Numerical models of ocean biogeochemistry are relied upon to make projections about the impact of climate change on marine resources and test hypotheses regarding the drivers of past changes in climate and ecosystems. In large areas of the ocean, iron availability regulates the functioning of marine ecosystems and hence the ocean carbon cycle. Accordingly, our ability to quantify the drivers and impacts of fluctuations in ocean ecosystems and carbon cycling in space and time relies on first achieving an appropriate representation of the modern marine iron cycle in models. When the iron distributions from 13 global ocean biogeochemistry models are compared against the latest oceanic sections from the GEOTRACES program, we find that all models struggle to reproduce many aspects of the observed spatial patterns. Models that reflect the emerging evidence for multiple iron sources or subtleties of its internal cycling perform much better in capturing observed features than their simpler contemporaries, particularly in the ocean interior. We show that the substantial uncertainty in the input fluxes of iron results in a very wide range of residence times across models, which has implications for the response of ecosystems and global carbon cycling to perturbations. Given this large uncertainty, iron fertilization experiments based on any single current generation model should be interpreted with caution. Improvements to how such models represent iron scavenging and also biological cycling are needed to raise confidence in their projections of global biogeochemical change in the ocean.

© 2015 American Geophysical Union

Under the Federal Aviation Administration’s (FAA) Aviation Climate Change Research Initiative (ACCRI), non-CO₂ climatic impacts of commercial aviation are assessed for current (2006) and for future (2050) baseline and mitigation scenarios. The effects of the non-CO₂ aircraft emissions are examined using a number of advanced climate and atmospheric chemistry transport models. Radiative forcing (RF) estimates for individual forcing effects are provided as a range for comparison against those published in the literature. Preliminary results for selected RF components for 2050 scenarios indicate that a 2% increase in fuel efficiency and a decrease in NO_x emissions due to advanced aircraft technologies and operational procedures, as well as the introduction of renewable alternative fuels, will significantly decrease future aviation climate impacts. In particular, the use of renewable fuels will further decrease RF associated with sulfate aerosol and black carbon. While this focused ACCRI program effort has yielded significant new knowledge, fundamental uncertainties remain in our understanding of aviation climate impacts. These include several chemical and physical processes associated with NO_x–O₃–CH₄ interactions and the formation of aviation-produced contrails and the effects of aviation soot aerosols on cirrus clouds as well as on deriving a measure of change in temperature from RF for aviation non-CO₂ climate impacts—an important metric that informs decision-making.

Extreme events such as droughts and heat waves have serious and damaging impacts on terrestrial processes. Under climate change, these extreme weather events are likely to shift in both magnitude and frequency at regional and local scales. The resulting interactions and feedbacks between the terrestrial and atmosphere systems could lead to non-linear and/or threshold responses in the eco-climate system, and raise a concern as to the resiliency of natural as well as managed ecosystems under extreme changes. This study investigates the response of ecosystem to droughts at different time scales and magnitudes. Four land surface models with different bio-geophysical parameterizations and representations are used to simulate soil-canopy processes, such as evapotranspiration, during these extreme events. The Terrestrial Ecosystem Model (TEM) is a process-based ecosystem model that uses spatially referenced information on climate, elevation, soils, vegetation and water availability to make monthly estimates of vegetation and soil carbon and nitrogen fluxes and pool sizes. There are two versions of TEM model, the TEM-Hydro daily model and the TEM monthly model. The Advanced Canopy-Atmosphere-Soil Algorithm (ACASA) is a multi-layered land surface model based on eddy-covariance theory to calculate the biosphere-atmosphere exchanges of carbon dioxide, water, and momentums. The Community Land Model (CLM) is a community-based model consists of biogeophysics, hydrological cycle, biogeochemistry and dynamic vegetation. Model simulations are evaluated using the biogeophysical and micrometeorological field observations from the AmeriFlux sites across the US. Preliminary results indicate that during a severe drought the link between evapotranspiration and Net Ecosystem Productivity (NEP) in the models is weaker than what observations indicate. This and other interpretations are presented and discussed in the context of planned experimental simulations with fully coupled regional ecosystem-climate model(s) driven by an integrated earth-system model.

CO₂ emissions mandates for new light-duty passenger vehicles have recently been adopted in the European Union (EU), which require steady reductions to 95 g CO₂/km in 2021. Using a computable general equilibrium (CGE) model, we analyze the impact of the mandates on oil demand, CO₂ emissions, and economic welfare, and compare the results to an emission trading scenario that achieves identical emissions reductions. We find that the mandates lower oil expenditures by about €6 billion, but at a net added cost of €12 billion in 2020. Emissions from transport are about 50MtCO₂ lower with the vehicle emission standards, but with the economy-wide emission trading, lower emissions in transport allow an equal increase in emissions elsewhere in the economy. We estimate that tightening CO₂ standards further after 2020 would cost the EU economy an additional €24–63 billion in 2025 compared with achieving the same reductions with an economy-wide emission trading system.