ATSC5370 Satellite Remote Sensing

Overview

On April 1st, 1960, the Television Infrared Observation Satellite (TIROS)-1, the very first weather satellite, was launched by the United States (Fig. 1), marking the birth of “Satellite Remote Sensing” as a tool for meteorological and atmospheric science research. Since then, enormous effort has been devoted to the technological and theoretical developments of satellite remote sensing for many decades by integrating interdisciplinary knowledge (e.g., electrodynamics, radiative transfer, quantum mechanics, etc.) that was originally founded on physics. Nowadays, satellite remote sensing plays a pivotal role in atmospheric science and climate research by providing long-term datasets of various atmospheric properties on regional and global scales. Needless to say, satellite remote sensing products have been extensively used for students’ thesis/dissertation projects in atmospheric science and, more broadly, Earth-system science. However, it is also increasingly noticeable that remote sensing methods have become more like a “black box” for users for many reasons. What method is used in the satellite-derived atmospheric product? Does this product involve potential biases/uncertainties? What is the underlying physical assumption for these properties retrieved from satellite measurements?  The purpose of this course is to provide you with advanced knowledge of satellite remote sensing methods for cloud, precipitation, aerosol, atmospheric gas, and meteorological property retrievals. I will particularly try hard to focus more on the physical concepts behind the remote sensing methods rather than the mathematical and algorithmic aspects of them.

Objectives

This course introduces the physical principles of atmospheric remote sensing, with a breadth of applications in passive and active remote sensing of the atmosphere. Offers a solid understanding of remote sensing instrumentation and retrieval approaches for a variety of atmospheric parameters such as clouds, aerosols, precipitations, atmospheric gases, and meteorological characteristics.  

Goals

The goal of this course is for the students to understand the physical principles of satellite remote sensing as the application of atmospheric radiation and Bayesian statistics and to be able to discuss the retrieval accuracies and limitations of individual methods of satellite remote sensing from a physics perspective.

Student Learning Outcomes: The students will be able to

• Understand the physical principle of satellite remote sensing to infer atmospheric properties (e.g., clouds, aerosols, and atmospheric gases).

• Demonstrate the ability to communicate the topics of satellite remote sensing clearly and concisely from a physics perspective.

• Acquire sufficient knowledge to utilize and discuss satellite-derived atmospheric products in the student’s thesis/dissertation projects.

• Demonstrate the ability to recognize tacit physical assumptions and simplifications in satellite remote sensing methods and to discuss potential uncertainties/biases due to these assumptions and simplifications.

Topics

The topics covered in this course include (subject to change):

• Physical and mathematical basis in satellite remote sensing

• Visible/near-infrared imaging for cloud/aerosol retrievals

• Ultraviolet DOAS approach for atmospheric gas retrievals

• Infrared/microwave radiometry for cloud and precipitation retrievals

• Active-sensor (radar/lidar) remote sensing for cloud, aerosol, and precipitation

• Limb sounding for stratospheric aerosol retrievals

• Advanced satellite remote sensing methods and future satellite missions

Anonymous student feedback (2024 Spring)

• I liked the in-depth discussion of the math and drawing the figures.

• The incorporation of discussions really helped, also the derivation of the equations and homeworks.

• The course content was well-structured. I really liked you providing effective recaps of previous lectures before diving into new material. The lectures were conveyed clearly and engagingly, contributing to a positive learning experience overall. I appreciate you been always open to feedback and suggestions from the students and for applying them in class. Discussion sessions were very effective.

• I really like MASA's classes. I believe the most effective aspect is having the mathmatic derivation to understand the physics principle of remote sensing techiniques.