scholarly journals Application of AIRS Soundings to Afternoon Convection Forecasting and Nowcasting at Airports

Atmosphere ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 61
Author(s):  
Nan-Ching Yeh ◽  
Yao-Chung Chuang ◽  
Hsin-Shuo Peng ◽  
Chih-Ying Chen
Keyword(s):  
Predictive Accuracy ◽  
Atmospheric Stability ◽  
Stability Index ◽  
Precipitable Water ◽  
Radiosonde Data ◽  
Observation Data ◽  
Accuracy Rate ◽  
Coverage Area ◽  
Forecast Precision ◽  
Data Coverage

In Taiwan, the frequency of afternoon convection increases in summer (July and August), and the peak hour of afternoon convection occurs at 1500–1600 local solar time (LST). Afternoon convection events are forecasted based on the atmospheric stability index, as computed from the 0800 LST radiosonde data. However, the temporal and spatial resolution and forecast precision are not satisfactory. This study used the observation data of Aqua satellite overpass near Taiwan around 1–3 h before the occurrence of afternoon convection. Its advantages are that it improves the prediction accuracy and increases the data coverage area, which means that more airports can use results of this research, especially those without radiosondes. In order to determine the availability of Atmospheric Infrared Sounder (AIRS) in Taiwan, 2010–2016 AIRS and radiosonde-sounding data were used to determine the accuracy of AIRS. This study also used 2017–2018 AIRS data to establish K index (KI) and total precipitable water (TPW) thresholds for the occurrence of afternoon convection of four airports in Taiwan. Finally, the KI and TPW were calculated using the independent AIRS atmospheric sounding (2019–2020) to forecast the occurrence of afternoon convection at each airport. The average predictive accuracy rate of the four airports is 84%. Case studies at Hualien Airport show the average predictive accuracy rate of this study is 81.8%, which is 9.1% higher than that of the traditional sounding forecast (72.7%) during the same period. Research results show that using AIRS data to predict afternoon convection in this study could not only increase data coverage area but also improve the accuracy of the prediction effectively.

Clinical utility of Shabda and Sparsha Pareeksha in evaluation of Prakruta and Vaikruta Garbhavastha

2016 ◽  
Vol 1 (2) ◽  
Author(s):  
Priyanka T K ◽  
V.N. K. Usha ◽  
Sucheta Kumari M
Keyword(s):  
Clinical Study ◽  
Clinical Utility ◽  
Neonatal Outcome ◽  
Predictive Accuracy ◽  
Cost Effective ◽  
Well Being ◽  
Prospective Clinical Study ◽  
Clinical Tool ◽  
Accuracy Rate ◽  
Fetal Pathology

Garbha is a conglomeration of biological mass with different strata including consciousness, needs an innovative clinical tool to evaluate its well being, which proves safe, potent, cost-effective and noninvasive. The idea of taking up this study was to sensitively predict the Prakrutavastha or well being w.r.t Garbha-pushti and ongoing Fetal Pathology, Vaikrutavastha w.s.r Garbhavyapads for a sharp interference to get a possible best neonatal outcome. The objective of this study was to calculate the predictive accuracy of evaluation of Garbhaspandanam on external Shabda and Sparsha Pareeksha. A Prospective Clinical study of Garbhaspandanam (FHS and FM) with external Shabda and Sparsha stimulation on maternal abdomen, from 24th week onwards was conducted in a cohort of 30 Singleton Pregnant women at Dept. of Prasuti Tantra and Stri Roga, S.D.M.C.A. Hospital, Udupi. Among the 9 cases in abnormal category, 2 cases had gone for IUD and one case though placed in abnormal category had responded relatively well to Shabda and Sparsha Pareeksha which may be due to the proper antenatal care and intervention given along with the patient’s Vatakara Nidana Parivarjana. Predictive Accuracy Rate on Shabda and Sparsha Pareeksha showed, FHS 70%, FM 76.7%; FHS 73.3%, FM 66.7% respectively. Shabda and Sparshapareeksha can be utilized as the Garbha - chetana - dyodakalakshana and can be performed as a routine antenatal bedside procedure, which can fairly detect the Prakruta and Vaikrutavastha of Garbha w.r.t Pushti. However larger prospective studies are required.

