Preliminary Investigation on Using IS Approved Real Time Dry Bulb and Relative Humidity Sensors in Underground Coalmines

2019 ◽  
Keyword(s):  
Relative Humidity ◽  
Real Time ◽  
Preliminary Investigation ◽  
Humidity Sensors

Preliminary Investigation on Using IS Approved Real Time Dry Bulb and Relative Humidity Sensors in Underground Coalmines

2019 ◽  
Vol 55 (1) ◽  
pp. 169-174
Author(s):  
M. Khanal ◽  
R. McPhee ◽  
B. Belle ◽  
P. Brisbane ◽  
B. Kathage
Keyword(s):  
Relative Humidity ◽  
Real Time ◽  
Preliminary Investigation ◽  
Humidity Sensors

Study of Real-Time Dry Bulb and Relative Humidity Sensors in Underground Coal Mines

2016 ◽  
Vol 37 (12) ◽  
Author(s):  
Manoj Khanal ◽  
Ron McPhee ◽  
Bharath Belle ◽  
Peter Brisbane ◽  
Bevan Kathage
Keyword(s):  
Relative Humidity ◽  
Real Time ◽  
Coal Mines ◽  
Humidity Sensors ◽  
Underground Coal Mines

scholarly journals HGPT2: An ERA5-Based Global Model to Estimate Relative Humidity

2021 ◽  
Vol 13 (11) ◽  
pp. 2179
Author(s):  
Pedro Mateus ◽  
Virgílio B. Mendes ◽  
Sandra M. Plecha
Keyword(s):  
Water Vapor ◽  
Relative Humidity ◽  
Real Time ◽  
Prediction Models ◽  
Weather Prediction ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Global Navigation Satellite Systems ◽  
International Gnss Service ◽  
Weighted Mean Temperature

The neutral atmospheric delay is one of the major error sources in Space Geodesy techniques such as Global Navigation Satellite Systems (GNSS), and its modeling for high accuracy applications can be challenging. Improving the modeling of the atmospheric delays (hydrostatic and non-hydrostatic) also leads to a more accurate and precise precipitable water vapor estimation (PWV), mostly in real-time applications, where models play an important role, since numerical weather prediction models cannot be used for real-time processing or forecasting. This study developed an improved version of the Hourly Global Pressure and Temperature (HGPT) model, the HGPT2. It is based on 20 years of ERA5 reanalysis data at full spatial (0.25° × 0.25°) and temporal resolution (1-h). Apart from surface air temperature, surface pressure, zenith hydrostatic delay, and weighted mean temperature, the updated model also provides information regarding the relative humidity, zenith non-hydrostatic delay, and precipitable water vapor. The HGPT2 is based on the time-segmentation concept and uses the annual, semi-annual, and quarterly periodicities to calculate the relative humidity anywhere on the Earth’s surface. Data from 282 moisture sensors located close to GNSS stations during 1 year (2020) were used to assess the model coefficients. The HGPT2 meteorological parameters were used to process 35 GNSS sites belonging to the International GNSS Service (IGS) using the GAMIT/GLOBK software package. Results show a decreased root-mean-square error (RMSE) and bias values relative to the most used zenith delay models, with a significant impact on the height component. The HGPT2 was developed to be applied in the most diverse areas that can significantly benefit from an ERA5 full-resolution model.

scholarly journals Temperature and Relative Humidity Profile Retrieval from Fengyun-3D/HIRAS in the Arctic Region

2021 ◽  
Vol 13 (10) ◽  
pp. 1884
Author(s):  
Jingjing Hu ◽  
Yansong Bao ◽  
Jian Liu ◽  
Hui Liu ◽  
George P. Petropoulos ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Real Time ◽  
Wide Spectrum ◽  
Warm Season ◽  
Arctic Region ◽  
Cold Season ◽  
The Arctic ◽  
Practical Applications ◽  
A New Technique ◽  
The Arctic Region

The acquisition of real-time temperature and relative humidity (RH) profiles in the Arctic is of great significance for the study of the Arctic’s climate and Arctic scientific research. However, the operational algorithm of Fengyun-3D only takes into account areas within 60°N, the innovation of this work is that a new technique based on Neural Network (NN) algorithm was proposed, which can retrieve these parameters in real time from the Fengyun-3D Hyperspectral Infrared Radiation Atmospheric Sounding (HIRAS) observations in the Arctic region. Considering the difficulty of obtaining a large amount of actual observation (such as radiosonde) in the Arctic region, collocated ERA5 data from European Centre for Medium-Range Weather Forecasts (ECMWF) and HIRAS observations were used to train the neural networks (NNs). Brightness temperature and training targets were classified using two variables: season (warm season and cold season) and surface type (ocean and land). NNs-based retrievals were compared with ERA5 data and radiosonde observations (RAOBs) independent of the NN training sets. Results showed that (1) the NNs retrievals accuracy is generally higher on warm season and ocean; (2) the root-mean-square error (RMSE) of retrieved profiles is generally slightly higher in the RAOB comparisons than in the ERA5 comparisons, but the variation trend of errors with height is consistent; (3) the retrieved profiles by the NN method are closer to ERA5, comparing with the AIRS products. All the results demonstrated the potential value in time and space of NN algorithm in retrieving temperature and relative humidity profiles of the Arctic region from HIRAS observations under clear-sky conditions. As such, the proposed NN algorithm provides a valuable pathway for retrieving reliably temperature and RH profiles from HIRAS observations in the Arctic region, providing information of practical value in a wide spectrum of practical applications and research investigations alike.All in all, our work has important implications in broadening Fengyun-3D’s operational implementation range from within 60°N to the Arctic region.

scholarly journals Role of nanostructured polymers on the improvement of electrical response-based relative humidity sensors

2016 ◽  
Vol 225 ◽  
pp. 96-108 ◽  
Author(s):  
I. Fratoddi ◽  
A. Bearzotti ◽  
I. Venditti ◽  
C. Cametti ◽  
M.V. Russo
Keyword(s):  
Relative Humidity ◽  
Electrical Response ◽  
Nanostructured Polymers ◽  
Humidity Sensors

Calibrating an optical fiber humidity sensor and applying it in real-time monitoring of relative humidity in fresh concrete

2013 ◽  
Vol 11 (9) ◽  
pp. 090604-90606 ◽  
Author(s):  
Xiaokang Zhang Xiaokang Zhang ◽  
Zhuoyong Deng Zhuoyong Deng ◽  
Hanlang Xu Hanlang Xu
Keyword(s):  
Relative Humidity ◽  
Optical Fiber ◽  
Real Time ◽  
Humidity Sensor ◽  
Fresh Concrete ◽  
Real Time Monitoring

Health-related quality of life and the physician–patient alliance: a preliminary investigation of ultra-brief, real-time measures for primary care

2018 ◽  
Vol 27 (12) ◽  
pp. 3275-3279
Author(s):  
Clay Graybeal ◽  
Brian DeSantis ◽  
Barry L. Duncan ◽  
Robert J. Reese ◽  
Kathryn Brandt ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Primary Care ◽  
Real Time ◽  
Preliminary Investigation ◽  
Health Related Quality ◽  
Related Quality ◽  
Health Related ◽  
Physician Patient
Sign in / Sign up

Export Citation Format

Share Document