scholarly journals Measurement of Solar Absolute Brightness Temperature Using a Ground-Based Multichannel Microwave Radiometer

2021 ◽  
Vol 13 (15) ◽  
pp. 2968
Author(s):  
Lianfa Lei ◽  
Zhenhui Wang ◽  
Yingying Ma ◽  
Lei Zhu ◽  
Jiang Qin ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Brightness Temperature ◽  
Microwave Radiation ◽  
Atmospheric Temperature ◽  
Solar Observation ◽  
The Sun ◽  
Temperature And Humidity ◽  
Microwave Radiometers ◽  
Humidity Profiles ◽  
Absolute Brightness

Ground-based multichannel microwave radiometers (GMRs) can observe the atmospheric microwave radiation brightness temperature at K-bands and V-bands and provide atmospheric temperature and humidity profiles with a relatively high temporal resolution. Currently, microwave radiometers are operated in many countries to observe the atmospheric temperature and humidity profiles. However, a theoretical analysis showed that a radiometer can be used to observe solar radiation. In this work, we improved the control algorithm and software of the antenna servo control system of the GMR so that it could track and observe the sun and we use this upgraded GMR to observe solar microwave radiation. During the observation, the GMR accurately tracked the sun and responded to the variation in solar radiation. Furthermore, we studied the feasibility for application of the GMR to measure the absolute brightness temperature (TB) of the sun. The results from the solar observation data at 22.235, 26.235, and 30.000 GHz showed that the GMR could accurately measure the TB of the sun. The derived solar TB measurements were 9950 ± 334, 10,351 ± 370, and 9217 ± 375 K at three frequencies. In a comparison with previous studies, we obtained average percentage deviations of 9.1%, 5.3%, and 4.5% at 22.235, 26.235, and 30.0 GHz, respectively. The results demonstrated that the TB of the sun retrieved from the GMR agreed well with the previous results in the literature. In addition, we also found that the GMR responded to the variation in sunspots and a positive relationship existed between the solar TB and the sunspot number. According to these results, it was demonstrated that the solar observation technique can broaden the field usage of GMR.

scholarly journals Application of the Deep Neural Network in Retrieving the Atmospheric Temperature and Humidity Profiles from the Microwave Humidity and Temperature Sounder Onboard the Feng-Yun-3 Satellite

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4673
Author(s):  
Qiurui He ◽  
Zhenzhan Wang ◽  
Jiaoyang Li
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Bias Correction ◽  
Deep Neural Network ◽  
Microwave Remote Sensing ◽  
Atmospheric Temperature ◽  
Superior Performance ◽  
Atmospheric Parameters ◽  
Temperature And Humidity ◽  
Humidity Profiles

The shallow neural network (SNN) is a popular algorithm in atmospheric parameters retrieval from microwave remote sensing. However, the deep neural network (DNN) has a stronger nonlinear mapping capability compared to SNN and has great potential for applications in microwave remote sensing. The Microwave Humidity and Temperature Sounder (Beijing, China, MWHTS) onboard the Fengyun-3 (FY-3) satellite has the ability to independently retrieve atmospheric temperature and humidity profiles. A study on the application of DNN in retrieving atmospheric temperature and humidity profiles from MWHTS was carried out. Three retrieval schemes of atmospheric parameters in microwave remote sensing based on DNN were performed in the study of bias correction of MWHTS observation and the retrieval of the atmospheric temperature and humidity profiles using MWHTS observations. The experimental results show that, compared with SNN, DNN can obtain better bias-correction results when applied to MWHTS observation, and can obtain higher retrieval accuracy of temperature and humidity profiles in all three retrieval schemes. Meanwhile, DNN shows higher stability than SNN when applied to the retrieval of temperature and humidity profiles. The comparative study of DNN and SNN applied in different atmospheric parameter retrieval schemes shows that DNN has a more superior performance.

scholarly journals A Study on the Retrieval of Temperature and Humidity Profiles Based on FY-3D/HIRAS Infrared Hyperspectral Data

2021 ◽  
Vol 13 (11) ◽  
pp. 2157
Author(s):  
Chunming Zhang ◽  
Mingjian Gu ◽  
Yong Hu ◽  
Pengyu Huang ◽  
Tianhang Yang ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Error Correction ◽  
Retrieval System ◽  
Atmospheric Temperature ◽  
Hyperspectral Data ◽  
Humidity Profile ◽  
Retrieval Accuracy ◽  
Temperature And Humidity ◽  
Humidity Profiles ◽  
Better Than