Evaluation of daily and diurnal signals of total precipitable water (TPW) over the Indian Ocean based on TMI retrieved 3-day composite estimates and radiosonde data

2007 ◽  
Vol 27 (6) ◽  
pp. 761-770 ◽  
Author(s):  
V. Sajith ◽  
Jimmy O. Adegoke ◽  
Santosh K. Raghavan ◽  
H. S. Ram Mohan ◽  
Vinod Kumar ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Precipitable Water ◽  
Radiosonde Data ◽  
Total Precipitable Water ◽  
The Indian Ocean

scholarly journals Interannual variability of precipitable water

1996 ◽  
Vol 14 (4) ◽  
pp. 464-467 ◽  
Author(s):  
R. P. Kane
Keyword(s):  
Interannual Variability ◽  
Southern Hemisphere ◽  
Northern Hemisphere ◽  
Precipitable Water ◽  
Radiosonde Data ◽  
High Latitudes ◽  
Zonal Winds ◽  
Low Latitudes ◽  
Linear Trends

Abstract. The 12-month running means of the surface-to-500 mb precipitable water obtained from analysis of radiosonde data at seven selected locations showed three types of variability viz: (1) quasi-biennial oscillations; these were different in nature at different latitudes and also different from the QBO of the stratospheric tropical zonal winds; (2) decadal effects; these were prominent at middle and high latitudes and (3) linear trends; these were prominent at low latitudes, up trends in the Northern Hemisphere and downtrends in the Southern Hemisphere.

scholarly journals Evaluation of MODIS Water Vapour Products over ALGERIA using Radiosonde Data

2021 ◽  
Vol 44 ◽  
Author(s):  
Houaria Namaoui ◽  
Salem Kahlouche ◽  
Ahmed Hafidh Belbachir
Keyword(s):  
Water Vapour ◽  
Satellite Data ◽  
Correlation Coefficients ◽  
Precipitable Water ◽  
Radiosonde Data ◽  
Precipitable Water Vapour ◽  
Total Precipitable Water ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Remote sensing of atmospheric water vapour using GNSS and Satellite data has become an efficient tool in meteorology and climate research. Many satellite data have been increasingly used to measure the content of water vapour in the atmosphere and to characterize its temporal and spatial variations. In this paper, we have used observations from radiosonde data collected from three stations (Algiers, Bechar and Tamanrasset) in Algeria from January to December 2012 to evaluate Moderate Resolution Imaging Spectroradiometer (MODIS) total precipitable water vapour (PWV) products. Results show strong agreement between the total precipitable water contents estimated based on radiosondes observations and the ones measured by the sensor MODIS with the correlation coefficients in the range 0.69 to 0.95 and a mean bias, which does not exceed 1.5.  

scholarly journals Soil Moisture-Boundary Layer Feedbacks on the Loess Plateau in China Using Radiosonde Data with 1-D Atmospheric Boundary Layer Model

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1619
Author(s):  
Yingsai Ma ◽  
Xianhong Meng ◽  
Yinhuan Ao ◽  
Ye Yu ◽  
Guangwei Li ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Atmospheric Boundary Layer ◽  
Loess Plateau ◽  
Atmospheric Stability ◽  
Heat Fluxes ◽  
Radiosonde Data ◽  
Atmospheric Conditions ◽  
The Loess Plateau ◽  
The Impact

The Loess Plateau is one land-atmosphere coupling hotspot. Soil moisture has an influence on atmospheric boundary layer development under specific early-morning atmospheric thermodynamic structures. This paper investigates the sensitivity of atmospheric convection to soil moisture conditions over the Loess Plateau in China by using the convective triggering potential (CTP)—humidity index (HIlow) framework. The CTP indicates atmospheric stability and the HIlow indicates atmospheric humidity in the low-level atmosphere. By comparing the model outcomes with the observations, the one-dimensional model achieves realistic daily behavior of the radiation and surface heat fluxes and the mixed layer properties with appropriate modifications. New CTP-HIlow thresholds for soil moisture-atmosphere feedbacks are found in the Loess Plateau area. By applying the new thresholds with long-time scales sounding data, we conclude that negative feedback is dominant in the north and west portion of the Loess Plateau; positive feedback is predominant in the south and east portion. In general, this framework has predictive significance for the impact of soil moisture on precipitation. By using this new CTP-HIlow framework, we can determine under what atmospheric conditions soil moisture can affect the triggering of precipitation and under what atmospheric conditions soil moisture has no influence on the triggering of precipitation.

