Date of Award

1-1-2023

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School/Department

Department of Atmospheric and Environmental Sciences

Content Description

1 online resource (xvi, 97 pages) : illustrations (some color), color maps.

Dissertation/Thesis Chair

Cheng-Hsuan Lu

Committee Members

Ryan Torn, Fangqun Yu, Liming Zhou

Keywords

Aerosol, Data Assimilation, Infrared Radiance, Numerical Weather Prediction, Atmospheric aerosols, Infrared radiation, Numerical weather forecasting, Weather forecasting

Subject Categories

Meteorology

Abstract

Aerosol radiative effects, both direct and indirect, have been extensively studied in climate projection and numerical weather prediction. However, the aerosol impacts on radiance in the context of data assimilation (DA) have received less research attention. In modern DA systems, thermal infrared (IR) radiance observations have been extensively assimilated since the mid-1990s. Prior studies have shown pronounced reduction of brightness temperature (BT) at the IR window region due to the presence of aerosols. Despite its effects on IR radiance, aerosol information is not considered in most DA systems.Without considering the aerosol impacts on radiance, the representation errors arise from the inconsistent aerosol representations among the numerical model, radiance simulations, and observations, especially over aerosol-laden regions. To constrain the effects of aerosols in DA systems, a common approach is to reject the observations with aerosol contamination. Alternatively, this dissertation introduces an aerosol-aware framework to assimilate aerosol-affected (i.e., hazy-sky) IR observations, so-called hazy-sky IR radiance DA. It extends the current assimilated dataset (clear-sky only) to include the hazy-sky observations instead of rejecting them. The overarching goal of this PhD research is to advance IR radiance DA by enhancing the use of hazy-sky observations. To accomplish it, two phases were conducted in this dissertation. First, the aerosol impacts on the radiance simulation and the analysis from the clear-sky framework were investigated. Second, an aerosol-aware framework including the observation processing and error characterization for hazy-sky IR observations was developed. Overall, dust aerosols result in the strongest cooling effects of BTs during IR window region compared to other aerosol types. Warmer first-guess departures were produced due to the cooler BTs and then assimilated. Consequently, the hazy-sky IR radiance DA provides warmer analyzed temperatures at surface and lower atmosphere. It also induces displacement to horizontal wind over the Tropic. In synoptic scale, it shows neutral results compared to baseline. Promisingly, it shows a better agreement with sea surface temperature measurements during episodic dust transport given a limited amount of assimilated hazy-sky IR data. Future work is needed to further enhance the quality control and the bias correction of the aerosol-aware framework.

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