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

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In the table below, 4.Equ means Equations and Algorithms, 5.Ver means Verification, 6.Perf - Performance, 7. Val - Validation

Equations: Document the equations that are being solved and describe algorithms
Verification Plans: Define tests that will be run to show that implementation is correct and robust. Involve unit tests to cover range of inputs as well as benchmarks.
Performance expectations: Explain the expected performance impact from this development
Validation Plans: Document what process-based, stand-alone component, and coupled model runs will be performed, and with what metrics will be used to assess validity

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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

Overview table for the owner and an approver of this feature

1.Description	New Improvements to Aerosols and Clouds
2.Owner	Hailong Wang
3.Created	11 Sep 2015
4.Equ
5.Ver
6.Perf
7.Val
8.Approver	Shaocheng Xie
9.Approved Date
V1.0	Accepted

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Table of Contents

Title: New Improvements to Aerosols and Clouds

Requirements and Design

ACME Atmosphere Group

Date: 11 Sep 2015

Summary

The goal of this task is to implement to the ACME V1 model newly improved treatments of aerosols, clouds and aerosol-cloud interactions, including

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)

References:

Neu, J. L. and Prather, M. J.: Toward a more physical representation of precipitation scavenging in global chemistry models: cloud overlap and ice physics and their impact on tropospheric ozone, Atmos. Chem. Phys., 12, 3289-3310, doi:10.5194/acp-12-3289-2012, 2012.

Shi, X., Liu, X., and Zhang, K.: Effects of pre-existing ice crystals on cirrus clouds and comparison between different ice nucleation parameterizations with the Community Atmosphere Model (CAM5), Atmos. Chem. Phys., 15, 1503-1520, doi:10.5194/acp-15-1503-2015, 2015.

Wan, H., Rasch, P. J., Zhang, K., Kazil, J., and Leung, L. R.: Numerical issues associated with compensating and competing processes in climate models: an example from ECHAM-HAM. Geosci. Model. Devel., 6, 861-874, 2013.

Wang, Y., Liu, X., Hoose, C., and Wang, B.: Different contact angle distributions for heterogeneous ice nucleation in the Community Atmospheric Model version 5, Atmos. Chem. Phys., 14, 10411-10430, doi:10.5194/acp-14-10411-2014, 2014.

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: 06 Oct 2015

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:29 Oct 2015

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: 06 Oct 2015

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: 06 Oct 2015
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: 06 Oct 2015
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.

Date last modified: 06 Oct 2015
Contributors: Hailong Wang, Richard Easter (Unlicensed), Kai Zhang, Balwinder Singh