3 research outputs found
The Climate Response to Emissions Reductions Due to COVID‐19: Initial Results From CovidMIP
Many nations responded to the corona virus disease-2019 (COVID-19) pandemic by restricting travel and other activities during 2020, resulting in temporarily reduced emissions of CO2, other greenhouse gases and ozone and aerosol precursors. We present the initial results from a coordinated Intercomparison, CovidMIP, of Earth system model simulations which assess the impact on climate of these emissions reductions. 12 models performed multiple initial-condition ensembles to produce over 300 simulations spanning both initial condition and model structural uncertainty. We find model consensus on reduced aerosol amounts (particularly over southern and eastern Asia) and associated increases in surface shortwave radiation levels. However, any impact on near-surface temperature or rainfall during 2020–2024 is extremely small and is not detectable in this initial analysis. Regional analyses on a finer scale, and closer attention to extremes (especially linked to changes in atmospheric composition and air quality) are required to test the impact of COVID-19-related emission reductions on near-term climate. © 2021. Crown Copyright. © 2021. Her Majesty the Queen in Right of Canada. This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland. Reproduced with the permission of the Minister of Environment and Climate Change Canada. This article has been contributed to by US Government employees and their work is in the public domain in the USA
Current model capabilities for simulating black carbon and sulfate concentrations in the Arctic atmosphere: a multi-model evaluation using a comprehensive measurement data set
The concentrations of sulfate, black carbon (BC)
and other aerosols in the Arctic are characterized by high values
in late winter and spring (so-called Arctic Haze) and low
values in summer. Models have long been struggling to capture
this seasonality and especially the high concentrations
associated with Arctic Haze. In this study, we evaluate sulfate
and BC concentrations from eleven different models driven
with the same emission inventory against a comprehensive
pan-Arctic measurement data set over a time period of 2
years (2008–2009). The set of models consisted of one Lagrangian
particle dispersion model, four chemistry transport
models (CTMs), one atmospheric chemistry-weather forecast
model and five chemistry climate models (CCMs), of
which two were nudged to meteorological analyses and three
were running freely. The measurement data set consisted of
surface measurements of equivalent BC (eBC) from five stations
(Alert, Barrow, Pallas, Tiksi and Zeppelin), elemental
carbon (EC) from Station Nord and Alert and aircraft measurements
of refractory BC (rBC) from six different campaigns.
We find that the models generally captured the measured
eBC or rBC and sulfate concentrations quite well, compared
to previous comparisons. However, the aerosol seasonality
at the surface is still too weak in most models. Concentrations
of eBC and sulfate averaged over three surface
sites are underestimated in winter/spring in all but one model
(model means for January–March underestimated by 59 and
37% for BC and sulfate, respectively), whereas concentrations
in summer are overestimated in the model mean (by
88 and 44% for July–September), but with overestimates
as well as underestimates present in individual models. The
most pronounced eBC underestimates, not included in the
above multi-site average, are found for the station Tiksi in
Siberia where the measured annual mean eBC concentration
is 3 times higher than the average annual mean for all other
stations. This suggests an underestimate of BC sources in
Russia in the emission inventory used. Based on the campaign
data, biomass burning was identified as another cause
of the modeling problems. For sulfate, very large differences
were found in the model ensemble, with an apparent anticorrelation
between modeled surface concentrations and total
atmospheric columns. There is a strong correlation between
observed sulfate and eBC concentrations with consistent
sulfate/eBC slopes found for all Arctic stations, indicating
that the sources contributing to sulfate and BC are
similar throughout the Arctic and that the aerosols are internally
mixed and undergo similar removal. However, only
three models reproduced this finding, whereas sulfate and
BC are weakly correlated in the other models. Overall, no
class of models (e.g., CTMs, CCMs) performed better than
the others and differences are independent of model resolution
Tropospheric ozone changes, radiative forcing and attribution to emissions in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP)
Ozone (O3) from 17 atmospheric chemistry models taking part in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) has been used to calculate tropospheric ozone radiative forcings (RFs). All models applied a common set of anthropogenic emissions, which are better constrained for the present-day than the past. Future anthropogenic emissions follow the four Representative Concentration Pathway (RCP) scenarios, which define a relatively narrow range of possible air pollution emissions. We calculate a value for the pre-industrial (1750) to present-day (2010) tropospheric ozone RF of 410mWm−2. The model range of pre-industrial to present-day changes in O3 produces a spread (±1 standard deviation) in RFs of ±17 %. Three different radiation schemes were used – we find differences in RFs between schemes (for the same ozone fields) of ±10 %. Applying two different tropopause definitions gives differences in RFs of ±3 %. Given additional (unquantified) uncertainties associated with emissions, climate-chemistry interactions and land-use change, we estimate an overall uncertainty of ±30% for the tropospheric ozone RF. Experiments carried out by a subset of six models attribute tropospheric ozone RF to increased emissions of methane (44±12 %), nitrogen oxides (31±9 %), carbon monoxide (15±3 %) and non-methane volatile organic compounds (9±2 %); earlier studies attributed more of the tropospheric ozone RF to methane and less to nitrogen oxides. Normalising RFs to changes in tropospheric column ozone, we find a global mean normalised RF of 42mWm−2 DU−1, a value similar to previous work. Using normalised RFs and future tropospheric column ozone projections we calculate future tropospheric ozone RFs (mWm−2; relative to 1750) for the four future scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) of 350, 420, 370 and 460 (in 2030), and 200, 300, 280 and 600 (in 2100). Models show some coherent responses of ozone to climate change: decreases in the tropical lower troposphere, associated with increases in water vapour; and increases in the sub-tropical to mid-latitude upper troposphere, associated with increases in lightning and stratosphere-to-troposphere transport. Climate change has relatively small impacts on global mean tropospheric ozone RF