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.

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

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 648
Author(s):  
Qing Li ◽  
Ming Wei ◽  
Zhenhui Wang ◽  
Sulin Jiang ◽  
Yanli Chu
Keyword(s):  
Water Vapor ◽  
Density Profile ◽  
Lower Troposphere ◽  
Microwave Remote Sensing ◽  
Atmospheric Temperature ◽  
Cloud Base ◽  
Vapor Density ◽  
Brightness Temperatures ◽  
Temperature And Humidity ◽  
Cloud Thickness

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.

Characteristics of Satellite-Derived Clear-Sky Atmospheric Temperature Inversion Strength in the Arctic, 1980–96

2006 ◽  
Vol 19 (19) ◽  
pp. 4902-4913 ◽  
Author(s):  
Yinghui Liu ◽  
Jeffrey R. Key ◽  
Axel Schweiger ◽  
Jennifer Francis
Keyword(s):  
Temperature Inversion ◽  
Atmospheric Temperature ◽  
Cold Season ◽  
The Arctic ◽  
Radiosonde Data ◽  
Clear Sky ◽  
Dominant Feature ◽  
Inversion Strength ◽  
Arctic Atmosphere ◽  
Temperature Inversions

Abstract The low-level atmospheric temperature inversion is a dominant feature of the Arctic atmosphere throughout most of the year. Meteorological stations that provide radiosonde data are sparsely distributed across the Arctic, and therefore provide little information on the spatial distribution of temperature inversions. Satellite-borne sensors provide an opportunity to fill the observational gap. In this study, a 17-yr time series, 1980–96, of clear-sky temperature inversion strength during the cold season is derived from High Resolution Infrared Radiation Sounder (HIRS) data using a two-channel statistical method. The satellite-derived clear-sky inversion strength monthly mean and trends agree well with radiosonde data. Both increasing and decreasing trends are found in the cold season for different areas. It is shown that there is a strong coupling between changes in surface temperature and changes in inversion strength, but that trends in some areas may be a result of advection aloft rather than warming or cooling at the surface.

scholarly journals Antarctic Low-Tropospheric Humidity Inversions: 10-Yr Climatology

2013 ◽  
Vol 26 (14) ◽  
pp. 5205-5219 ◽  
Author(s):  
Tiina Nygård ◽  
Teresa Valkonen ◽  
Timo Vihma
Keyword(s):  
Water Vapor ◽  
Climate Models ◽  
Weather Prediction ◽  
Temperature Inversion ◽  
Statistical Characteristics ◽  
The Arctic ◽  
Radiosonde Data ◽  
Atmospheric Moisture Budget ◽  
Temperature Inversions ◽  
The Antarctic

Abstract Humidity inversions are nearly permanently present in the coastal Antarctic atmosphere. This is shown based on an investigation of statistical characteristics of humidity inversions at 11 Antarctic coastal stations using radiosonde data from the Integrated Global Radiosonde Archive (IGRA) from 2000 to 2009. The humidity inversion occurrence was highest in winter and spring, and high atmospheric pressure and cloud-free conditions generally increased the occurrence. A typical humidity inversion was less than 200 m deep and 0.2 g kg−1 strong, and a typical humidity profile contained several separate inversion layers. The inversion base height had notable seasonal variations, but generally the humidity inversions were located at higher altitudes than temperature inversions. Roughly half of the humidity inversions were associated with temperature inversions, especially near the surface, and humidity and temperature inversion strengths as well as depths correlated at several stations. On the other hand, approximately 60% of the humidity inversions were accompanied by horizontal advection of water vapor increasing with height, which is also a probable factor supporting humidity inversions. The spatial variability of humidity inversions was linked to the topography and the water vapor content of the air. Compared to previous results for the Arctic, the most striking differences in humidity inversions in the Antarctic were a much higher frequency of occurrence in summer, at least under clear skies, and a reverse seasonal cycle of the inversion height. The results can be used as a baseline for validation of weather prediction and climate models and for studies addressing changes in atmospheric moisture budget in the Antarctic.

scholarly journals A New Technique for Estimation of Lower-Tropospheric Temperature and Water Vapor Profiles from Radio Occultation Refractivity

2009 ◽  
Vol 26 (6) ◽  
pp. 1075-1089 ◽  
Author(s):  
D. Jagadheesha ◽  
B. Simon ◽  
P-K. Pal ◽  
P. C. Joshi ◽  
A. Maheshwari
Keyword(s):  
Radio Occultation ◽  
Specific Humidity ◽  
New Technique ◽  
Radiosonde Data ◽  
Boreal Summer ◽  
Tropospheric Temperature ◽  
Lower Altitude ◽  
Temperature And Humidity ◽  
The Tropics ◽  
Humidity Profiles

