Ground-based single-frequency microwave radiometric measurement of water vapour

Karmakar, P. K.; Maiti, Manabendra; Calheiros, Alan James Peixoto; Angelis, Carlos Frederico de; Machado, Luiz A. T.; Costa, Susanga

doi:10.1080/01431161.2010.543185

Cited by 6 publications

(2 citation statements)

References 14 publications

(11 reference statements)

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“…30 GHz lies in weak water vapour attenuation region. It has also been found that the choice of this frequency pair is optimal (4,20) for the measurement of vapour and liquid water.…”

Section: Methodsmentioning

confidence: 99%

Determination of sky status by ground based radiometric data analysis

Maiti¹,

Bhattacharyya²,

Biswas³

et al. 2021

IJST

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Objectives: To predict meteorological phenomena such as rain events from sky status during rainy and non-rainy periods. Methods: The method used here is based on brightness temperature ratio measurement at two different frequencies, namely 23.8 GHz and 30 GHz respectively, using ground based dual frequency radiometric data. The ratios of brightness temperature readings obtained by the dual-frequency radiometer at the two above mentioned frequencies are calculated for each simultaneously-taken pair of measurements. Data obtained by the authors for the year 2009 at Cachoeira Paulista in Brazil has been used for analysis. Findings: The major results obtained from the analysis of data collected over a continuous period of seven months are used to construct corresponding histograms and cumulative count graphs of brightness temperature ratios. The histograms and graphs clearly show three peak values that could be interpreted as thresholds between clear sky, cloudy sky and rainy sky conditions respectively. Novelty: The study implements detection of rain events from sky status during rainy and non-rainy periods using peak brightness temperature values obtained from graphs generated using the observation data. The outlined technique can therefore be used to clearly determine sky conditions and accurately predict rain phenomena. The ratio of brightness temperatures at the two frequencies is a unique parameter which is critical to the successful estimation of rain from sky status. The results agree well with multi-channel radiometric data obtained by other researchers at lower frequencies.

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“…30 GHz lies in weak water vapour attenuation region. It has also been found that the choice of this frequency pair is optimal (4,20) for the measurement of vapour and liquid water.…”

Section: Methodsmentioning

confidence: 99%

Determination of sky status by ground based radiometric data analysis

Maiti¹,

Bhattacharyya²,

Biswas³

et al. 2021

IJST

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“…(9) T BO2 from the 19 channels is used in the inversion of temperature and humidity profiles. The inversion method used in this study is the traditional, multiple regression method [21,40,41], and the regression coefficients are calculated from clear-sky observations.…”

Section: Algorithm For Atmospheric Temperature and Humidity Profile Inversion In Cloudy Conditionsmentioning

confidence: 99%

Improving the Retrieval of Cloudy Atmospheric Profiles from Brightness Temperatures Observed with a Ground-Based Microwave Radiometer

Wei

Wang

et al. 2021

Atmosphere

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Atmospheric temperature and humidity retrievals from ground-based microwave remote sensing are useful in a variety of meteorological and environmental applications. Though the influence of clouds is usually considered in current retrieval algorithms, the resulting temperature and humidity estimates are still biased high in overcast conditions compared to radiosonde observations. Therefore, there is a need to improve the quality of retrievals in cloudy conditions. This paper presents an approach to make brightness temperature (TB) correction for cloud influence before the data can be used in the inversion of vertical profiles of atmospheric temperature and humidity. A three-channel method is proposed to make cloud parameter estimation, i.e., of the total 22 channels of the ground-based radiometer, three are adopted to set up a relationship between cloud parameters and brightness temperatures, so that the observations from the three channels can be used to estimate cloud thickness and water content and complete the cloud correction for the rest of the channels used in the retrieval. Based on two years of data from the atmosphere in Beijing, a comparison of the retrievals with radiosonde observations (RAOB) shows: (1) the temperature retrievals from this study have a higher correlation with RAOB and are notably better than in the vendor-provided LV2. The bias of the temperature retrievals from this study is close to zero at all heights, and the RMSE is greatly reduced from >5 °C to <2 °C in the layer, from about 1.5 km up to 5 km. The temperature retrievals from this study have higher correlation with RAOB data compared to the vendor-provided LV2, especially at and above a 2 km height. (2) The bias of the water vapor density profile from this study is near to zero, while the LV2 has a positive bias as large as 4 g/m3. The RMSE of the water vapor density profile from this study is <2 g/m3, while the RMSE for LV2 is as large as 10 g/m3. That is, both the bias and RMSE from this study are evidently less than the LV2, with a greater improvement in the lower troposphere below 5 km. Correlation with RAOB is improved even more for the water vapor density. The correlation of the retrievals from this study increases to one within the boundary layer, but the correlation of LV2 with RAOB is only 0.8 at 0.5 km height, 0.7 at 1 km, and even less than 0.5 at 2 km. (3) A parameter named the Cloud Impact index, determined by cloud water concentration and cloud thickness, together with the cloud base height, has been defined to show that both BIAS and RMSE of “high-CI subsample” are larger than those of the “low-CI subsample”, indicating that high-CI cloud has a higher impact on the retrievals and the correction for cloud influence is more necessary.

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