Threefold reduction of modeled uncertainty in direct radiative effects over biomass burning regions by constraining absorbing aerosols.

Absorbing aerosols emitted from biomass burning (BB) greatly affect the radiation balance, cloudiness, and circulation over tropical regions. Assessments of these impacts rely heavily on the modeled aerosol absorption from poorly constrained global models and thus exhibit large uncertainties. By combining the AeroCom model ensemble with satellite and in situ observations, we provide constraints on the aerosol absorption optical depth (AAOD) over the Amazon and Africa. Our approach enables identification of error contributions from emission, lifetime, and MAC (mass absorption coefficient) per model, with MAC and emission dominating the AAOD errors over Amazon and Africa, respectively. In addition to primary emissions, our analysis suggests substantial formation of secondary organic aerosols over the Amazon but not over Africa. Furthermore, we find that differences in direct aerosol radiative effects between models decrease by threefold over the BB source and outflow regions after correcting the identified errors. This highlights the potential to greatly reduce the uncertainty in the most uncertain radiative forcing agent.

Using modelled relationships and satellite observations to attribute modelled aerosol biases over biomass burning regions.

Biomass burning (BB) is a major source of aerosols that remain the most uncertain components of the global radiative forcing. Current global models have great difficulty matching observed aerosol optical depth (AOD) over BB regions. A common solution to address modelled AOD biases is scaling BB emissions. Using the relationship from an ensemble of aerosol models and satellite observations, we show that the bias in aerosol modelling results primarily from incorrect lifetimes and underestimated mass extinction coefficients. In turn, these biases seem to be related to incorrect precipitation and underestimated particle sizes. We further show that boosting BB emissions to correct AOD biases over the source region causes an overestimation of AOD in the outflow from Africa by 48%, leading to a double warming effect compared with when biases are simultaneously addressed for both aforementioned factors. Such deviations are particularly concerning in a warming future with increasing emissions from fires.

Black carbon and dust alter the response of mountain snow cover under climate change.

By darkening the snow surface, mineral dust and black carbon (BC) deposition enhances snowmelt and triggers numerous feedbacks. Assessments of their long-term impact at the regional scale are still largely missing despite the environmental and socio-economic implications of snow cover changes. Here we show, using numerical simulations, that dust and BC deposition advanced snowmelt by 17 ± 6 days on average in the French Alps and the Pyrenees over the 1979-2018 period. BC and dust also advanced by 10-15 days the peak melt water runoff, a substantial effect on the timing of water resources availability. We also demonstrate that the decrease in BC deposition since the 1980s moderates the impact of current warming on snow cover decline. Hence, accounting for changes in light-absorbing particles deposition is required to improve the accuracy of snow cover reanalyses and climate projections, that are crucial for better understanding the past and future evolution of mountain social-ecological systems.

Assessing the Influence of COVID-19 on the Shortwave Radiative Fluxes Over the East Asian Marginal Seas.

The Coronavirus Disease 2019 (COVID-19) pandemic led to a widespread reduction in aerosol emissions. Using satellite observations and climate model simulations, we study the underlying mechanisms of the large decreases in solar clear-sky reflection (3.8 W m-2 or 7%) and aerosol optical depth (0.16 W m-2 or 32%) observed over the East Asian Marginal Seas in March 2020. By separating the impacts from meteorology and emissions in the model simulations, we find that about one-third of the clear-sky anomalies can be attributed to pandemic-related emission reductions, and the rest to weather variability and long-term emission trends. The model is skillful at reproducing the observed interannual variations in solar all-sky reflection, but no COVID-19 signal is discerned. The current observational and modeling capabilities will be critical for monitoring, understanding, and predicting the radiative forcing and climate impacts of the ongoing crisis.

Projection of American dustiness in the late 21st century due to climate change.