Abstract An empirical technique is proposed to obtain temperature and humidity profiles over the tropics using radio occultation refractivity profiles and surface/available lower-altitude temperature and pressure measurements over humid tropical regions. The technique is tested on a large number of diverse radiosonde-derived refractivity profiles over the tropics (30°S–30°N) and selected Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation refractivity profiles that have collocated radiosonde observations over the region 10°S–30°N during the boreal summer of 2006. In a number of cases, the results were in good agreement with the collocated radiosonde data. The error statistics of temperature and humidity profiles obtained from the proposed technique are discussed and compared with the previously published results from another technique and also with the results of a one-dimensional variational data assimilation (1DVAR) technique given with COSMIC data. It is found that the previously published results and proposed technique are marginally better (worse) in reproducing observed relative humidity (specific humidity) when compared to the 1DVAR technique. The proposed new technique is applied on COSMIC refractivity profiles over the Bay of Bengal during summer 2007 to derive changes in vertical thermal and moisture changes in the troposphere between active and break phases of the monsoon pattern and many of the observed features are captured reasonably well.

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 Accuracy of retrieving temperature and humidity profiles by ground-based microwave radiometry in truly complex terrain

2015 ◽  
Vol 8 (8) ◽  
pp. 3355-3367 ◽  
Author(s):  
G. Massaro ◽  
I. Stiperski ◽  
B. Pospichal ◽  
M. W. Rotach
Keyword(s):  
Complex Terrain ◽  
Microwave Radiometer ◽  
Radiosonde Data ◽  
Alpine Valley ◽  
Topographic Slope ◽  
Retrieval Algorithms ◽  
Temperature And Humidity ◽  
Upper Level ◽  
The One ◽  
Humidity Profiles

Abstract. Within the Innsbruck Box project, a ground-based microwave radiometer (RPG-HATPRO) was operated in the Inn Valley (Austria), in very complex terrain, between September 2012 and May 2013 to obtain temperature and humidity vertical profiles of the full troposphere with a specific focus on the valley boundary layer. In order to assess its performance in a deep alpine valley, the profiles obtained by the radiometer with different retrieval algorithms based on different climatologies are compared to local radiosonde data. A retrieval that is improved with respect to the one provided by the manufacturer, based on better resolved data, shows a significantly smaller root mean square error (RMSE), both for the temperature and humidity profiles. The improvement is particularly substantial at the heights close to the mountaintop level and in the upper troposphere. Lower-level inversions, common in an alpine valley, are resolved to a satisfactory degree. On the other hand, upper-level inversions (above 1200 m) still pose a significant challenge for retrieval. For this purpose, specialized retrieval algorithms were developed by classifying the radiosonde climatologies into specialized categories according to different criteria (seasons, daytime, nighttime) and using additional regressors (e.g., measurements from mountain stations). The training and testing on the radiosonde data for these specialized categories suggests that a classification of profiles that reproduces meaningful physical characteristics can yield improved targeted specialized retrievals. A novel and very promising method of improving the profile retrieval in a mountainous region is adding further information in the retrieval, such as the surface temperature at fixed levels along a topographic slope or from nearby mountaintops.

scholarly journals GPS tomography: validation of reconstructed 3-D humidity fields with radiosonde profiles

2013 ◽  
Vol 31 (9) ◽  
pp. 1491-1505 ◽  
Author(s):  
M. Shangguan ◽  
M. Bender ◽  
M. Ramatschi ◽  
G. Dick ◽  
J. Wickert ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Water Vapor ◽  
Tomographic Reconstruction ◽  
Radiosonde Data ◽  
Total Delay ◽  
Temporal And Spatial Distribution ◽  
Spatial Coverage ◽  
Independent Observations ◽  
Determination System

Abstract. Water vapor plays an important role in meteorological applications; GeoForschungsZentrum (GFZ) therefore developed a tomographic system to derive 3-D distributions of the tropospheric water vapor above Germany using GPS data from about 300 ground stations. Input data for the tomographic reconstructions are generated by the Earth Parameter and Orbit determination System (EPOS) software of the GFZ, which provides zenith total delay (ZTD), integrated water vapor (IWV) and slant total delay (STD) data operationally with a temporal resolution of 2.5 min (STD) and 15 min (ZTD, IWV). The water vapor distribution in the atmosphere is derived by tomographic reconstruction techniques. The quality of the solution is dependent on many factors such as the spatial coverage of the atmosphere with slant paths, the spatial distribution of their intersections and the accuracy of the input observations. Independent observations are required to validate the tomographic reconstructions and to get precise information on the accuracy of the derived 3-D water vapor fields. To determine the quality of the GPS tomography, more than 8000 vertical water vapor profiles at 13 German radiosonde stations were used for the comparison. The radiosondes were launched twice a day (at 00:00 UTC and 12:00 UTC) in 2007. In this paper, parameters of the entire profiles such as the wet refractivity, and the zenith wet delay have been compared. Before the validation the temporal and spatial distribution of the slant paths, serving as a basis for tomographic reconstruction, as well as their angular distribution were studied. The mean wet refractivity differences between tomography and radiosonde data for all points vary from −1.3 to 0.3, and the root mean square is within the range of 6.5–9. About 32% of 6803 profiles match well, 23% match badly and 45% are difficult to classify as they match only in parts.

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.

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