Satellite infrared hyperspectral instruments can obtain a wealth of atmospheric spectrum information. In order to obtain high-precision atmospheric temperature and humidity profiles, we used the traditional One-Dimensional Variational (1D-Var) retrieval algorithm, combined with the information capacity-weight function coverage method to select the spectrum channel. In addition, an Artificial Neural Network (ANN) algorithm was introduced to correct the satellite observation data error and compare it with the conventional error correction method. Finally, to perform the temperature and humidity profile retrieval calculation, we used the FY-3D satellite HIRAS (Hyperspectral Infrared Atmospheric Sounder) infrared hyperspectral data and combined the RTTOV (Radiative Transfer for TOVS) radiative transfer model to build an atmospheric temperature and humidity profile retrieval system. We used data on the European region from July to August 2020 to carry out the training and testing of the retrieval system, respectively, and used the balloon-retrieved sounding data of temperature and humidity published by the University of Wyoming as standard truth values to evaluate the retrieval accuracy. Our preliminary research results show that, compared with the retrieval results of conventional deviation correction, the introduction of ANN algorithm error correction can improve the retrieval accuracy of the retrieval system effectively and the RMSE (Root-Mean-Square Error) of the temperature and humidity has a maximum accuracy of improvement of about 0.5 K (The K represents the thermodynamic temperature unit) and 5%, respectively. The temperature and humidity results obtained by the retrieval system were compared with Global Forecast System (GFS) forecast data. The retrieved temperature RMSE was less than 1.5 K on average, which was better than that for the GFS; the humidity RMSE was less than 15% as a whole, and better than the forecast profile between 100 hpa (1 hpa is 100 pa, the pa represents the air pressure unit) and 600 hpa. Compared with AIRS (Atmospheric Infrared Sounder) products, the result of the retrieval system also had a higher accuracy. The main improvement of the temperature was at 200 hpa and 800 hpa, with maximum accuracy improvements of 2 K and 1.5 K, respectively. The RMSE of the humidity retrieved by the system was also better than the AIRS humidity products at most pressure levels, and the error of maximum difference could reach 15%. After combining the two algorithms, the FY-3D/HIRAS infrared hyperspectral retrieval system could obtain higher-precision temperature and humidity profiles, and relevant results could provide a reference for improving the accuracy of business products.

scholarly journals A Numerical Method for Synthesizing Atmospheric Temperature and Humidity Profiles

1998 ◽  
Vol 37 (7) ◽  
pp. 718-729 ◽  
Author(s):  
Maia S. Tatarskaia ◽  
Richard J. Lataitis ◽  
B. Boba Stankov ◽  
Viatcheslav V. Tatarskii
Keyword(s):  
Numerical Method ◽  
Atmospheric Temperature ◽  
Temperature And Humidity ◽  
Humidity Profiles

scholarly journals Evaluation and Improvement of the Quality of Ground-Based Microwave Radiometer Clear-Sky Data

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 435
Author(s):  
Qing Li ◽  
Ming Wei ◽  
Zhenhui Wang ◽  
Yanli Chu
Keyword(s):  
Water Vapor ◽  
Temperature Inversion ◽  
Atmospheric Temperature ◽  
Radiosonde Data ◽  
Vapor Density ◽  
Clear Sky ◽  
Brightness Temperatures ◽  
Temperature And Humidity ◽  
Humidity Profiles

To assess the quality of the retrieved products from ground-based microwave radiometers, the “clear-sky” Level-2 data (LV2) products (profiles of atmospheric temperature and humidity) filtered through a radiometer in Beijing during the 24 months from January 2010 to December 2011 were compared with radiosonde data. Evident differences were revealed. Therefore, this paper investigated an approach to calibrate the observed brightness temperatures by using the model-simulated brightness temperatures as a reference under clear-sky conditions. The simulation was completed with a radiative transfer model and National Centers for Environmental Prediction final analysis (NCEP FNL) data that are independent of the radiometer system. Then, the least-squares method was used to invert the calibrated brightness temperatures to the atmospheric temperature and humidity profiles. A comparison between the retrievals and radiosonde data showed that the calibration of the brightness temperature observations is necessary, and can improve the inversion of temperature and humidity profiles compared with the original LV2 products. Specifically, the consistency with radiosonde was clearly improved: the correlation coefficients are increased, especially, the correlation coefficient for water vapor density increased from 0.2 to 0.9 around the 3 km height; the bias decreased to nearly zero at each height; the RMSE (root of mean squared error) for temperature profile was decreased by more than 1 degree at most heights; the RMSE for water vapor density was decreased from greater than 4 g/m3 to less than 1.5 g/m3 at 1 km height; and the decrease at all other heights were also noticeable. In this paper, the evolution of a temperature inversion process is given as an example, using the high-temporal-resolution brightness temperature after quality control to obtain a temperature and humidity profile every two minutes. Therefore, the characteristics of temperature inversion that cannot be seen by conventional radiosonde data (twice daily) were obtained by radiometer. This greatly compensates for the limited temporal coverage of radiosonde data. The approach presented by this paper is a valuable reference for the reprocessing of the historical observations, which have been accumulated for years by less-calibrated radiometers.

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