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.

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.

scholarly journals Evaluating the lower-tropospheric COSMIC GPS radio occultation sounding quality over the Arctic

2018 ◽  
Vol 11 (4) ◽  
pp. 2051-2066 ◽  
Author(s):  
Xiao Yu ◽  
Feiqin Xie ◽  
Chi O. Ao
Keyword(s):  
Data Processing ◽  
Radio Occultation ◽  
Weather Prediction ◽  
Lower Troposphere ◽  
Parametric Uncertainty ◽  
Ocean Surface ◽  
Specific Humidity ◽  
The Arctic ◽  
Near Surface ◽  
Active Research

Abstract. Lower-tropospheric moisture and temperature measurements are crucial for understanding weather prediction and climate change. Global Positioning System radio occultation (GPS RO) has been demonstrated as a high-quality observation technique with high vertical resolution and sub-kelvin temperature precision from the upper troposphere to the stratosphere. In the tropical lower troposphere, particularly the lowest 2 km, the quality of RO retrievals is known to be degraded and is a topic of active research. However, it is not clear whether similar problems exist at high latitudes, particularly over the Arctic, which is characterized by smooth ocean surface and often negligible moisture in the atmosphere. In this study, 3-year (2008–2010) GPS RO soundings from COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) over the Arctic (65–90° N) show uniform spatial sampling with average penetration depth within 300 m above the ocean surface. Over 70 % of RO soundings penetrate deep into the lowest 300 m of the troposphere in all non-summer seasons. However, the fraction of such deeply penetrating profiles reduces to only about 50–60 % in summer, when near-surface moisture and its variation increase. Both structural and parametric uncertainties of GPS RO soundings were also analyzed. The structural uncertainty (due to different data processing approaches) is estimated to be within  ∼  0.07 % in refractivity,  ∼  0.72 K in temperature, and  ∼  0.05 g kg−1 in specific humidity below 10 km, which is derived by comparing RO retrievals from two independent data processing centers. The parametric uncertainty (internal uncertainty of RO sounding) is quantified by comparing GPS RO with near-coincident radiosonde and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim profiles. A systematic negative bias up to  ∼  1 % in refractivity below 2 km is only seen in the summer, which confirms the moisture impact on GPS RO quality.

scholarly journals Analysis of GPS radio occultation data from the FORMOSAT-3/COSMIC and Metop/GRAS missions at CDAAC

2011 ◽  
Vol 4 (10) ◽  
pp. 2255-2272 ◽  
Author(s):  
W. Schreiner ◽  
S. Sokolovskiy ◽  
D. Hunt ◽  
C. Rocken ◽  
Y.-H. Kuo
Keyword(s):  
Noise Level ◽  
Radio Occultation ◽  
Signal To Noise Ratio ◽  
Lower Troposphere ◽  
Mean Difference ◽  
Bending Angle ◽  
Tropical Regions ◽  
Gps Radio Occultation ◽  
Single Difference ◽  
Bending Angles

Abstract. This study investigates the noise level and mission-to-mission stability of Global Positioning System (GPS) radio occultation (RO) neutral atmospheric bending angle data at the UCAR COSMIC Data Analysis and Archive Center (CDAAC). Data are used from two independently developed RO instruments currently flying in orbit on the FORMOSAT-3/COSMIC (F3C) and Metop/GRAS (GNSS Receiver for Atmospheric Sounding) missions. The F3C 50 Hz RO data are post-processed with a single-difference excess atmospheric phase algorithm, and the Metop/GRAS 50 Hz closed loop and raw sampling (down-sampled from 1000 Hz to 50 Hz) data are processed with a zero-difference algorithm. The standard deviations of the F3C and Metop/GRAS bending angles from climatology between 60 and 80 km altitude from June–December 2009 are approximately 1.78 and 1.13 μrad, respectively. The F3C standard deviation reduces significantly to 1.44 μrad when single-difference processing uses GPS satellites on the same side of the spacecraft. The higher noise level for F3C bending angles can be explained by additional noise from the reference link phase data that are required with single-difference processing. The F3C and Metop/GRAS mean bending angles differences relative to climatology during the same six month period are statistically significant and have values of −0.05 and −0.02 μrad, respectively. A comparison of ~13 500 collocated F3C and Metop/GRAS bending angle profiles over this six month period shows a similar mean difference of ~0.02 ± 0.02 μrad between 30 and 60 km impact heights that is marginally significant. The observed mean difference between the F3C and Metop/GRAS bending angles of ~0.02–0.03 μrad is quite small and illustrates the high degree of re-produceability and mission independence of the GPS RO data at high altitudes. Collocated bending angles between two F3C satellites from early in the mission differ on average by up to 0.5% near the surface due to systematically lower signal-to-noise ratio for one of the satellites. Results from F3C and Metop/GRAS differences in the lower troposphere suggest the Metop/GRAS bending angles are negatively biased compared to F3C with a maximum of several percents near the surface in tropical regions. This bias is related to different tracking depths (deeper in F3C) and data gaps in Metop/GRAS which make it impossible to process the data from both missions in exactly the same way.

