Abstract
This paper intends to briefly present some basic concepts on the microwave radiometry and radiometer calibration research in remote sensing applications and demonstrate results and analysis of the cryogenic calibration of a microwave ground-based radiometer currently deployed in scientific campaigns in Brazil. The equipment described in this text operates at 22 – 30 GHz and at 51 – 59 GHz frequency ranges and uses as the calibration standard a target cooled by liquid nitrogen. Since an accurate calibration (with observation errors below 0.5 K) is important to provide confidence in the retrieval of vertical temperature and humidity profiles, this work aims also to comment on some effects of the errors in calibration procedure on the atmospheric parameters of interest.
Highlights
A microwave radiometer is a passive device conceived for the detection of electromagnetic energy emitted by a source, a scene, or an object, since this energy has an inherent noise behavior
Remote sensing of the microwave radiation of the atmosphere using ground-based radiometers has been proved highly efficient in a range of applications such as meteorology, weather forecast, nowcasting, telecommunications, astronomy, satellite and radar validation data, and so on (Miacci et al 2015; Westwater et al 2004; Godoy and Yung 1995; Janssen 1993; Ulaby et al 1986; Hayes 1989)
For the humidity profiles are expected errors of approximately 5 up to 25% depending on the altitude – a greater error at high altitudes due to radiometer’s spatial resolution and artificial neural networks technique employed
Summary
A microwave radiometer is a passive device conceived for the detection of electromagnetic energy emitted by a source, a scene, or an object, since this energy has an inherent noise behavior. Remote sensing of the microwave radiation of the atmosphere using ground-based radiometers has been proved highly efficient in a range of applications such as meteorology, weather forecast, nowcasting, telecommunications, astronomy, satellite and radar validation data, and so on (Miacci et al 2015; Westwater et al 2004; Godoy and Yung 1995; Janssen 1993; Ulaby et al 1986; Hayes 1989). Those results have contributed to the development and enhancements of radiative transfer models for clear and cloudy sky conditions
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