scholarly journals Medium- and small-scale ionospheric irregularities detected by GPS radio occultation method

2005 ◽  
Vol 32 (9) ◽  
Author(s):  
K. Tsybulya
2008 ◽  
Vol 35 (14) ◽  
Author(s):  
C. Arras ◽  
J. Wickert ◽  
G. Beyerle ◽  
S. Heise ◽  
T. Schmidt ◽  
...  

2011 ◽  
Vol 4 (8) ◽  
pp. 1627-1636 ◽  
Author(s):  
T. Tsuda ◽  
X. Lin ◽  
H. Hayashi ◽  

Abstract. GPS radio occultation (RO) is characterized by high accuracy and excellent height resolution, which has great advantages in analyzing atmospheric structures including small-scale vertical fluctuations. The vertical resolution of the geometrical optics (GO) method in the stratosphere is about 1.5 km due to Fresnel radius limitations, but full spectrum inversion (FSI) can provide superior resolutions. We applied FSI to COSMIC GPS-RO profiles from ground level up to 30 km altitude, although basic retrieval at UCAR/CDAAC sets the sewing height from GO to FSI below the tropopause. We validated FSI temperature profiles with routine high-resolution radiosonde data in Malaysia and North America collected within 400 km and about 30 min of the GPS RO events. The average discrepancy at 10–30 km altitude was less than 0.5 K, and the bias was equivalent with the GO results. Using the FSI results, we analyzed the vertical wave number spectrum of normalized temperature fluctuations in the stratosphere at 20–30 km altitude, which exhibits good consistency with the model spectra of saturated gravity waves. We investigated the white noise floor that tends to appear at high wave numbers, and the substantial vertical resolution of the FSI method was estimated as about 100–200 m in the lower stratosphere. We also examined a criterion for the upper limit of the FSI profiles, beyond which bending angle perturbations due to system noises, etc., could exceed atmospheric excess phase fluctuations. We found that the FSI profiles can be used up to about 28 km in studies of temperature fluctuations with vertical wave lengths as short as 0.5 km.


2011 ◽  
Vol 4 (2) ◽  
pp. 2071-2097
Author(s):  
T. Tsuda ◽  
X. Lin ◽  
H. Hayashi ◽  

Abstract. GPS radio occultation (RO) is characterized by high accuracy and excellent height resolution, which has great advantages in analyzing atmospheric structures including small-scale vertical fluctuations. The vertical resolution of the geometrical optics (GO) method in the stratosphere is about 1.5 km due to Fresnel radius limitations, but full spectrum inversion (FSI) can provide superior resolutions. We applied FSI to COSMIC GPS-RO profiles from ground level up to 30 km altitude, although basic retrieval at UCAR/CDAAC sets the sewing height from GO to FSI below the tropopause. We validated FSI temperature profiles with routine high-resolution radiosonde data in Malaysia and North America collected within 400 km and about 30 min of the GPS RO events. The average discrepancy at 10–30 km altitude was less than 0.5 K, and the bias was equivalent with the GO results. Using the FSI results, we analyzed the vertical wave number spectrum of normalized temperature fluctuations in the stratosphere at 20–30 km altitude, which exhibits good consistency with the model spectra of saturated gravity waves. We investigated the white noise floor that tends to appear at high wave numbers, and the substantial vertical resolution of the FSI method was estimated as about 100–200 m in the lower stratosphere. We also examined a criterion for the upper limit of the FSI profiles, beyond which bending angle perturbations due to system noises, etc, could exceed atmospheric excess phase fluctuations. We found that the FSI profiles can be used up to about 28 km in studies of temperature fluctuations with vertical wave lengths as short as 0.5 km.


2009 ◽  
Vol 26 (7) ◽  
pp. 1398-1403 ◽  
Author(s):  
S. Sokolovskiy ◽  
W. Schreiner ◽  
C. Rocken ◽  
D. Hunt

Abstract GPS radio occultation remote sensing of the neutral atmosphere requires ionospheric correction of L1 and L2 signals. The ionosphere-corrected variables derived from radio occultation signals—such as the phase, Doppler, and bending angle—are affected by small-scale ionospheric effects that are not completely eliminated by the ionospheric correction. They are also affected by noise from mainly the L2 signal. This paper introduces a simple method for optimal filtering of the L4 = L1 − L2 signal used to correct the L1 signal, which minimizes the combined effects of both the small-scale ionospheric residual effects and L2 noise on the ionosphere-corrected variables. Statistical comparisons to high-resolution numerical weather models from the European Centre for Medium-Range Weather Forecasts (ECMWF) validate that this increases the accuracy of radio occultation inversions in the stratosphere.


2004 ◽  
Vol 61 (7-12) ◽  
pp. 1055-1071
Author(s):  
N. N. Gerasimova ◽  
V. G. Sinitsin ◽  
Yu. M. Yampolski

2017 ◽  
Vol 919 (1) ◽  
pp. 48-51
Author(s):  
N.H. Javadov ◽  
R.A. Eminov ◽  
N.Ya. Ismailov

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.


2020 ◽  
Vol 13 (1) ◽  
pp. 1
Author(s):  
Xu Xu ◽  
Xiaolei Zou

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.


2014 ◽  
Vol 31 (9) ◽  
pp. 2008-2014 ◽  
Author(s):  
Xin Zhang ◽  
Ying-Hwa Kuo ◽  
Shu-Ya Chen ◽  
Xiang-Yu Huang ◽  
Ling-Feng Hsiao

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.


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