scholarly journals Analysis of GPS radio occultation data from the FORMOSAT-3/COSMIC and Metop/GRAS missions at CDAAC

2011 ◽  
Vol 4 (2) ◽  
pp. 2433-2489
Author(s):  
W. Schreiner ◽  
S. Sokolovskiy ◽  
D. Hunt ◽  
C. Rocken ◽  
Y.-H. Kuo
Keyword(s):  
Noise Level ◽  
Radio Occultation ◽  
Signal To Noise Ratio ◽  
Lower Troposphere ◽  
Mean Difference ◽  
Bending Angle ◽  
Tropical Regions ◽  
Gps Radio Occultation ◽  
Single Difference ◽  
Bending Angles

Abstract. This study investigates the noise level and mission-to-mission stability of Global Positioning System (GPS) radio occultation (RO) neutral atmospheric bending angle data at the UCAR COSMIC Data Analysis and Archive Center (CDAAC). Data are used from two independently developed RO instruments currently flying in orbit on the FORMOSAT-3/COSMIC (F3C) and Metop/GRAS (GNSS Receiver for Atmospheric Sounding) missions. The F3C 50 Hz RO data are post-processed with a single-difference excess atmospheric phase algorithm, and the Metop/GRAS 50 Hz closed loop and raw sampling (down-sampled from 1000 Hz to 50 Hz) data are processed with a zero-difference algorithm. The standard deviations of the F3C and Metop/GRAS bending angles from climatology between 60 and 80 km altitude from June–December 2009 are approximately 1.78 and 1.13 μrad, respectively. The F3C standard deviation reduces significantly to 1.44 μrad when single-difference processing uses GPS satellites on the same side of the spacecraft. The higher noise level for F3C bending angles can be explained by additional noise from the reference link phase data that are required with single-difference processing. The F3C and Metop/GRAS mean bending angles differences relative to climatology during the same six month period are statistically significant and have values of −0.05 and −0.02 μrad, respectively. A comparison of ~13 500 collocated F3C and Metop/GRAS bending angle profiles over this six month period shows a similar mean difference of ~0.02 ± 0.02 μrad between 30 and 60 km impact heights that is marginally significant. The observed mean difference between the F3C and Metop/GRAS bending angles of ~0.02–0.03 μrad is quite small and illustrates the high degree of re-produceability and mission independence of the GPS RO data at high altitudes. Collocated bending angles between two F3C satellites from early in the mission differ on average by up to 0.5% near the surface due to systematically lower signal-to-noise ratio for one of the satellites. Results from F3C and Metop/GRAS differences in the lower troposphere suggest the Metop/GRAS bending angles are negatively biased compared to F3C with a maximum of several percents near the surface in tropical regions. This bias is related to different tracking depths (deeper in F3C) and data gaps in Metop/GRAS which make it impossible to process the data from both missions in exactly the same way.

scholarly journals Towards All-sky Assimilation of Microwave Temperature Sounding Channels in Environment Canada’s Global Deterministic Weather Prediction System

2021 ◽  
Author(s):  
Maziar Bani Shahabadi ◽  
Mark Buehner
Keyword(s):  
Standard Deviation ◽  
Weather Prediction ◽  
Lower Troposphere ◽  
Forecast Model ◽  
Specific Humidity ◽  
Horizontal Wind ◽  
Observation Error ◽  
Horizontal Wind Speed ◽  
Observation Operator ◽  
Background State

