An Adaptive Carrier Tracking Algorithm for Low Altitude Mountain-based GPS Radio Occultation Measurement

2017 ◽  
Author(s):  
Rong Yang ◽  
Yu Morton ◽  
Bo Han
Keyword(s):  
Radio Occultation ◽  
Tracking Algorithm ◽  
Gps Radio Occultation ◽  
Low Altitude ◽  
Radio Occultation Measurement

Optimum prediction of atmospheric temperature using GPS radio occultation measurements

2017 ◽  
Vol 919 (1) ◽  
pp. 48-51
Author(s):  
N.H. Javadov ◽  
R.A. Eminov ◽  
N.Ya. Ismailov
Keyword(s):  
Radio Occultation ◽  
General Procedure ◽  
Atmospheric Temperature ◽  
Mean Value ◽  
Optimization Criterion ◽  
Temperature Measurements ◽  
Gps Radio Occultation ◽  
Applied Optimization ◽  
Quadratic Deviation ◽  
The Mean

The matters of optimum forecasting atmospheric temperature using GPS radio occultation measurements are considered. The analysis of the available data regarding to the comparison of temperature measurements using radio occultation method and radiosondes was made. As a result it was concluded that the mean value of those results’ difference and also the mean quadratic deviation of these difference increases in common by increase of the forecasting time. In order to prevent surplus loading of telemetry channels and broadcasting inaccurate forecast values via them the optimization of general procedure of radio occultation temperature measurements are carried out using fine functions method. For optimization the concurrent parameters, changing on antiphase order are determined. It is found out that utilization of fine function method taking into account the applied optimization criterion and some limitation conditions make it possible to optimize the whole procedure of forecasting atmospheric temperature using the GPS radio occultation measurements.

scholarly journals Global 3D Features of Error Variances of GPS Radio Occultation and Radiosonde Observations

2020 ◽  
Vol 13 (1) ◽  
pp. 1
Author(s):  
Xu Xu ◽  
Xiaolei Zou
Keyword(s):  
Radio Occultation ◽  
Weather Prediction ◽  
Lower Troposphere ◽  
Error Variance ◽  
Specific Humidity ◽  
Temperature Error ◽  
Observation Error ◽  
Bending Angle ◽  
Gps Radio Occultation ◽  
Low Latitudes

Global Positioning System (GPS) radio occultation (RO) and radiosonde (RS) observations are two major types of observations assimilated in numerical weather prediction (NWP) systems. Observation error variances are required input that determines the weightings given to observations in data assimilation. This study estimates the error variances of global GPS RO refractivity and bending angle and RS temperature and humidity observations at 521 selected RS stations using the three-cornered hat method with additional ERA-Interim reanalysis and Global Forecast System forecast data available from 1 January 2016 to 31 August 2019. The global distributions, of both RO and RS observation error variances, are analyzed in terms of vertical and latitudinal variations. Error variances of RO refractivity and bending angle and RS specific humidity in the lower troposphere, such as at 850 hPa (3.5 km impact height for the bending angle), all increase with decreasing latitude. The error variances of RO refractivity and bending angle and RS specific humidity can reach about 30 N-unit2, 3 × 10−6 rad2, and 2 (g kg−1)2, respectively. There is also a good symmetry of the error variances of both RO refractivity and bending angle with respect to the equator between the Northern and Southern Hemispheres at all vertical levels. In this study, we provide the mean error variances of refractivity and bending angle in every 5°-latitude band between the equator and 60°N, as well as every interval of 10 hPa pressure or 0.2 km impact height. The RS temperature error variance distribution differs from those of refractivity, bending angle, and humidity, which, at low latitudes, are smaller (less than 1 K2) than those in the midlatitudes (more than 3 K2). In the midlatitudes, the RS temperature error variances in North America are larger than those in East Asia and Europe, which may arise from different radiosonde types among the above three regions.