Precipitable water vapor estimation in India from GPS-derived zenith delays using radiosonde data

2013 ◽  
Vol 123 (3-4) ◽  
pp. 209-220 ◽  
Author(s):  
Dinesh Singh ◽  
Jayanta Kumar Ghosh ◽  
Deepak Kashyap
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Radiosonde Data

scholarly journals Characterization of downwelling radiance measured from a ground-based microwave radiometer using numerical weather prediction model data

2016 ◽  
Vol 9 (1) ◽  
pp. 281-293 ◽  
Author(s):  
M.-H. Ahn ◽  
H. Y. Won ◽  
D. Han ◽  
Y.-H. Kim ◽  
J.-C. Ha
Keyword(s):  
Prediction Model ◽  
Numerical Weather Prediction ◽  
Reference Data ◽  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Radiosonde Data ◽  
Absolute Calibration ◽  
Observation Data ◽  
Numerical Weather ◽  
Better Than

Abstract. The ground-based microwave sounding radiometers installed at nine weather stations of Korea Meteorological Administration alongside with the wind profilers have been operating for more than 4 years. Here we apply a process to assess the characteristics of the observation data by comparing the measured brightness temperature (Tb) with reference data. For the current study, the reference data are prepared by the radiative transfer simulation with the temperature and humidity profiles from the numerical weather prediction model instead of the conventional radiosonde data. Based on the 3 years of data, from 2010 to 2012, we were able to characterize the effects of the absolute calibration on the quality of the measured Tb. We also showed that when clouds are present the comparison with the model has a high variability due to presence of cloud liquid water therefore making cloudy data not suitable for assessment of the radiometer's performance. Finally we showed that differences between modeled and measured brightness temperatures are unlikely due to a shift in the selection of the center frequency but more likely due to spectroscopy issues in the wings of the 60 GHz absorption band. With a proper consideration of data affected by these two effects, it is shown that there is an excellent agreement between the measured and simulated Tb. The regression coefficients are better than 0.97 along with the bias value of better than 1.0 K except for the 52.28 GHz channel which shows a rather large bias and variability of −2.6 and 1.8 K, respectively.

An atmospheric stability index based on radon progeny measurements for the evaluation of primary urban pollution

2001 ◽  
Vol 35 (31) ◽  
pp. 5235-5244 ◽  
Author(s):  
Cinzia Perrino ◽  
Adriana Pietrodangelo ◽  
Antonio Febo
Keyword(s):  
Atmospheric Stability ◽  
Urban Pollution ◽  
Stability Index ◽  
Radon Progeny

scholarly journals Application of GNSS Methodologies to Obtain Precipitable Water Vapor (PWV) and Its Comparison with Radiosonde Data

Proceedings ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 24 ◽  
Author(s):  
Raquel Perdiguer-López ◽  
José Luis Berné-Valero ◽  
Natalia Garrido-Villén
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Weather Conditions ◽  
Precipitable Water Vapor ◽  
Radiosonde Data ◽  
Tropospheric Delay ◽  
The North ◽  
Radiosonde Station ◽  
Observation Method ◽  
North Of Spain

A processing methodology with GNSS observations to obtain Zenith Tropospheric Delay using Bernese GNSS Software version 5.2 is revised in order to obtain Precipitable Water Vapor (PWV). The most traditional PWV observation method is the radiosonde and it is often used as a standard to validate those derived from GNSS. For this reason, a location in the north of Spain, in A Coruña, which has a GNSS station with available data and also a radiosonde station, was chosen. Two GPS weeks, in different weather conditions were calculated. The result of the comparison between the GNSS- retrieved PWV and Radiosonde-PWV is explained in the last section of this paper.

scholarly journals A Method to Improve the Distribution of Observations in GNSS Water Vapor Tomography

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2526 ◽  
Author(s):  
Fei Yang ◽  
Jiming Guo ◽  
Junbo Shi ◽  
Lv Zhou ◽  
Yi Xu ◽  
...  
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Absolute Error ◽  
Satellite System ◽  
Observation Data ◽  
Radiosonde Station ◽  
Satellite Signal ◽  
Comparative Results ◽  
Global Navigation Satellite ◽  
Vapor Distribution

Water vapor is an important driving factor in the related weather processes in the troposphere, and its temporal-spatial distribution and change are crucial to the formation of cloud and rainfall. Global Navigation Satellite System (GNSS) water vapor tomography, which can reconstruct the water vapor distribution using GNSS observation data, plays an increasingly important role in GNSS meteorology. In this paper, a method to improve the distribution of observations in GNSS water vapor tomography is proposed to overcome the problem of the relatively concentrated distribution of observations, enable satellite signal rays to penetrate more tomographic voxels, and improve the issue of overabundance of zero elements in a tomographic matrix. Numerical results indicate that the accuracy of the water vapor tomography is improved by the proposed method when the slant water vapor calculated by GAMIT is used as a reference. Comparative results of precipitable water vapor (PWV) and water vapor density (WVD) profiles from radiosonde station data indicate that the proposed method is superior to the conventional method in terms of the mean absolute error (MAE), standard deviations (STD), and root-mean-square error (RMS). Further discussion shows that the ill-condition of tomographic equation and the richness of data in the tomographic model need to be discussed separately.

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