Investigations of scalar transfer coefficients in fog during the Coupled Boundary Layers and Air Sea Transfer experiment : a case study

Abstract

The uncertainty in the determination of the momentum and scalar fluxes remains one of the main obstacles to accurate numerical forecasts in low to moderate wind conditions. For example, latent heat fluxes computed from data using direct covariance and bulk aerodynamic methods show that there is good agreement in unstable conditions when the latent heat flux values are generally positive. However, the agreement is relatively poor in stable conditions, particularly when the moisture flux is directed downward. If the direct covariance measurements are indeed accurate, then they clearly indicate that the bulk aerodynamic formula overestimate the downward moisture flux in stable conditions. As a result, comparisons of the Dalton number for unstable and stable conditions indicate a marked difference in value between the two stability regimes. Investigations done for this thesis used data taken primarily at the Air-Sea Interaction Tower (ASIT) during the Coupled Boundary Layers and Air-Sea Transfer (CBLAST) Experiment 2003 from the 20-27 August 2003. Other data from the shore based Martha's Vineyard Coastal Observatory (MVCO) and moored buoys in the vicinity of the ASIT were also incorporated.

(cont.) During this eight day period, the boundary layer was often characterized by light winds, a stably stratified surface layer and a swell dominated wave field. Additionally, the advection of warm moist air over cooler water resulted in fog formation and a downward flux of moisture on at least three occasions. Therefore, a primary objective of this thesis is to present a case study to investigate the cause of this shortcoming in the bulk formula under these conditions by examining the physical processes that are unique to these boundary layers. Particular attention will be paid to the behavior of the Dalton number in a stable marine atmospheric boundary layer under foggy conditions using insights derived from the study of fog formation and current flux parameterization methods.