Satellite assessment of sea spray aerosol productivity: Southern Ocean case study

Abstract

Despite many years of observations by multiple sensors, there is still substantial ambiguity regarding aerosol optical depths (AOD) over remote oceans, in particular, over the pristine Southern Ocean. Passive satellite retrievals (e.g., Multiangle Imaging Spectroradiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS)) and global aerosol transport models show a distinct AOD maximum around the 60°S latitude band. Sun photometer measurements performed by the Maritime Aerosol Network (MAN), on the other hand, indicate no increased AODs over the Southern Ocean. In this study elevated Southern Ocean AODs are examined from the modeling perspective. The primary aerosol component over the Southern Ocean is sea spray aerosol (SSA). Multiple simulations of SSA concentrations and optical depths are carried out using a single modeling framework, the Navy Aerosol Analysis and Prediction System (NAAPS) model. Several SSA emission functions are examined, including recently proposed formulations with sea surface temperature corrections. The differences between NAAPS simulations are primarily due to different SSA emission formulations. The results are compared against satellite‐derived AODs from the MISR and MODIS instruments. MISR and MODIS AOD retrievals are further filtered to eliminate retrievals potentially affected by cloud contamination and cloud adjacency effects. The results indicate a very large impact of SSA emission parameterization on the simulated AODs. For some scenarios, the Southern Ocean AOD maximum almost completely disappears. Further MISR and MODIS AOD quality screening substantially improves model/satellite agreement. Based on these comparisons, an optimal SSA emission function for global aerosol transport models is recommended.

Aerosol Optical Depth and Burden From Large Sea Salt Particles

“…There are well‐known positive biases in satellite‐based aerosol data sets over middle‐to‐high latitude oceans, including MODIS and Multi‐angle Imaging Spectro Radiometer. But as Multi‐angle Imaging Spectro Radiometer generally has a larger positive bias over oceans than MODIS when compared with other ground‐based data (Toth et al, ; Witek et al, ), we only use MODIS data in this study.…”

“…Generally, biases of satellite retrievals mainly result from signal uncertainty, algorithm bias, and cloud contamination (Kaufman et al, ; J. Zhang & Reid, ). As for the bias over middle‐to‐high latitude oceans where we are most interested in, cloud contamination is the main cause, and the bias between MODIS and ground‐based observation data significantly decreases as the cloud fraction decreases (Toth et al, ; Witek et al, ). In order to minimize the bias caused by possible cloud contamination on AOD, we introduce a screening procedure similar to that in Jaeglé et al () and Toth et al ().…”

Performance of MODIS C6 Aerosol Product during Frequent Haze-Fog Events: A Case Study of Beijing

“…The major method of validating MODIS data is through surface-deployed sun-photometers [52][53][54]. MODIS C5.1 aerosol products (mainly the 10 km DT product) have already been validated over China.…”

Introducing the 4.4 km spatial resolution Multi-Angle Imaging SpectroRadiometer (MISR) aerosol product

“…Most importantly, the efforts focused on mitigating the existence of a gap in retrieved AOD values below about 0.02. Tackling the quantization noise at low AOD mentioned in Kahn et al (2010) was only part of the solution; addressing the gap problem required identification and development of a method for correcting stray light in MISR cameras (Witek et al, 2018a). In addition, substantial work was devoted to reengineering the retrieval process to make the utilization of goodness-offit functions in DW processing less threshold dependent.…”