Parallelization Strategies for the GPS Radio Occultation Data Assimilation with a Nonlocal Operator in the Weather Research and Forecasting Model

2014 ◽  
Vol 31 (9) ◽  
pp. 2008-2014 ◽  
Author(s):  
Xin Zhang ◽  
Ying-Hwa Kuo ◽  
Shu-Ya Chen ◽  
Xiang-Yu Huang ◽  
Ling-Feng Hsiao
Keyword(s):  
Data Assimilation ◽  
Radio Occultation ◽  
Weather Prediction ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Observation Operator ◽  
Gps Radio Occultation ◽  
Phase Observation ◽  
Excess Phase ◽  
Weather Research

Abstract The nonlocal excess phase observation operator for assimilating the global positioning system (GPS) radio occultation (RO) sounding data has been proven by some research papers to produce significantly better analyses for numerical weather prediction (NWP) compared to the local refractivity observation operator. However, the high computational cost and the difficulties in parallelization associated with the nonlocal GPS RO operator deter its application in research and operational NWP practices. In this article, two strategies are designed and implemented in the data assimilation system for the Weather Research and Forecasting Model to demonstrate the capability of parallel assimilation of GPS RO profiles with the nonlocal excess phase observation operator. In particular, to solve the parallel load imbalance problem due to the uneven geographic distribution of the GPS RO observations, round-robin scheduling is adopted to distribute GPS RO observations among the processing cores to balance the workload. The wall clock time required to complete a five-iteration minimization on a demonstration Antarctic case with 106 GPS RO observations is reduced from more than 3.5 h with a single processing core to 2.5 min with 106 processing cores. These strategies present the possibility of application of the nonlocal GPS RO excess phase observation operator in operational data assimilation systems with a cutoff time limit.

scholarly journals Impact of GPS Radio Occultation Refractivity Soundings on a Simulation of Typhoon Bilis (2006) upon Landfall

2009 ◽  
Vol 20 (1) ◽  
pp. 115 ◽  
Author(s):  
Mien-Tze Kueh ◽  
Ching-Yuang Huang ◽  
Shu-Ya Chen ◽  
Shu-Hua Chen ◽  
Chien-Ju Wang
Keyword(s):  
Radio Occultation ◽  
Gps Radio Occultation

scholarly journals GPS radio occultation with TerraSAR-X and TanDEM-X: sensitivity of lower troposphere sounding to the Open-Loop Doppler model

2014 ◽  
Vol 7 (12) ◽  
pp. 12719-12733 ◽  
Author(s):  
F. Zus ◽  
G. Beyerle ◽  
S. Heise ◽  
T. Schmidt ◽  
J. Wickert
Keyword(s):  
Radio Occultation ◽  
Weather Prediction ◽  
Lower Troposphere ◽  
Systematic Difference ◽  
Open Loop ◽  
Negative Bias ◽  
Upper Troposphere ◽  
Gps Radio Occultation ◽  
Global Positioning ◽  
Data Source

Abstract. The Global Positioning System (GPS) radio occultation (RO) technique provides valuable input for numerical weather prediction and is considered as a data source for climate related research. Numerous studies outline the high precision and accuracy of RO atmospheric soundings in the upper troposphere and lower stratosphere. In this altitude region (8–25 km) RO atmospheric soundings are considered to be free of any systematic error. In the tropical (30° S–30° N) Lower (<8 km) Troposphere (LT), this is not the case; systematic differences with respect to independent data sources exist and are still not completely understood. To date only little attention has been paid to the Open Loop (OL) Doppler model. Here we report on a RO experiment carried out on-board of the twin satellite configuration TerraSAR-X and TanDEM-X which possibly explains to some extent biases in the tropical LT. In two sessions we altered the OL Doppler model aboard TanDEM-X by not more than ±5 Hz with respect to TerraSAR-X and compare collocated atmospheric refractivity profiles. We find a systematic difference in the retrieved refractivity. The bias mainly stems from the tropical LT; there the bias reaches up to ±1%. Hence, we conclude that the negative bias (several Hz) of the OL Doppler model aboard TerraSAR-X introduces a negative bias (in addition to the negative bias which is primarily caused by critical refraction) in our retrieved refractivity in the tropical LT.

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