Estimating GPS radio occultation observation error standard deviations over China using the three‐cornered hat method

2020 ◽  
Author(s):  
X. Xu ◽  
X. Zou
Keyword(s):  
Radio Occultation ◽  
Observation Error ◽  
Gps Radio Occultation ◽  
Radio Occultation Observation ◽  
Standard Deviations

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.

Improvement in the Use of an Operational Constellation of GPS Radio Occultation Receivers in Weather Forecasting

2010 ◽  
Vol 25 (2) ◽  
pp. 749-767 ◽  
Author(s):  
L. Cucurull
Keyword(s):  
Radio Occultation ◽  
Weather Forecasting ◽  
Model Performance ◽  
Observation Error ◽  
Gps Radio Occultation ◽  
Additional Information ◽  
Model Skill ◽  
Global Data Assimilation System ◽  
Control Procedures ◽  
Environmental Prediction

Abstract As of May 2007, the National Centers for Environmental Prediction (NCEP) implemented a new Global Data Assimilation System. This system incorporated the assimilation of global positioning system (GPS) radio occultation (RO) profiles from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) mission, which was launched in April 2006. Since then, this new type of observation has been shown to provide additional information on the thermodynamic state of the atmosphere, resulting in a significant increase in the model skill. Recent updates of the analysis and modeling codes have required a revision of the algorithm that assimilates GPS RO data. In addition, some modifications in the processing of the observations have further enhanced the need for a revisiting of the assimilation code. Better characterizations of the quality control procedures, observation error structure, and forward modeling for the GPS RO observations are described. The updated system significantly improves the data usage, in particular in the tropics. Different sets of the atmospheric refractive indices are also evaluated in this study. The model performance is proven to be quite sensitive to the chosen coefficients and a reevaluation of these constants is recommended within the GPS community. The new assimilation configuration results in an improvement in the anomaly correlation scores for the Southern Hemisphere extratropics (∼4.5 h for the 500-mb geopotential heights at day 7) and a reduction of the high- and low-level tropical wind errors. Overall, the benefits of using COSMIC on top of all the other observations used in the operational system are still very significant. The loss in model skill when COSMIC is removed from the observing system is remarkable at day 4 (∼8 h) and steadily increases beyond 12 h with the extended forecast range.

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.

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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