Characterizing Variability of Marine Boundary Layer Using Global Field Campaign Data

Abstract:

The atmospheric boundary layer (ABL) is of critical importance as it not only connects all components of the Earth system from the atmosphere to the oceans, land, and ice, but also is where people live. However, our current ability of observing the 3D structure of the ABL globally from space is limited and remains as an unmet challenge. The marine ABL over the global oceans, covers about 75% of the Earth surface, are particularly difficult to observe. It interacts with the air-sea interface and affects momentum, heat, moisture, gas and particle exchanges, all of which have direct impact on global weather and climate. Although the last a few decades have seen a growth in our ability to sample the marine ABL in field campaigns, the vast majority of the marine ABL is data-sparse because of a lack of density in surface-based observations and because the marine ABL presents challenging conditions for satellite remote penetrating and its relatively shallow but complex vertical structure. The ABL parameterizations used in current global numerical weather prediction (NWP) and climate models were developed primarily based on observations over land, e.g., experiments in Kansas (LeMone et al, 2019), which are not representative over the ocean. The models are often biased in representing the marine ABL compared with some field campaign observations.

This study aims to 1) better understand and model ABL by developing an integrated marine ABL dataset, which will integrate observations from existing surface-based network (e.g., ships, moorings, small islands/atolls), selected satellite measurements relevant to the marine ABL properties, and field campaigns over the tropical, subtropical, and high-latitude oceans, as well as in the coastal environment where the marine ABL most acutely impacts humans and ecosystems, and 2) enable close collaborations between the Earth system modelling and observational communities to advance process-based model improvement studies using the marine ABL dataset. Initial results show that the marine ABL is highly variable over a wide range of temporal and spatial scales. The physical processes at the air-sea interface in various wind regimes and processes driving clouds at the top of the ABL are highly complex.