A method to improve the accuracy of continuous measuring of vertical profiles of temperature and water vapor density by means of a ground-based microwave radiometer

2013 ◽  
Vol 122 ◽  
pp. 43-54 ◽  
Author(s):  
J.L. Sánchez ◽  
R. Posada ◽  
E. García-Ortega ◽  
L. López ◽  
J.L. Marcos
Keyword(s):  
Water Vapor ◽  
Microwave Radiometer ◽  
Vertical Profiles ◽  
Vapor Density ◽  
Continuous Measuring

Ground-Based Microwave Radiometer Profiler Observations before a Heavy Rainfall

2011 ◽  
Vol 137 ◽  
pp. 312-315
Author(s):  
Wen Jing Xu ◽  
Hong Yan Liu
Keyword(s):  
Water Vapor ◽  
Temporal Resolution ◽  
Density Profile ◽  
Heavy Rainfall ◽  
Microwave Radiometer ◽  
Cloud Water ◽  
Vapor Density ◽  
Apparent Change

Ground-based 12-channel microwave radiometer profiler TP/WVP-3000 can provide temperature and vapor density profile per minute up to 10 km height. The observations feature apparent change before heavy rainfall obtained by TP/WVP-3000 is presented in this paper. It demonstrates the detailed thermodynamic features that the atmosphere becomes colder and drier above height 3-4 km about 9 hours before the rain, the integrated water vapor gradually increases from 5 cm to 9 cm, the integrated cloud water change from near zero to 15 mm and the vapor density also increases rapidly about half an hour before the rain, which can be concluded that the radiometer profiler is able to improve the understanding of mesoscale weather in this case due to the profiler significantly improves the temporal resolution of atmospheric thermodynamic observations.

scholarly journals The Seasonal and Diurnal Cycles of Refractivity and Anomalous Propagation in the Sahelian Area from Microwave Radiometric Profiling

2016 ◽  
Vol 33 (10) ◽  
pp. 2095-2112 ◽  
Author(s):  
Valentin Louf ◽  
Olivier Pujol ◽  
Henri Sauvageot
Keyword(s):  
Water Vapor ◽  
Microwave Radiometer ◽  
Radar Data ◽  
Vertical Profiles ◽  
Microwave Propagation ◽  
Diurnal Cycles ◽  
Propagation Regime ◽  
Strong Amplitude ◽  
Anomalous Propagation ◽  
One Year

AbstractThe Sahelian zone of West Africa is a semiarid area where strong amplitude of the seasonal and diurnal cycles of water vapor and temperature is observed. One year of continuous observation of vertical profiles of water vapor and temperature gathered from Niamey, Niger, with a profiling microwave radiometer is used to analyze the climatology of refractivity and microwave propagation regimes in the low troposphere. Seasonal and diurnal cycles of refractivity and ground-based radar anomalous propagation are emphasized. It is shown that the combined effect of water vapor and temperature vertical gradients is responsible for strong seasonal and diurnal cycles of the ducting propagation regime. Statistics of propagation regimes are given. The probability density functions of the refractivity gradient are found lognormally distributed. Three months of C-band radar data simultaneous with the profiling microwave radiometer observations have also been collected. Relations between the vertical refractivity gradient and the ground-based radar anomalous propagation echoes (APE) are illustrated and discussed. APE spatial distributions are found strongly related to the main features of the orography and topography inside the radar-observed area. Contingency tests show that the probability for APE to be linked to ducting is higher than 95%. In addition, this paper suggests that observing the refractivity vertical profiles from a microwave radiometer profiler located close to a meteorological radar provides information on whether anomalous propagation has to be considered as a potential cause of spurious signal in the measured reflectivity field.

The Analysis of Atmospheric Water Vapor Based on Ground-Based Microwave Radiometer

2012 ◽  
Vol 500 ◽  
pp. 335-340
Author(s):  
Jie Ying He ◽  
Feng Lin Sun ◽  
Sheng Wei Zhang ◽  
Yu Zhang
Keyword(s):  
Neural Network ◽  
Water Vapor ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Microwave Radiometer ◽  
Mean Square ◽  
Vapor Density ◽  
China Meteorological Administration ◽  
Density Profiles

The paper introduces a widely used atmospheric absorption models: MPM by Liebe in 1989. Using this absorption model, the paper simulates the temperature and humidity weighting functions and brightness temperature according to the different frequencies and bandwidth of the multi-channel ground-based microwave radiometer. The results show that simulated brightness temperatures are very well agreement with the observation values with an acceptable root mean square error. This paper uses widely used retrieval method of artificial neural network to obtain the water vapor density profiles and calculates the root mean square error of each dataset. Also, to improve the accuracy of retrievals, this paper adopts multi-layers neural network which has two hidden layers. The results show that the retrievals of water vapor density profiles based on ground-based microwave radiometer are agreement with the water vapor density profile which is observed by radiosonde. Grant Nos. GYHY200906035 China Meteorological Administration nonprofit sector (meteorology) special research

