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The Fast Response of Land Precipitation to Historical Anthropogenic Black Carbon and Sulfate Aerosols in the GFDL ESM4 Climate Model



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  • Journal Title:
    Journal of Climate
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    Aerosol effects on precipitation are crucial factors in climate change, yet they remain poorly understood, representing a large source of uncertainty in climate models. In the Geophysical Fluid Dynamics Laboratory (GFDL) Earth system model, version 4 (ESM4), simulated historical century-scale trends of global land precipitation demonstrate significant drying biases compared to observations, even when imposing observed historical variations of sea surface temperature and sea ice concentrations (LongAMIP simulations). These biases manifest as overestimated decreasing trends in precipitation over tropical–subtropical land and underestimated increases in higher latitudes. In this study, we investigate the “fast response” of land precipitation to historical anthropogenic aerosol emissions and its contributions to the model trend biases, by conducting idealized ESM4 LongAMIP experiments with emissions of either black carbon (BC) or sulfate (SO4) aerosol precursors set to near-preindustrial levels (1850). Local aerosol effects, occurring through alteration of atmospheric energy balance and circulation, emerge as critical drivers of excessive precipitation declines in the LongAMIP runs in some regions: 1) over East Asia, a negative SO4 effect and a positive BC effect contribute to the simulated negative trend bias in LongAMIP; 2) for regions of Africa, the negative fast response to BC and SO4 partially contributes to the overestimated precipitation decline; and 3) over west-central North America, the negative fast response to BC in the model contributes toward underestimating a modest observed increasing precipitation trend. However, over South Asia, eastern North America, and northwest Eurasia, the fast responses of precipitation to aerosols cannot account for the LongAMIP model bias (in the opposite direction), indicating the dominant influence of other factors.
  • Source:
    Journal of Climate, 38(10), 2395-2411
  • DOI:
  • ISSN:
    0894-8755 ; 1520-0442
  • Format:
    PDF
  • Publisher:
    American Meteorological Society
  • Document Type:
    Journal Article
  • Rights Information:
    Other
  • Compliance:
    Submitted
  • Main Document Checksum:
    urn:sha-512:44ac950934309400802696f9a78000997c1332101b72062f8abc4f993af20b62ba2bafde6d2044bb6a7e563de45b0302049fd1a6e46144384fa485771235eb63
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  • File Type:
    Filetype[PDF - 5.04 MB ]
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