Biological and Environmental Research - Earth and Environmental System Sciences
Earth and Environmental System Modeling

Enabling Chemistry of Gases and Aerosols for Assessment of Short-Lived Climate Forcers: Improving Solar Radiation Modeling in the DOE-ACME and CESM models

In first year of funding.  Cloud-J has just been completed and Solar-J with link of UCI Fast-J to RRTMG-SW at 600 nm (bins 24 & 25) is now in testing.

Rapid mitigation of short-lived climate forcing agents (SLCFs: tropospheric O3, CH4, some HFCs, black carbon and other aerosols) has been promoted as a near-term solution to simultaneously slow global warming and improve air quality. Mitigation of these SLCFs is a core component of current international programs, including the US-initiated Climate and Clean Air Coalition, and also a subject at the 2013 UNFCCC Conference of the Parties. While mitigation efforts focus on emissions reductions, the atmospheric abundances of these climate forcing agents, once emitted, are determined primarily by atmospheric chemistry. Successful SLCF mitigation plans must have a detailed knowledge of the atmospheric chemistry and radiative properties today, and understand how processes will change with future climate and anthropogenic emissions. Such knowledge is realized in global chemistry-climate models (CCMs).

This proposal seeks to maintain the DOE-ACME as one of the leading CCMs to evaluate near-term climate mitigation. It will implement, test, and optimize the new UCI photolysis codes within CESM CAM5 and new CAM versions in ACME. Fast-J is a high-order-accuracy (8 stream) code for calculating solar scattering and absorption in a single column atmosphere containing clouds, aerosols, and gases that was developed at UCI and implemented in CAM5 under the previous BER/SciDAC grant. Task 1 will implement cloud-J, a wrapper for fast-J that accounts for sub-grid cloud scenes or multiple column atmospheres within a cell (e.g., from cloud resolving models). This work also will improve computational throughput by leveraging GPU capabilities to speed the core calculation of solving a (4x4) x ~200 block tri-diagonal system for each wavelength and each independent column atmosphere. The fast-J photolysis rates calculated using the clouds and aerosols generated by the model running historical meteorology will be tested against aircraft measurements. The spectrally resolved solar radiation field, both direct and diffuse, will be compared with observations from DOE ARM sites used to validate the rapid radiative transfer model (RRTM) used in CAM. With CAM running fast-J and full chemistry, additional novel diagnostics of chemical rates can be used to test CAM’s climatology, involving probability distributions of the more chemically reactive air parcels. Task 1 has a short time frame as DOE-ACME and CESM must be ready to start the chemistry-climate simulations for the next IPCC assessment by early 2016. Observational tests of cloud-J will continue after this first deadline.

Cloud-J will be expanded (at no additional computational cost) to provide a more accurate representation of PAR, including diffuse and direct components, with a more realistic response to aerosols, including geo-engineered stratospheric aerosols (Task 2). A high-risk venture (Task 3) is the extension of cloud-J to a multi-angle-scattering, solar-heating code that could provide an alternative, more realistic calculation of the aerosol radiative effects than the current solar code in CAM5 (RRTMG-SW). RRTMG uses approximations that require unphysical representation of cloud and aerosol scattering functions with known systematic errors; these are not needed in cloud-J. The risk in expanding cloud-J beyond its design range (the photolysis region 180-850 nm) to the full solar spectrum (180-5000 nm) is that some of the current computational efficiency may be lost. The payoff for DOE climate modeling is high – a faster, internally consistent, interactive solar radiation code for atmospheric chemistry, land-surface modeling, and atmospheric heating rates.

Project Term: 
2014 to 2017
Project Type: 
University Project