A8 Improvements to Aerosols and Clouds Design Document
The Design Document page provides a description of the algorithms, implementation and planned testing including unit, verification, validation and performance testing. Please read Step 1.3 Performance Expectations that explains feature documentation requirements from the performance group point of view.
Design Document
In the table below, 4.Equ means Equations and Algorithms, 5.Ver means Verification, 6.Perf - Performance, 7. Val - Validation, - completed, - in progress, - not done
Title: New Improvements to Aerosols and Clouds
Requirements and Design
ACME Atmosphere Group
Date:
Summary
- Improved treatment of aerosol resuspension from drop evaporation. (RESUSP_TO_COARSE)
- Improved treatment of H2SO4 vapor fro new particle formation. (H2SO4_TIME_SPLIT)
- New treatment of trace gas removal and SO2 solubility. (GAS_WET_REMOVE)
- New treatment of sub-grid vertical velocity for ice nucleation (WSUB)
- Parameterization of the impact of pre-existing ice crystals on ice nucleation in cirrus clouds (PREICE)
- Classical-nucleation-theory based parameterization for mixed-phase clouds (CNT)
- New treatment of ice crystal to snow conversion (DCS)
Requirements
- RESUSP_TO_COARSE: the aerosol wet-scavenging modules are revised to use a more physically-based treatment in which all aerosol material is released to the coarse mode as relatively large particles. This requires a modest increase in the number of transported aerosol species (i.e., coarse-mode BC, POA and SOA)
H2SO4_TIME_SPLIT: modify the MAM treatment of H2SO4 vapor production and loss to use a parallel time-split approach, instead of a serial time-split approach.
- GAS_WET_REMOVE: Implement a new treatment of trace gas removal
- WSUB: implement a new sub-grid parameterization of the characteristic updraft velocity, assuming a Gaussian distribution for the sub-grid variation of vertical velocities.
- PREICE: modify the ice nucleation scheme to consider the impact of pre-existing ice crystals
- CNT: add a classical-nucleation-theory based parameterization for mixed-phase clouds
- DCS: add a temperature dependent threshold size for auto conversion of cloud ice to snow
Date last modified:
Contributors: Hailong Wang, Richard Easter (Unlicensed), Kai Zhang, Balwinder Singh
Each requirement is to be listed under a ”section” heading, as there will be a one-to-one correspondence between requirements, design, proposed imple- mentation and testing. Requirements should not discuss technical software issues, but rather focus on model capability. To the extent possible, require- ments should be relatively independent of each other, thus allowing a clean design solution, implementation and testing plan.
Algorithmic Formulations
- For RESUSP_TO_COARSE, to be documented.
- For H2SO4_TIME_SPLIT, to be documented.
- For GAS_WET_REMOVE, see Neu and Prather (2012)
- For PREICE, see Shi et al. (2015)
- For CNT, see Wang et al. (2014)
- For WSUB, see this page.
- For DCS, see this page.
Date last modified:
Contributors: Hailong Wang, Richard Easter (Unlicensed), Kai Zhang, Balwinder Singh
Design and Implementation
Implementation:
Code design/implementation for all the sub-tasks, except for GAS_WET_REMOVE that will follow an initial implementation to CESM, has been done in separate ACME branches. Closely related implementations will be grouped together for testing and pull request.
Date last modified:
Contributors: Hailong Wang, Richard Easter (Unlicensed), Kai Zhang, Balwinder Singh
Planned Verification and Unit Testing
Verification and Unit Testing:
We will run tests to verify that the B4B with default model is maintained and results of the new implementation is consistent with our expectations based on the physics and/or with those in the published studies (see references above).
Date last modified:
Contributors: Hailong Wang, Richard Easter (Unlicensed), Kai Zhang, Balwinder Singh
Planned Validation Testing
Validation Testing:
Results of the ACME model with the new implementations will be validated against those in the published studies (see references above). As documented in our progress reports, for some of the sub-tasks results have been evaluated against in-situ measurements at fixed stations and/or in field campaigns, as well as satellite and ground-based remote sensing data.
Date last modified:
Contributors: Hailong Wang, Richard Easter (Unlicensed), Kai Zhang, Balwinder Singh
Planned Performance Testing
Performance Testing:
Except for the RESUSP_TO_COARSE sub-task, in which three additional tracers will increase computational cost by less than 10%, the new implementations are not expected to have significant impact on the computational performance, but we will work with the performance team to get the new implementations in ACME fully tested.