Overview

Overview#

IPTpy enables users to generate global anthropogenic emissions from Copernicus Atmosphere Monitoring Service (CAMS) or Community Emissions Data System (CEDS) inventories for the finite volume dynamic core (FV dycore) in Community Atmosphere Model (CAM), covering the most recent historical data. Compared to the original, IPTpy offers greater flexibility by allowing users to generate specific species and specify data on a monthly basis.

Emission#

The differences between IPT and IPTpy include the programming language, supported model dycores, inventory versions, and output method, as summarized in Table 1.

Table 1 Comparison between Input Processing Tools (IPT) and Python-based IPT (IPTpy).

Feature

IPT

IPTpy

Function

Processing anthropogenic and biomass emission for FV and spectral element (SE) dycores

Processing anthropogenic emissions for FV dycores

Programming language

NCAR Command Language (NCL)

Python

Supported global anthropogenic emission inventories

CAMS-GLOB-ANTv4.2[1], CEDSv2017_05_18

CAMS-GLOB-ANTv5.3 [2][3], CAMS-GLOB-ANTv6.1, CEDSv2021_04_21

Supported global biomass burning emission inventories

FINN, QFED

Not applicable

Species

Generates all species by default (no user selection)

Allows users to select specific species as needed

Period

Selected by year(s)

Selected by year(s) and months

  • While IPT-py does not yet replicate all IPT functionalities, contributions are welcome to enhance its capabilities further.

  • Emission data varies across versions.

    • For example, black carbon emissions exhibit notable differences between CAMS-GLOB-ANTv4.2 and CAMS-GLOB-ANTv5.3. On 1 January 2019, the relative difference \(\frac{\text{CAMS-GLOB-ANTv4.2} - \text{CAMS-GLOB-ANTv5.3}}{\text{CAMS-GLOB-ANTv5.3}} \times 100\%\) exceeds 100% (Figure 1a) or \(-\)100% (Figure 1b).


      diffFigure 1 Relative difference in black carbon between CAMS-GLOB-ANTv4.2 and CAMS-GLOB-ANTv5.3 on 1 January 2019.


    • CEDS releases have also introduced changes in history emissions. For details, refer to the CEDS release notes.

Acknowledgment#

This work used the ARCHER2 UK National Supercomputing Service and JASMIN, the UK’s collaborative data analysis environment.

Notes#