COMET® Microwave Remote Sensing Distance Learning Course Modules

Description:
This module presents an overview of space-based microwave remote sensing for environmental applications. It provides basic information on polar-orbiting satellite characteristics, current microwave instruments, and the imagery and products currently available from these sensors. Special attention is given to the improvements expected in the NPOESS era. This module is an introduction to other, more in-depth modules covering the science and application of cloud, precipitation, water vapor, land and sea surface observations.

Objectives:
• Describe how microwave remote sensing compliments visible and infrared observations
• Describe the general spatial and temporal coverage characteristics of microwave observations from polar-orbiting satellites
• Define data latency and explain why it occurs
• Describe the improvements to data latency coming in 2006, and then in the NPOESS era
• List several products that rely on microwave remote sensing
• Explain the fundamental difference between active versus passive remote sensing
• State the six “key” NPOESS Environmental Data Records (EDRs) considered essential to weather and climate monitoring and prediction
• Describe the importance and impact of microwave observations on numerical weather prediction models
• State the key differences between microwave and radiosonde sounding of atmospheric temperature and moisture
• Describe radio frequency interference as it relates to microwave observations, its geographical distribution, and potential impact on products

Estimated time to complete: 40 min

Description:
This module provides an introduction to polar-orbiting-satellite-based microwave remote sensing products that depict moisture and precipitation in the atmosphere. The module begins with definitions and descriptions of total precipitable water and cloud liquid water products, contrasting each with more familiar infrared water vapor and window channel products. This is followed by an overview of microwave precipitation estimation and a discussion of how polar-satellite products compare with those from geostationary satellites and ground-based radar. A series of case examples highlights potential weather forecasting applications for total precipitable water and precipitation products. The module also includes an introduction to the Global Precipitation Monitoring Mission to which future NPOESS satellites will be an important contributor. This module takes about 75 minutes to complete.

Objectives:
After completing this module, learners will be able to:
• State the definition of total precipitable water
• State the definition of cloud liquid water
• Describe the difference between window regions and absorption regions of the electromagnetic spectrum
• Describe how precipitation rates are derived over land and ocean
• Describe the goals of the Global Precipitation Monitoring Program
• Interpret total precipitable water, cloud liquid water, and precipitation products presented in case examples

Estimated time to complete: 75 min

Description:
This module introduces the concepts and principles basic to retrieving important land and ocean surface properties using microwave remote sensing observations from polar-orbiting satellites. Section one reviews the advantages of microwave remote sensing from polar-orbiting platforms and briefly highlights some of the unique spectral characteristics that allow for differentiation between various surface types and properties. Subsequent sections present a more in-depth look at the derivation and application of microwave products that quantify four different land and ocean surface properties and their characteristics, including snow cover and water equivalent, sea ice, surface wetness and soil moisture, and sea surface temperature. The module reviews both past and current satellite missions and also discusses the future NPOESS constellation that is expected to include a passive microwave sensing capability beginning with the second NPOESS satellite. This module takes about 120 minutes to complete.

Objectives:
After completing this module learners will be able to:

• Describe the benefits of microwave remote sensing for observing various surface properties when compared to visible and infrared approaches
• Describe the key application areas and users that benefit from characterization of snow cover, sea ice, sea surface temperature, and surface wetness and soil moisture
• Understand the basic principles that enable the microwave remote sensing of the various surface properties described in the module
• Describe the limitations common to the retrieval of surface properties covered in the module
• Describe some of the limitations unique to each of the four surface properties covered in the module
• Name the polar-orbiting satellite systems currently available and those planned for future implementation

Estimated time to complete: 2 h

Description:
This Webcast covers the ocean surface wind retrieval process, the basics of microwave polarization as it relates to wind retrievals, and several operational examples. Information on the development of microwave sensors used to retrieve ocean surface wind speed and the ocean surface wind vector (speed and direction) is also included.

