Earth Systems

Evaluating Simplified Chemical Mechanisms within CESM Version 1.2 CAM-chem (CAM4): MOZART-4 vs. Reduced Hydrocarbon vs. Super-Fast Chemistry

Summary: We conduct three simulations of atmospheric chemistry using chemical mechanisms of different levels of complexity and compare their results to observations. We explore situations in which the simplified mechanisms match the output of the most complex mechanism, as well as when they diverge. We investigate how the concurrent utilization of chemical mechanisms of different complexities can further our understanding of atmospheric chemistry at various scales and some strategies for future research.

Abstract: While state-of-the-art complex chemical mechanisms expand our understanding of atmospheric chemistry, their sheer size and computational requirements often limit simulations to short length, or ensembles to only a few members. Here we present and compare three 25-year offline simulations with chemical mechanisms of different levels of complexity using CESM Version 1.2 CAM-chem (CAM4): the MOZART-4 mechanism, the Reduced Hydrocarbon mechanism, and the Super-Fast mechanism. We show that, for most regions and time periods, differences in simulated ozone chemistry between these three mechanisms is smaller than the model-observation differences themselves. The MOZART-4 mechanism and the Reduced Hydrocarbon are in close agreement in their representation of ozone throughout the troposphere during all time periods (annual, seasonal and diurnal). While the Super-Fast mechanism tends to have higher simulated ozone variability and differs from the MOZART-4 mechanism over regions of high biogenic emissions, it is surprisingly capable of simulating ozone adequately given its simplicity. We explore the trade-offs between chemical mechanism complexity and computational cost by identifying regions where the simpler mechanisms are comparable to the MOZART-4 mechanism, and regions where they are not. The Super-Fast mechanism is three times as fast as the MOZART-4 mechanism, which allows for longer simulations, or ensembles with more members, that may not be feasible with the MOZART-4 mechanism given limited computational resources.

Statistical Emulators of Irrigated Crop Yields and Irrigation Water Requirements

Statistical emulators of globally gridded crop models are designed to provide decision-makers with a far less computationally intensive way to assess the impact of climate change on crop yields. In a previous paper (Blanc, 2017) focused on four major rain-fed breadbasket crops—maize, rice, soybean and wheat—the author developed a new set of crop yield emulators and showed that they could produce results comparable to those generated by an ensemble of globally gridded crop model simulations upon which they were trained. This study advances statistical emulators to provide an accessible tool to assess the impact of climate change on irrigated crop yields and irrigation water withdrawals, while accounting for crop modeling uncertainty. Together with the 2017 study, this research enables decision-makers to estimate the impact of climate change on, separately, rain-fed and irrigated crops, resulting in a more comprehensive assessment of the impact of climate change on agriculture.  

Baseline evaluation of the impact of updates to the MIT Earth System Model on its model parameter estimates

Authors' summary: We present a transparent method for evaluating how changes to the MIT Earth System Model impact its response to anthropogenic and natural forcings. We tested the effects that changes to both model components and forcings have on the estimates of model parameters that agree with historical observations. Overall, changes to model forcings are more important than the new components, while the long-term model response is unchanged. The methodology serves as a guide for documenting model development.

The future of the Earth’s energy, water and land resources will depend, in part, on how the climate will change in coming decades. To generate meaningful projections of global climate change, one must take into account two major sources of uncertainty—first, in the level of external forcings to the climate system; and second, in the magnitude of the climate system’s response to those forcings.

Description and Evaluation of the MIT Earth System Model (MESM)
Ecological control of nitrite in the upper ocean

Microorganisms oxidize organic nitrogen to nitrate in a series of steps. Nitrite, an intermediate product, accumulates at the base of the sunlit layer in the subtropical ocean, forming a primary nitrite maximum, but can accumulate throughout the sunlit layer at higher latitudes. We model nitrifying chemoautotrophs in a marine ecosystem and demonstrate that microbial community interactions can explain the nitrite distributions. Our theoretical framework proposes that nitrite can accumulate to a higher concentration than ammonium because of differences in underlying redox chemistry and cell size between ammonia- and nitrite-oxidizing chemoautotrophs. Using ocean circulation models, we demonstrate that nitrifying microorganisms are excluded in the sunlit layer when phytoplankton are nitrogen-limited, but thrive at depth when phytoplankton become light-limited, resulting in nitrite accumulation there. However, nitrifying microorganisms may coexist in the sunlit layer when phytoplankton are iron- or light-limited (often in higher latitudes). These results improve understanding of the controls on nitrification, and provide a framework for representing chemoautotrophs and their biogeochemical effects in ocean models.

Pages

Subscribe to Earth Systems