A Study of a Retrieval Method for Temperature and Humidity Profiles from Microwave Radiometer Observations Based on Principal Component Analysis and Stepwise Regression

2011 ◽  
Vol 28 (3) ◽  
pp. 378-389 ◽  
Author(s):  
Haobo Tan ◽  
Jietai Mao ◽  
Huanhuan Chen ◽  
P. W. Chan ◽  
Dui Wu ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Water Vapor ◽  
Stepwise Regression ◽  
Microwave Radiometer ◽  
Principal Component ◽  
Component Analysis ◽  
Mean Square ◽  
Vapor Density ◽  
Retrieval Method ◽  
Brightness Temperatures

Abstract This paper discusses the application of principal component analysis and stepwise regression in the retrieval of vertical profiles of temperature and humidity based on the measurements of a 35-channel microwave radiometer. It uses the radiosonde data of 6 yr from Hong Kong, China, and the monochromatic radiative transfer model (MonoRTM) to calculate the brightness temperatures of the 35 channels of the radiometer. The retrieval of the atmospheric profile is then established based on principal component analysis and stepwise regression. The accuracy of the retrieval method is also analyzed. Using an independent sample, the root-mean-square error of the retrieved temperature is less than 1.5 K, on average, with better retrieval results in summer than in winter. Likewise, the root-mean-square error of the retrieved water vapor density reaches a maximum value of 1.4 g m−3 between 0.5 and 2 km, and is less than 1 g m−3 for all other heights. The retrieval method is then applied to the actual measured brightness temperatures by the 35-channel microwave radiometer at a station in Nansha, China. It is shown that the statistical model as developed in this paper has better retrieval results than the profiles obtained from the neural network as supplied with the radiometer. From numerical analysis, the error with the water vapor density retrieval is found to arise from the treatment of cloud liquid water. Finally, the retrieved profiles from the radiometer are studied for two typical weather phenomena during the observation period, and the retrieved profiles using the method discussed in the present paper is found to capture the evolution of the atmospheric condition very well.

scholarly journals Estimating Water Vapor Using Signals from Microwave Links below 25 GHz

2021 ◽  
Vol 13 (8) ◽  
pp. 1409
Author(s):  
Kun Song ◽  
Xichuan Liu ◽  
Taichang Gao ◽  
Peng Zhang
Keyword(s):  
Water Vapor ◽  
Weather Forecasting ◽  
Water Cycle ◽  
Correlation Coefficients ◽  
Support Vector ◽  
Vapor Density ◽  
Measurement Resolution ◽  
Sensing Model ◽  
Numerical Weather Forecasting ◽  
Mean Square Errors

Water vapor is a key element in both the greenhouse effect and the water cycle. However, water vapor has not been well studied due to the limitations of conventional monitoring instruments. Recently, estimating rain rate by the rain-induced attenuation of commercial microwave links (MLs) has been proven to be a feasible method. Similar to rainfall, water vapor also attenuates the energy of MLs. Thus, MLs also have the potential of estimating water vapor. This study proposes a method to estimate water vapor density by using the received signal level (RSL) of MLs at 15, 18, and 23 GHz, which is the first attempt to estimate water vapor by MLs below 20 GHz. This method trains a sensing model with prior RSL data and water vapor density by the support vector machine, and the model can directly estimate the water vapor density from the RSLs without preprocessing. The results show that the measurement resolution of the proposed method is less than 1 g/m3. The correlation coefficients between automatic weather stations and MLs range from 0.72 to 0.81, and the root mean square errors range from 1.57 to 2.31 g/m3. With the large availability of signal measurements from communications operators, this method has the potential of providing refined data on water vapor density, which can contribute to research on the atmospheric boundary layer and numerical weather forecasting.

scholarly journals New Gridded Product for the Total Columnar Atmospheric Water Vapor over Ocean Surface Constructed from Microwave Radiometer Satellite Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2402
Author(s):  
Weifu Sun ◽  
Jin Wang ◽  
Yuheng Li ◽  
Junmin Meng ◽  
Yujia Zhao ◽  
...  
Keyword(s):  
Water Vapor ◽  
Microwave Radiometer ◽  
Atmospheric Water Vapor ◽  
Global Ocean ◽  
Optimal Interpolation ◽  
Fusion Product ◽  
Mean Deviation ◽  
Atmospheric Water ◽  
Absolute Deviation ◽  
Better Than

Based on the optimal interpolation (OI) algorithm, a daily fusion product of high-resolution global ocean columnar atmospheric water vapor with a resolution of 0.25° was generated in this study from multisource remote sensing observations. The product covers the period from 2003 to 2018, and the data represent a fusion of microwave radiometer observations, including those from the Special Sensor Microwave Imager Sounder (SSMIS), WindSat, Advanced Microwave Scanning Radiometer for Earth Observing System sensor (AMSR-E), Advanced Microwave Scanning Radiometer 2 (AMSR2), and HY-2A microwave radiometer (MR). The accuracy of this water vapor fusion product was validated using radiosonde water vapor observations. The comparative results show that the overall mean deviation (Bias) is smaller than 0.6 mm; the root mean square error (RMSE) and standard deviation (SD) are better than 3 mm, and the mean absolute deviation (MAD) and correlation coefficient (R) are better than 2 mm and 0.98, respectively.