Objectives:
State some key meteorological applications for ocean surface winds

• Describe the benefits of using microwave remote sensing to observe ocean winds
• Describe the differences between active and passive microwave remote sensing
• Describe in general terms, the emission, transmission, and scattering of microwave energy within the Earth-atmosphere system
• State the key assumptions for derivation of wind speed and direction from passive observation of microwave radiation
• Describe the limitations of passive microwave remote sensing and impacts on deriving wind speed and direction (this applies to both product limits and accuracy)
• Use cloud liquid water imagery to help assess the validity of the wind speed and direction vector

Estimated time to complete: 45 min

Description:
This module provides background information on microwave remote sensing with polar-orbiting satellites. It reviews coverage, orbits, and data latency issues of current operational and selected research satellites and notes improvements expected in the NPP and NPOESS era. The module contrasts active vs. passive remote sensing, discusses advantages and limitations of different microwave instrument scanning strategies, and addresses viewing geometry with implications for spatial resolution and swath coverage. Finally, it offers a review of the microwave spectrum and special characteristics of microwave energy important for understanding microwave imagery and derived products. This module takes about 1 hour to complete.

Objectives:
* Describe the orbits and coverage of current polar-orbiting environmental satellites.
* Describe improvements in data latency with the implementation of pipeline processing and the NPOESS SafetyNet© ground system.
* State the differences between active and passive microwave remote sensing.
* Describe crosstrack, conical, and fan beam scanning strategies, the advantages and limitations of each, and their impacts on viewing geometry and spatial resolution.
* Describe the difference between window regions and absorption regions of the electromagnetic spectrum.
* State the relationship between observed microwave energy, sensor field-of-view, and spatial resolution.
* Describe the basic principle of polarization, how it can affect emitted microwave radiation, and its importance for characterizing surface features and atmospheric constituents.
* Describe why water surfaces generally appear relatively cold and land surfaces appear relatively warm in the microwave.
* Describe how passive microwave observations can be used to infer ocean surface wind speed and direction.
* Describe the relationship between dielectric effect, scattering, and emissivity and its importance for microwave remote sensing.
* Name some of the remote sensing applications that rely on the dielectric effect on observed microwave radiation.

Estimated time to complete: 1 h

Description:
This module introduces forecasters to the use of microwave image products for observing and analyzing tropical cyclones. Microwave data from polar-orbiting satellites is crucial to today’s operational forecasters, and particularly for those with maritime forecasting responsibilities where in situ observations are sparse. This module includes information on storm structure and techniques for improved storm positioning using the 37 and 85-91 GHz channels from several satellite sensors. Information on current sensors and on the product availability in the NPOESS era is also presented.

Objectives:
• Explain how single channel and multispectral microwave imagery can be used to locate centers of circulation and other features within tropical cyclones
• Explain how parallax error affects imagery from different microwave channels
• Identify satellites that carry microwave imagers and sounders
• Contrast active and passive microwave remote sensing strategies
• Contrast conical and cross-track scanning strategies
• Explain how clouds, precipitation, and the ocean surface interact with microwave
energy at different frequencies
• Associate storm characteristics with features observed in microwave imagery

Estimated time to complete: 60 min

Description:
The COMET Program and the Integrated Program Office are pleased to announce the publication of The Operational Tropical Rainfall Potential (TRaP) module. This module, developed by Sheldon Kusselson (Satellite Analysis Branch, NESDIS), traces the development of the present TRaP product and shows numerous examples from recent hurricane seasons comparing model precipitation forecast amounts, TRaP estimated rainfall amounts, and observed rainfall. Guidelines for using the TRaP product and future improvements are presented at the conclusion of the module.

Objectives:
• State the basis of the TRaP technique, its formulation, and inputs
• State the assumptions and the limitations of the technique
• Find and access TRaP products on the Internet
• Interpret TRaP imagery for use in precipitation estimation

Estimated time to complete: 1 h