Response of the climatic temperature to dust forcing, inferred from total ozone mapping spectrometer (TOMS) aerosol index and the NASA assimilation model

P. Alpert, J. Herman, Y. J. Kaufman, I. Carmona

Research output: Contribution to journalArticlepeer-review

Abstract

Recently, Alpert et al. (Alpert, P., Shay-El, Y., Kaufman, Y.J., Tanre, D., DaSilva, A., Schubert, S., Joseph, J.H., 1998. Quantification of dust-forced heating of the lower troposphere, Nature 395 (6700), 367-370, (24 September).) suggested an indirect measure of the tropospheric temperature response to dust aerosols by using model updates -roughly speaking model errors - of the NASA Goddard Earth Observing System version No. 1 (GEOS-1) data assimilation system. They have shown that these updates, which provide information about missing physical processes not included in the predictive model, have monthly mean patterns, which bear a striking similarity to patterns of dust over the Atlantic. This similarity in the number of dusty days was used to estimate the atmospheric response to dust. Here, the study is extended for all the major subtropical deserts over Africa and Asia using the total ozone mapping spectrometer (TOMS) aerosol index (AI) for dust recently derived by Herman et al. (Herman, J.R., Bhartia, P.K., Torres, O., Hsu, C., Seftor, C., Celarier, E., 1997. Global distribution of UV-absorbing aerosols from Nimbus 7/TOMS data, J. Geophys. Res. 102, 16911-16922.). It is shown that the TOMS dust is highly correlated with the model errors with a maximum at the altitude of about 580 hPa and for the month of June with average correlation coefficient of 0.69 reaching up to 0.8 for specific months. In contrast to the previous study where only dust over ocean was employed, here, much higher dust concentrations are detected and the linear heating for weak dust becomes quickly saturated for AI above 1.5, then drops for very high values of AI that exceed about 3. This result is consistent with the theoretical predictions.

Original languageEnglish
Pages (from-to)3-14
Number of pages12
JournalAtmospheric Research
Volume53
Issue number1-3
DOIs
StatePublished - 2000

Keywords

  • Climate change
  • Climate forcing
  • Data assimilation
  • Dust
  • Dust aerosols
  • Model errors
  • TOMS

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