Remote sounding of atmospheric variables by groundbased microwave radiometers has proved to be useful for several applications. These radiometers are used to measure profiles or integrated values of temperature, water vapor, and cloud liquid. The information provided is useful in meteorology, astronomy, geodesy, communication, for correction of space observations, for atmospheric research, etc. It may be possible to combine ground-based radiometers, satellite-borne radiometers, and VHF radars to form a meteorological network which provides profiles of temperature, humidity, and wind continuously in time. This paper will review some of the developments in this area, describe basic principles and results of field experiments, including the recent ONSAM-experiment, and summarize two years' performance of the NOAA Profiler.

A Review of Ground-Based Remote Sensing of Temperature and Moisture by Passive Microwave Radiometers

A new neural network algorithm for the inversion of radiometric data to retrieve atmospheric profiles of temperature and vapor has been developed. The potentiality of the neural networks has been exploited not only for inversion purposes but also for data feature extraction and dimensionality reduction. In its complete form, the algorithm uses a neural network architecture consisting of three stages: 1) the input stage reduces the dimension of the input vector; 2) the middle stage performs the mapping from the reduced input vector to the reduced output vector; 3) the third stage brings the output of the middle stage to the desired actual dimension. The effectiveness of the algorithm has been evaluated comparing its performance to that obtainable with more traditional linear techniques.

Nonlinear principal component analysis for the radiometric inversion of atmospheric profiles by using neural networks

An inversion technique is presented for retrieving vertical profiles of atmospheric temperature and vapor from the brightness temperatures measured by a ground-based multichannel microwave radiometer and the surface measurements of temperature and relative humidity. It combines a profile expansion over a complete set of natural orthogonal functions with a neural network which performs the estimate of the coefficients of the expansion itself. A simulation study has been carried out, and the algorithm has been tested by comparing its retrievals with those obtained by means of linear statistical inversion applied on the same data sets. The analysis has been limited to the case of profiles with clouds in order to test the ability of the neural network to face nonlinear problems. The technique has proven to be flexible, showing a good capability of exploiting information provided by other instruments, such as a laser ceilometer. A fault tolerance evaluation has also been considered, which showed interesting properties of robustness of the algorithm.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/97RS02219

A combined natural orthogonal functions/neural network technique for the radiometric estimation of atmospheric profiles

The NASA/GSFC Crustal Dynamics Project microwave water vapor radiometer (J03) is evaluated in terms of measurements of the integrated precipitable water vapor content of a particular column of the troposphere. The measurements were taken during the Atmospheric Moisture Intercomparison Study (ATMIS) held at Wallops Island (Virginia) during April 1989. Water vapor sensing instruments used during ATMIS, included radiometers, radiosondes, and the NASA/GSFC Raman lidar. Comparisons between water vapor measurements by the radiometer and the lidar yielded a correlation coefficient of 0.998 and rms differences for three nights of -0.2 +/- 0.2 mm (April 11-12), -0.8 +/- 0.5 mm (April 16-17), and -0.4 +/- 0.3 mm (April 17-18). The integrated precipitable water vapor measurements for these three nights were approximately 5, 10 and 21 mm, respectively. This study shows that the radiometer provides accurate continuous measurements of the water vapor integrated through the depth of the atmosphere.

Atmospheric water vapor measurements: Comparison of microwave radiometry and lidar

A low power and high gain V-band CMOS low-noise amplifier (LNA) is proposed in this letter with a three-stage cascode topology. Using the gate-inductive gain-peaking technique to boost the gain, the proposed LNA achieves a good figure of merit (FOM) with less power consumption. This proposed LNA is fabricated in a 0.13 μm RF CMOS process, which achieves a peak gain of 21 dB at 53 GHz, a noise figure (NF) of 7.6 dB at 53 GHz, a 3 dB frequency bandwidth ranging from 51.3 to 55.8 GHz, an input 1 dB compression point (P1 dB) of - 25 dBm at 53 GHz, and an input third-order intercept point (IIP3) of -16 dBm. Also, the LNA consumes only 15.1 mW at a supply voltage of 1.5 V. The calculated FOM is 0.81 in average. Such a V-band LNA design is applicable to the cost-efficiency integration of a microwave radiometer front-end circuit over the operation frequency band of 52 to 56 GHz.

Low-Power, High-Gain V-Band CMOS Low Noise Amplifier for Microwave Radiometer Applications

The performance of a ground-based microwave radiometer of new design to be used for remote sensing of the temperature profile of the atmosphere has been tested. It is continuously tunable in the range 52-8-58-8 GHz and has a high absolute accuracy. The radiometer measurements have been analysed with the statistical inversion method and the retrieved profiles have been compared with 28 simultaneous radiosoundings. The r.m.s. difference under clear-sky and cloudy conditions was, on these occasions, less than l-5degK up to 6km and 4km, respectively, less than OdegK up to 8 and 5-5 km, respectively, and less than 3-0degK up to 9 and 7-5 km, respectively. Methods to increase the profiling accuracy are discussed.

Test of a ground-based microwave radiometer for atmospheric temperature profiling with meteorological applications

The ONSala Atmospheric Measurement program was carried out in May 1983 in order to test the performance of new remote sensing equipment, compared with radiosondes launched for this particular program. A temperature profiling radiometer and a water vapor radiometer as well as a lidar were tested, and recordings from the NOAA-7 satellite were analyzed. Retrieval algorithms have been developed and various possible ways to improve the profiling accuracy, such as developing an air mass classification scheme, have been studied. The results constitute a valuable database of observations obtained from traditional and remote sensing equipment. In this paper, the results currently available are presented and summarized.

The ONSAM Experiment: Remote Sensing Techniques for Vertical Sounding of the Atmosphere

The design of a continuously tuned 53 - 59 GHz radiometer for measurement of the atmospheric temperature profile is presented. The broadband solution makes the radiometer cost-effective and permits observations on a large number of frequencies which increases the profiling accuracy. To meet the demand for high-precision measurements two calibration loads are included one of which is cooled to 253 K. During a field experiment the radiometer was calibrated and the absolute accuracy of the radiometer was found to be better than 0.5 K. The profiling capability was evaluated using the statistical inversion method. The accuracy of the retrieved profiles was improved when the number of channels was increased from four to eleven.

E. Winberg

Papers

Test of a ground-based microwave radiometer for atmospheric temperature profiling with meteorological applications

The ONSAM Experiment: Remote Sensing Techniques for Vertical Sounding of the Atmosphere

A Continuously Tuned 53 - 59 GHz Radiometer for Measurement of Atmospheric Temperature Profiles

Atmospheric remote sensing as test of models for propagation in moist air