China on the drought in the western-to-central US

In recent decades, droughts have occurred in the western-to-central United States (US), significantly affecting food production, water supplies, ecosystem health, and the propagation of vector-borne diseases. Previous studies have suggested natural sea surface temperature (SST) forcing in the Pacific as the main driver of precipitation deficits in the US. Here, we show that the aerosol forcing in China, which has been known to alter the regional hydrological cycle in East Asia, may also contribute to reducing the precipitation in the western-to-central US through atmospheric teleconnections across the Pacific. Our model experiments show some indications that both the SST forcing and the increase in regional sulphate forcing in China play a similar role in modulating the western-to-central US precipitation, especially its long-term variation. This result indicates that regional air quality regulations in China have important implications for hydrological cycles in East Asia, as well as in the USopen1

Reduced body sizes in climate-impacted tropical insect assemblages are primarily explained by range shifts

Both community composition changes due to species redistribution and within-species size shifts may alter body size structures under climate warming. Here we assess the relative contribution of these processes in community-level body size changes in tropical moth assemblages that moved uphill during a period of warming. Based on resurvey data for seven assemblages (>8000 individuals) on Mt. Kinabalu, Borneo in 1965 and 2007, we show significant wing-length reduction (mean shrinkage of 1.3% per species). Range shifts explain most size re-structuring, due to uphill shifts of relatively small species, especially at high elevations. Overall, mean forewing length shrank by ca. 5%, much of which accounted for by species range boundary shifts (3.9%), followed by within-boundary distribution changes (0.5%), and within-species size shrinkage (0.6%). We conclude that the effects of range shifting predominate, but considering species physiological responses is also important for understanding community size reorganization under climate warming

Satellite-based terrestrial production efficiency modeling

Production efficiency models (PEMs) are based on the theory of light use efficiency (LUE) which states that a relatively constant relationship exists between photosynthetic carbon uptake and radiation receipt at the canopy level. Challenges remain however in the application of the PEM methodology to global net primary productivity (NPP) monitoring. The objectives of this review are as follows: 1) to describe the general functioning of six PEMs (CASA; GLO-PEM; TURC; C-Fix; MOD17; and BEAMS) identified in the literature; 2) to review each model to determine potential improvements to the general PEM methodology; 3) to review the related literature on satellite-based gross primary productivity (GPP) and NPP modeling for additional possibilities for improvement; and 4) based on this review, propose items for coordinated research

Sources of uncertainty in modeled land carbon storage within and across three MIPs: Diagnosis with three new techniques

Terrestrial carbon cycle models have incorporated increasingly more processes as a means to achieve more-realistic representations of ecosystem carbon cycling. Despite this, there are large across-model variations in the simulation and projection of carbon cycling. Several model intercomparison projects (MIPs), for example, the fifth phase of the Coupled Model Intercomparison Project (CMIP5) (historical simulations), Trends in Net Land-Atmosphere Carbon Exchange (TRENDY), and Multiscale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), have sought to understand intermodel differences. In this study, the authors developed a suite of new techniques to conduct post-MIP analysis to gain insights into uncertainty sources across 25 models in the three MIPs. First, terrestrial carbon storage dynamics were characterized by a three-dimensional (3D) model output space with coordinates of carbon residence time, net primary productivity (NPP), and carbon storage potential. The latter represents the potential of an ecosystem to lose or gain carbon. This space can be used to measure how and why model output differs. Models with a nitrogen cycle generally exhibit lower annual NPP in comparison with other models, and mostly negative carbon storage potential. Second, a transient traceability framework was used to decompose any given carbon cycle model into traceable components and identify the sources of model differences. The carbon residence time (or NPP) was traced to baseline carbon residence time (or baseline NPP related to the maximum carbon input), environmental scalars, and climate forcing. Third, by applying a variance decomposition method, the authors show that the intermodel differences in carbon storage can be mainly attributed to the baseline carbon residence time and baseline NPP (>90% in the three MIPs). The three techniques developed in this study offer a novel approach to gain more insight from existing MIPs and can point out directions for future MIPs. Since this study is conducted at the global scale for an overview on intermodel differences, future studies should focus more on regional analysis to identify the sources of uncertainties and improve models at the specified mechanism level