Pollution and dust aerosols modulating tropical cyclones intensities

Daniel Rosenfeld*, Michal Clavner, Ronit Nirel

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

42 Scopus citations

Abstract

Tropical cyclones (TC) are propelled mostly by realization of latent heat that is stored in vapor coming off warm sea surfaces. The heating occurs when the vapor condenses into cloud drops. Re-evaporation of the cloud water takes back the released heat, whereas precipitation of the water as rain fixates the heat in the air. Therefore, it is expected that TC intensities would be sensitive to precipitation forming processes that affect the amount and distribution of latent heat release. This has been simulated by numerical models, which showed that cloud condensation nuclei (CCN) aerosols weaken the storms apparently by slowing the conversion of cloud drops into precipitation. If so, we should expect that storm predictions that do not take this aerosol effect into account would over-predict TC intensities. Here we show that increased aerosols quantities in a TC periphery can explain about 8% of the forecast errors of the TC. Indeed, actual intensities of polluted TCs were found to be on average lower than their predicted values, providing supporting observational evidence to the hypothesis. It was also found that TC intensity might be more susceptible to the impacts of aerosols during their developing stages and less in the TC mature and dissipating stages.

Original languageEnglish
Pages (from-to)66-76
Number of pages11
JournalAtmospheric Research
Volume102
Issue number1-2
DOIs
StatePublished - Oct 2011

Bibliographical note

Funding Information:
This study was funded by the Hurricane Aerosol and Microphysics Program (HAMP) of the US Department of Homeland Security . The authors thank Dr. Albert Arking for constructive discussions and Dr. Mian Chin for her very helpful advice regarding the GOCART model.

Keywords

  • Cloud seeding
  • Cloud-aerosols
  • Hurricane mitigation
  • Hurricane prediction
  • Tropical cyclone

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