scholarly journals Water vapor transport in the lower mesosphere of the subtropics: a trajectory analysis

2008 ◽  
Vol 8 (23) ◽  
pp. 7273-7280 ◽  
Author(s):  
T. Flury ◽  
S. C. Müller ◽  
K. Hocke ◽  
N. Kämpfer
Keyword(s):  
Water Vapor ◽  
Trajectory Analysis ◽  
Microwave Radiometer ◽  
Rotational Transition ◽  
Transport Processes ◽  
Water Vapor Transport ◽  
Transition Line ◽  
Wind Fields ◽  
Large Variability ◽  
Northern India

Abstract. The Institute of Applied Physics operates an airborne microwave radiometer AMSOS that measures the rotational transition line of water vapor at 183.3 GHz. Water vapor profiles are retrieved for the altitude range from 15 to 75 km along the flight track. We report on a water vapor enhancement in the lower mesosphere above India and the Arabian Sea. The measurements took place on our flight from Switzerland to Australia and back in November 2005 conducted during EC- project SCOUT-O3. We find an enhancement of up to 25% in the lower mesospheric H2O volume mixing ratio measured on the return flight one week after the outward flight. The origin of the air is traced back by means of a trajectory model in the lower mesosphere and wind fields from ECMWF. During the outward flight the air came from the Atlantic Ocean around 25 N and 40 W. On the return flight the air came from northern India and Nepal around 25 N and 90 E. Mesospheric H2O measurements from Aura/MLS confirm the transport processes of H2O derived by trajectory analysis of the AMSOS data. Thus the large variability of H2O VMR during our flight is explained by a change of the winds in the lower mesosphere. This study shows that trajectory analysis can be applied in the mesosphere and is a powerful tool to understand the large variability in mesospheric H2O.

scholarly journals A Lidar at Clermont-Ferrand—France to describe the boundary layer dynamics, aerosols, cirrus and tropospheric water vapor

2018 ◽  
Vol 176 ◽  
pp. 05047
Author(s):  
J.L. Baray ◽  
P. Fréville ◽  
N. Montoux ◽  
A. Chauvigné ◽  
D. Hadad ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Water Vapor ◽  
Vertical Profiles ◽  
Raman Lidar ◽  
Tropospheric Aerosols ◽  
Boundary Layer Dynamics

A Rayleigh-Mie-Raman LIDAR provides vertical profiles of tropospheric variables at Clermont-Ferrand (France) since 2008, in order to describe the boundary layer dynamics, tropospheric aerosols, cirrus and water vapor. It is included in the EARLINET network. We performed hardware/software developments in order to upgrade the quality, calibration and improve automation. We present an overview of the system and some examples of measurements and a preliminary geophysical analysis of the data.

scholarly journals Uncertainties of ground-based microwave radiometer retrievals in zenith and off-zenith observations under snow conditions

2017 ◽  
Vol 10 (1) ◽  
pp. 155-165 ◽  
Author(s):  
Wengang Zhang ◽  
Guirong Xu ◽  
Yuanyuan Liu ◽  
Guopao Yan ◽  
Dejun Li ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Microwave Radiometer ◽  
Retrieval Algorithm ◽  
Mean Square ◽  
Atmospheric Conditions ◽  
Vapor Density ◽  
Heavy Snowfall ◽  
Snow Conditions ◽  
The Impact ◽  
Mean Square Errors

Abstract. This paper is to investigate the uncertainties of microwave radiometer (MWR) retrievals in snow conditions and also explore the discrepancies of MWR retrievals in zenith and off-zenith observations. The MWR retrievals were averaged in a ±15 min period centered at sounding times of 00:00 and 12:00 UTC and compared with radiosonde observations (RAOBs). In general, the MWR retrievals have a better correlation with RAOB profiles in off-zenith observations than in zenith observations, and the biases (MWR observations minus RAOBs) and root mean square errors (RMSEs) between MWR and RAOB are also clearly reduced in off-zenith observations. The biases of temperature, relative humidity, and vapor density decrease from 4.6 K, 9 %, and 1.43 g m−3 in zenith observations to −0.6 K, −2 %, and 0.10 g m−3 in off-zenith observations, respectively. The discrepancies between MWR retrievals and RAOB profiles by altitude present the same situation. Cases studies show that the impact of snow on accuracies of MWR retrievals is more serious in heavy snowfall than in light snowfall, but off-zenith observation can mitigate the impact of snowfall. The MWR measurements become less accurate in snowfall mainly due to the retrieval algorithm, which does not consider the effect of snow, and the accumulated snow on the top of the radome increases the signal noise of MWR measurements. As the snowfall drops away by gravity on the sides of the radome, the off-zenith observations are more representative of the atmospheric conditions for RAOBs.

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