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Smaller desert dust cooling effect estimated from analysis of dust size and abundance (1710.07630v1)

Published 20 Oct 2017 in physics.ao-ph

Abstract: Desert dust aerosols affect Earth's global energy balance through direct interactions with radiation, and through indirect interactions with clouds and ecosystems. But the magnitudes of these effects are so uncertain that it remains unclear whether atmospheric dust has a net warming or cooling effect on global climate. Consequently, it is still uncertain whether large changes in atmospheric dust loading over the past century have slowed or accelerated anthropogenic climate change, or what the effects of potential future changes in dust loading will be. Here we present an analysis of the size and abundance of dust aerosols to constrain the direct radiative effect of dust. Using observational data on dust abundance, in situ measurements of dust optical properties and size distribution, and climate and atmospheric chemical transport model simulations of dust lifetime, we find that the dust found in the atmosphere is substantially coarser than represented in current global climate models. Since coarse dust warms climate, the global dust direct radiative effect is likely to be less cooling than the ~-0.4 W/m2 estimated by models in a current global aerosol model ensemble. Instead, we constrain the dust direct radiative effect to a range between -0.48 and +0.20 W/m2, which includes the possibility that dust causes a net warming of the planet.

Citations (330)

Summary

  • The paper refines the assessment of desert dust’s direct radiative effect by integrating revised size distributions with observational data.
  • The study reveals that climate models overestimate fine dust, leading to biased cooling estimates and suggesting a potential net warming effect.
  • The methodology combines in situ measurements with model simulations, emphasizing the significant impact of dust particle shape on radiation balance.

Assessment of the Cooling Effect of Desert Dust: A Reevaluation of Dust Particle Size and Abundance

The paper presented in this paper offers a refined assessment of the direct radiative effect (DRE) of desert dust aerosols on global climate by thoroughly evaluating the dust particle size distribution and atmospheric abundance. This investigation challenges the existing assumptions embedded in current global climate models and proposes a substantially divergent interpretation of the role of desert dust in climate dynamics.

Key Findings

The paper provides critical insights into discrepancies between observed atmospheric dust properties and their representation in global climate models. Specifically, the authors identify a key limitation: the prevailing models tend to simulate too much fine dust and not enough coarse dust. Consequently, this discrepancy leads to a bias in estimating the cooling effect of dust, which by scattering solar radiation primarily derives from fine dust. In contrast, coarse dust, associated with warming, tends to absorb solar and infrared radiation.

By utilizing observational data, in situ measurements, and climate model simulations, the authors have ascertained that:

  • Atmospheric dust is coarser than current models predict. The means of leveraging both global models and extensive observations permit an improved characterization of the dust size distribution.
  • The dust DRE likely ranges between -0.48 and +0.20 W/m², introducing the possibility of a net warming effect, contrary to earlier model estimates suggesting more pronounced cooling.
  • The common representation of dust particles as spherical entities results in an underestimation (~20–60%) of the extinction efficiency for particles with a diameter greater than 1 μm. Consequently, ignoring the aspherical shape of dust particles could mislead radiation balance estimates.

Methodological Rigor

The paper adopts an alternative analytical approach, using observational constraints to reinforce or correct model outcomes, thus offering a more reliable estimation of dust DRE. This method overcomes biases inherent to model simulations by anchoring assessments in experimental findings and observational data. The authors provide a statistical model to synthesize various data sets, which enhances the robustness of their conclusions regarding dust properties and prevalence.

Implications of Findings

This reevaluation holds significant implications for the understanding of aerosols in climate science:

  • Theoretical Implications: This research signifies the intricacies involved in accurately describing the atmospheric impact of desert dust. The refined dust size distribution model could improve the accuracy of simulated impacts on climate by correctly representing the balance between atmospheric cooling and warming.
  • Practical Implications: The paper underscores the need for refining climate models, particularly concerning dust parameters. Global policy may benefit from these refined models, adjusting climate mitigation strategies accordingly. The possibility that desert dust could be contributing less to cooling than anticipated, or indeed serving as a net warming agent, impacts projections and strategies concerning anthropogenic climate change.

Prospects for Future Research

The findings pave the way for further investigations into dust-related research, particularly focusing on:

  • The refinement of models to ensure that dust particle shapes and comprehensive size distributions are accurately captured.
  • Exploring the regional variability in dust DRE to ascertain source-specific impacts that can aid in focusing regional climate interventions.
  • Longitudinal assessment of dust impacts to include variables such as deposition schemes, aggregation effects and interactions with clouds and biogeochemical cycles.

In conclusion, the paper renders an indispensable contribution to the comprehension of dust's role in global climate dynamics. By aligning observational datasets with refined modeling frameworks, it both challenges and augments the current understanding of dust as a climate actor, emphasizing the necessity for continual methodological refinement and data integration.