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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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The first table in Design Document gives overview of this document, from this info the Design Documents Overview page is automatically created.

In the overview 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

Use the symbols below (copy and paste) to indicate if the section is in progress or done or not started.

In the table below 4.Equ means Equations and Algorithms, 5.Ver means Verification, 6.Perf - Performance, 7. Val - Validation,   (tick) - competed, (warning) - in progress, (error) - not done


Overview table for the owner and an approver of this feature

1.Description

Improved Dust Aerosol Physics

2.Owner

Yan Feng

3.Created 
4.Equ
5.Ver
6.Perf
7.Val
8.Approver
 
9.Approved Date
V2.0Pending
V1.0 Declined
 Click here for Table of Contents ...

Table of Contents




Title: NA1: Improved Dust Aerosol Physics

Requirements and Design

NGD Atmosphere

Date:    2019-05-03

Summary


Dust aerosols play an important role in Earth's energy balance and atmospheric interactions with biogeochemical cycles. It is critical to quantify dust life cycle and radiative effects in the coupled E3SM. The development and evaluation of dust representation in the V1 model have mainly focused on the global constraint of the dust optical depth (AOD) with observational estimates. However,  further analysis of the dust model simulations with V1 suggested that the dust shortwave (SW) absorption is too strong compared with observations and other GCMs. While the direct radiative effect of dust at the top atmosphere is constrained to a large extent by AOD, the heating effect of dust in the atmosphere is overestimated. This could lead to changes of the lower troposphere thermostructure and the subsequent cloud and precipitation changes.
The second issue identified is with the dust size distribution at emission used in the model, which leads to over-predicted fine-mode (<1 um) dust particles in the atmosphere as shown by Kok et al. (2017). As a result, the overall cooling effect by dust at TOA may be over-estimated. In addition, increasing model vertical resolution from 30 vertical layers to 72 layers has led to an over-deposition of dust in source regions and less long-range transport. Despite the global AOD is constrained by increasing global dust emissions by nearly a factor of 2, dust layer height is low-biased compared to observations, and the lifetime of dust is less than 2 days.
Therefore, the following dust updates proposed for V2 will address these issues identified. First, we will update the dust refractive index in the SW with the AERONET (obs)-derived values from the OPAC data (Hess, 1998) that is used in the default configuration. Second, we will update the fractional dust emission fluxes in accumulation and coarse modes, calculated with the size distribution by Kok (2011). With these updates implemented, dust emissions need to be re-tuned for the globally constrained AOD.
To fundamentally address the over-deposition bias in dust, it requires some surgical change in the code - the aerosol turbulence transport term needs to be moved from CLUBB and add to the aerosol emission/deposition equation. This issue might also need affect other aerosols and water vapor, which probably requires extensive model evaluation. In view of the timeline for the V2, a simple fix is proposed. We will implement an alternative option that distribute dust evenly in the PBL, instead of the lowest model layer. As insufficient dust transport is common in large-scale models for various reasons, similar approaches have been adopted in other modeling studies to enhance the dust vertical transport. We propose to implement this simple fix as an option in the namelist so that we will have a short-term solution, while we are working on a more physically-based solution.

Requirements

Requirement: (1) update namelist options in the default compset; (2) update dust fractional emissions; (3) update dust emission layers


Date last modified: 2019-05-13
Contributors: Yan Feng

The first two updates have been implemented and tested in V1. The third update is implemented and tests are not completed.



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Algorithmic Formulations, and Design Implementation


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Planned Verification and Unit Testing 

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Planned Validation Testing 

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Planned Performance Testing 

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