Climate models project rising drought risks over the southwestern and central U.S. in the twenty-first century due to increasing greenhouse gases. The projected drier regions largely overlay the major dust sources in the United States. However, whether dust activity in U.S. will increase in the future is not clear, due to the large uncertainty in dust modeling. This study found that changes of dust activity in the U.S. in the recent decade are largely associated with the variations of precipitation, soil bareness, and surface winds speed. Using multi-model output under the Representative Concentration Pathways 8.5 scenario, we project that climate change will increase dust activity in the southern Great Plains from spring to fall in the late half of the twenty-first century - largely due to reduced precipitation, enhanced land surface bareness, and increased surface wind speed. Over the northern Great Plains, less dusty days are expected in spring due to increased precipitation and reduced bareness. Given the large negative economic and societal consequences of severe dust storms, this study complements the multi-model projection on future dust variations and may help improve risk management and resource planning.

Development of High-Resolution Dynamic Dust Source Function -A Case Study with a Strong Dust Storm in a Regional Model.

A high-resolution dynamic dust source has been developed in the NASA Unified-Weather Research and Forecasting (NU-WRF) model to improve the existing coarse static dust source. In the new dust source map, topographic depression is in 1-km resolution and surface bareness is derived using the Normalized Difference Vegetation Index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS). The new dust source better resolves the complex topographic distribution over the Western United States where its magnitude is higher than the existing, coarser resolution static source. A case study is conducted with an extreme dust storm that occurred in Phoenix, Arizona in 02-03 UTC July 6, 2011. The NU-WRF model with the new high-resolution dynamic dust source is able to successfully capture the dust storm, which was not achieved with the old source identification. However the case study also reveals several challenges in reproducing the time evolution of the short-lived, extreme dust storm events.

Global air quality and climate.

Emissions of air pollutants and their precursors determine regional air quality and can alter climate. Climate change can perturb the long-range transport, chemical processing, and local meteorology that influence air pollution. We review the implications of projected changes in methane (CH(4)), ozone precursors (O(3)), and aerosols for climate (expressed in terms of the radiative forcing metric or changes in global surface temperature) and hemispheric-to-continental scale air quality. Reducing the O(3) precursor CH(4) would slow near-term warming by decreasing both CH(4) and tropospheric O(3). Uncertainty remains as to the net climate forcing from anthropogenic nitrogen oxide (NO(x)) emissions, which increase tropospheric O(3) (warming) but also increase aerosols and decrease CH(4) (both cooling). Anthropogenic emissions of carbon monoxide (CO) and non-CH(4) volatile organic compounds (NMVOC) warm by increasing both O(3) and CH(4). Radiative impacts from secondary organic aerosols (SOA) are poorly understood. Black carbon emission controls, by reducing the absorption of sunlight in the atmosphere and on snow and ice, have the potential to slow near-term warming, but uncertainties in coincident emissions of reflective (cooling) aerosols and poorly constrained cloud indirect effects confound robust estimates of net climate impacts. Reducing sulfate and nitrate aerosols would improve air quality and lessen interference with the hydrologic cycle, but lead to warming. A holistic and balanced view is thus needed to assess how air pollution controls influence climate; a first step towards this goal involves estimating net climate impacts from individual emission sectors. Modeling and observational analyses suggest a warming climate degrades air quality (increasing surface O(3) and particulate matter) in many populated regions, including during pollution episodes. Prior Intergovernmental Panel on Climate Change (IPCC) scenarios (SRES) allowed unconstrained growth, whereas the Representative Concentration Pathway (RCP) scenarios assume uniformly an aggressive reduction, of air pollutant emissions. New estimates from the current generation of chemistry-climate models with RCP emissions thus project improved air quality over the next century relative to those using the IPCC SRES scenarios. These two sets of projections likely bracket possible futures. We find that uncertainty in emission-driven changes in air quality is generally greater than uncertainty in climate-driven changes. Confidence in air quality projections is limited by the reliability of anthropogenic emission trajectories and the uncertainties in regional climate responses, feedbacks with the terrestrial biosphere, and oxidation pathways affecting O(3) and SOA.