Abstract

Abstract. We combine in situ measurements of sea salt aerosols (SS) from open ocean cruises and ground-based stations together with aerosol optical depth (AOD) observations from MODIS and AERONET, and the GEOS-Chem global chemical transport model to provide new constraints on SS emissions over the world's oceans. We find that the GEOS-Chem model using the Gong (2003) source function overestimates cruise observations of coarse mode SS mass concentrations by factors of 2–3 at high wind speeds over the cold waters of the Southern, North Pacific and North Atlantic Oceans. Furthermore, the model systematically underestimates SS over the warm tropical waters of the Central Pacific, Atlantic, and Indian Oceans. This pattern is confirmed by SS measurements from a global network of 15 island and coastal stations. The model discrepancy at high wind speeds (>6 m s −1) has a clear dependence on sea surface temperature (SST). We use the cruise observations to derive an empirical SS source function depending on both wind speed and SST. Implementing this new source function in GEOS-Chem results in improved agreement with in situ observations, with a decrease in the model bias from +64% to +33% for the cruises and from +32% to −5% for the ground-based sites. We also show that the wind speed-SST source function significantly improves agreement with MODIS and AERONET AOD, and provides an explanation for the high AOD observed over the tropical oceans. With the wind speed-SST formulation, global SS emissions show a small decrease from 5200 Mg yr−1 to 4600 Mg yr−1, while the SS burden decreases from 9.1 to 8.5 mg m−2. The spatial distribution of SS, however, is greatly affected, with the SS burden increasing by 50% in the tropics and decreasing by 40% at mid- and high-latitudes. Our results imply a stronger than expected halogen source from SS in the tropical marine boundary layer. They also imply stronger radiative forcing of SS in the tropics and a larger response of SS emissions to climate change than previously thought.

Highlights

  • Sea salt aerosols (SS) are significant players in the climate and chemistry of the marine atmosphere

  • The sea surface temperature (SST) dependence is similar to the one we found when comparing GEOS-Chem to the Pacific Marine Environmental Laboratory (PMEL) cruise and ground-based observations, but the MODIS points tend to fall above the PMEL fit

  • We examine shipboard aerosol optical depth (AOD) observations collected as part of the Maritime Aerosol Network (AERONET-MAN), which is a component of Aerosol Robotic NETwork (AERONET)

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Summary

Introduction

Sea salt aerosols (SS) are significant players in the climate and chemistry of the marine atmosphere. Open ocean, and laboratory measurements of SS size distribution have been used as a basis to develop multiple parameterizations to express the production flux of SS and its dependence on wind speed, with often conflicting results (e.g., Monahan et al, 1986; Smith and Harrison, 1998; Andreas, 1998; Martensson et al, 2003; Clarke et al, 2006) Their use in CTMs leads to factors of 2–3 differences in calculated SS concentrations (e.g., Guelle et al, 2001; Pierce and Adams, 2006). Similar sampling protocols were used for all these shipboard measurements (including using a stable reference RH) allowing for constant aerosol size segregations and helping eliminate biases in the data This dataset will provide the cornerstone of our analysis and together with the GEOS-Chem CTM will be used to derive a new empirical SS source function applicable over a wide range of environmental conditions.

The GEOS-Chem model
Sea salt simulation
Sea salt optical properties
Simulations conducted in this work
In situ observations of sea salt concentrations
AOD observations
Comparison between PMEL observations and GEOS-Chem
Dependence of sea salt emissions on u10 m
Dependence of sea salt emissions on SST
Performance of new SS source functions for PMEL cruises
Performance of new SS source functions for ground-based observations
MODIS Aqua AOD
AERONET AOD
New sea salt budget
Findings
Discussion
Summary and implications
Full Text
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