Global aerosol simulations are conducted by using the Community Atmosphere Model version 5 with the Aerosol Two‐dimensional bin module for foRmation and Aging Simulation version 2 (CAM5‐chem/ATRAS2) ...which was developed in part 1. The model uses a two‐dimensional (2‐D) section representation with 12 size bins from 1 nm to 10 μm and 8 black carbon (BC) mixing state bins, and it can calculate detailed aerosol processes and their interactions with radiation and clouds. The simulations have similar or better agreement with aerosol observations (e.g., aerosol optical depth, absorption aerosol optical depth (AAOD), aerosol number concentrations, mass concentrations of each species) compared with the simulations using the Modal Aerosol Model with three modes. Sensitivity simulations show that global mean AAOD is reduced by 15% by resolving BC mixing state as a result of two competing effects (optical and lifetime effects). AAOD is reduced by 10–50% at low and midlatitudes in the 2‐D sectional simulation because BC absorption enhancement by coating species is reduced by resolving pure BC, thinly coated BC, and BC‐free particles in the model (optical effect). In contrast, AAOD is enhanced by 5–30% at high‐latitudes because BC concentrations are enhanced by 40–200% over the regions by resolving less CCN active particles (lifetime effect). The simulations also suggest a model which resolves more than 3 BC categories (including BC‐free particles) is desirable to calculate the optical and lifetime effects accurately. The complexity of aerosol representation is shown to be especially important for simulations of BC and CCN concentrations and AAOD.
Key Points
Simulations of a 2‐D sectional global aerosol model (CAM5‐chem/ATRAS2) have reasonable agreements with various aerosol measurements
AAOD is enhanced or reduced regionally (5–50%) by improving the representation of optical and lifetime effects of BC mixing state
The complexity of aerosol representation (mixing state and composition) is important for simulations of BC, AAOD, and CCN concentrations
THE COMMUNITY EARTH SYSTEM MODEL Hurrell, James W.; Holland, M. M.; Gent, P. R. ...
Bulletin of the American Meteorological Society,
09/2013, Letnik:
94, Številka:
9
Journal Article
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The Community Earth System Model (CESM) is a flexible and extensible community tool used to investigate a diverse set of Earth system interactions across multiple time and space scales. This global ...coupled model significantly extends its predecessor, the Community Climate System Model, by incorporating new Earth system simulation capabilities. These comprise the ability to simulate biogeochemical cycles, including those of carbon and nitrogen, a variety of atmospheric chemistry options, the Greenland Ice Sheet, and an atmosphere that extends to the lower thermosphere. These and other new model capabilities are enabling investigations into a wide range of pressing scientific questions, providing new foresight into possible future climates and increasing our collective knowledge about the behavior and interactions of the Earth system. Simulations with numerous configurations of the CESM have been provided to phase 5 of the Coupled Model Intercomparison Project (CMIP5) and are being analyzed by the broad community of scientists. Additionally, the model source code and associated documentation are freely available to the scientific community to use for Earth system studies, making it a true community tool. This article describes this Earth system model and its various possible configurations, and highlights a number of its scientific capabilities.
Landscape fires during the 21st century are expected to change in response to multiple agents of global change. Important controlling factors include climate controls on the length and intensity of ...the fire season, fuel availability, and fire management, which are already anthropogenically perturbed today and are predicted to change further in the future. An improved understanding of future fires will contribute to an improved ability to project future anthropogenic climate change, as changes in fire activity will in turn impact climate. In the present study we used a coupled-carbon-fire model to investigate how changes in climate, demography, and land use may alter fire emissions. We used climate projections following the SRES A1B scenario from two different climate models (ECHAM5/MPI-OM and CCSM) and changes in population. Land use and harvest rates were prescribed according to the RCP 45 scenario. In response to the combined effect of all these drivers, our model estimated, depending on our choice of climate projection, an increase in future (2075-2099) fire carbon emissions by 17 and 62% compared to present day (1985-2009). The largest increase in fire emissions was predicted for Southern Hemisphere South America for both climate projections. For Northern Hemisphere Africa, a region that contributed significantly to the global total fire carbon emissions, the response varied between a decrease and an increase depending on the climate projection. We disentangled the contribution of the single forcing factors to the overall response by conducting an additional set of simulations in which each factor was individually held constant at pre-industrial levels. The two different projections of future climate change evaluated in this study led to increases in global fire carbon emissions by 22% (CCSM) and 66% (ECHAM5/MPI-OM). The RCP 45 projection of harvest and land use led to a decrease in fire carbon emissions by -5%. The RCP 26 and RCP 60 harvest and landuse projections caused decreases around -20%. Changes in human ignition led to an increase of 20%. When we also included changes in fire management efforts to suppress fires in densely populated areas, global fire carbon emission decreased by -6% in response to changes in population density. We concluded from this study that changes in fire emissions in the future are controlled by multiple interacting factors. Although changes in climate led to an increase in future fire emissions this could be globally counterbalanced by coupled changes in land use, harvest, and demography.
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