Cristin-resultat-ID: 2025633
Sist endret: 3. juni 2022, 16:43
NVI-rapporteringsår: 2022
Resultat
Vitenskapelig artikkel
2022

Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study

Bidragsytere:
  • Cynthia Whaley
  • Rashed Mahmood
  • Knut von Salzen
  • Barbara Winter
  • Sabine Eckhardt
  • Stephen R. Arnold
  • mfl.

Tidsskrift

Atmospheric Chemistry and Physics (ACP)
ISSN 1680-7316
e-ISSN 1680-7324
NVI-nivå 2

Om resultatet

Vitenskapelig artikkel
Publiseringsår: 2022
Publisert online: 2022
Volum: 22
Sider: 5775 - 5828
Open Access

Beskrivelse Beskrivelse

Tittel

Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study

Sammendrag

While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios. In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008–2009 and 2014–2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, seasonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH4, O3, BC, and SO), the mmm was within ±25 % of the measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs. Of the SLCFs in our study, model biases were smallest for CH4 and greatest for OA. For most SLCFs, model biases skewed from positive to negative with increasing latitude. Our analysis suggests that vertical mixing, long-range transport, deposition, and wildfires remain highly uncertain processes. These processes need better representation within atmospheric models to improve their simulation of SLCFs in the Arctic environment. As model development proceeds in these areas, we highly recommend that the vertical and 3-D distribution of SLCFs be evaluated, as that information is critical to improving the uncertain processes in models.

Bidragsytere

Cynthia Whaley

  • Tilknyttet:
    Forfatter
    ved Environnement et Changement climatique Canada

Rashed Mahmood

  • Tilknyttet:
    Forfatter
    ved Université de Montréal
  • Tilknyttet:
    Forfatter
    ved Centro Nacional de Supercomputación

Knut von Salzen

  • Tilknyttet:
    Forfatter
    ved Environnement et Changement climatique Canada

Barbara Winter

  • Tilknyttet:
    Forfatter
    ved Environnement et Changement climatique Canada

Sabine Eckhardt

  • Tilknyttet:
    Forfatter
    ved Atmosfære og klima ved NILU - Norsk institutt for luftforskning
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