AbstractThe all-sky assimilation of radiances from microwave instruments is developed in the 4D-EnVar analysis system at Environment and Climate Change Canada (ECCC). Assimilation of cloud-affected radiances from Advanced Microwave Sounding Unit A (AMSUA) temperature sounding channels 4 and 5 for non-precipitating scenes over the ocean surface is the focus of this study. Cloud-affected radiances are discarded in the ECCC operational data assimilation system due to the limitations of forecast model physics, radiative transfer models, and the strong non-linearity of the observation operator. In addition to using symmetric estimate of innovation standard deviation for quality control, a state-dependent observation error inflation is employed at the analysis stage. The background state clouds are scaled by a factor of 0.5 to compensate for a systematic overestimation by the forecast model, before being used in the observation operator. The changes in the fit of the background state to observations show mixed results. The number of AMSUA channels 4 and 5 assimilated observations in the all-sky experiment is 5-12% higher than in the operational system. The all-sky approach improves temperature analysis when verified against ECMWF operational analysis in the areas where the extra cloud-affected observations were assimilated. Statistically significant reductions in error standard deviation by 1-4% for the analysis and forecasts of temperature, specific humidity, and horizontal wind speed up to maximum 4 days were achieved in the all-sky experiment in the lower troposphere. These improvements result mainly from the use of cloud information for computing the observation-minus-background departures. The operational implementation of all-sky assimilation is planned for Fall 2021.

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 Estimation and evaluation of COSMIC radio occultation excess phase using undifferenced measurements

2017 ◽  
Vol 10 (5) ◽  
pp. 1813-1821
Author(s):  
Pengfei Xia ◽  
Shirong Ye ◽  
Kecai Jiang ◽  
Dezhong Chen
Keyword(s):  
Radio Occultation ◽  
Weather Prediction ◽  
Lower Troposphere ◽  
Double Difference ◽  
Cosmic Radio ◽  
Processing Strategy ◽  
Single Difference ◽  
Excess Phase ◽  
Mean Square Errors ◽  
Better Than

Abstract. In the GPS radio occultation technique, the atmospheric excess phase (AEP) can be used to derive the refractivity, which is an important quantity in numerical weather prediction. The AEP is conventionally estimated based on GPS double-difference or single-difference techniques. These two techniques, however, rely on the reference data in the data processing, increasing the complexity of computation. In this study, an undifferenced (ND) processing strategy is proposed to estimate the AEP. To begin with, we use PANDA (Positioning and Navigation Data Analyst) software to perform the precise orbit determination (POD) for the purpose of acquiring the position and velocity of the mass centre of the COSMIC (The Constellation Observing System for Meteorology, Ionosphere and Climate) satellites and the corresponding receiver clock offset. The bending angles, refractivity and dry temperature profiles are derived from the estimated AEP using Radio Occultation Processing Package (ROPP) software. The ND method is validated by the COSMIC products in typical rising and setting occultation events. Results indicate that rms (root mean square) errors of relative refractivity differences between undifferenced and atmospheric profiles (atmPrf) provided by UCAR/CDAAC (University Corporation for Atmospheric Research/COSMIC Data Analysis and Archive Centre) are better than 4 and 3 % in rising and setting occultation events respectively. In addition, we also compare the relative refractivity bias between ND-derived methods and atmPrf profiles of globally distributed 200 COSMIC occultation events on 12 December 2013. The statistical results indicate that the average rms relative refractivity deviation between ND-derived and COSMIC profiles is better than 2 % in the rising occultation event and better than 1.7 % in the setting occultation event. Moreover, the observed COSMIC refractivity profiles from ND processing strategy are further validated using European Centre for Medium-Range Weather Forecasts (ECMWF) analysis data, and the results indicate that the undifferenced method reduces the noise level on the excess phase paths in the lower troposphere compared to the single-difference processing strategy.

Assimilation of SSM/I and GOES Humidity Retrievals with a One-Dimensional Variational Analysis Scheme

1995 ◽  
Vol 34 (7) ◽  
pp. 1536-1550 ◽  
Author(s):  
Godelieve Deblonde ◽  
Louis Garand ◽  
Pierre Gauthier ◽  
Christopher Grassotti
Keyword(s):  
Variational Analysis ◽  
Lower Troposphere ◽  
Precipitable Water ◽  
Error Variance ◽  
Specific Humidity ◽  
One Dimensional ◽  
Brightness Temperatures ◽  
Analysis Technique ◽  
Analysis Scheme ◽  
The Tropics

Abstract Total precipitable water (TPW) retrieved from Special Sensor Microwave/lmager (SSM/I) brightness temperatures and specific humidity retrieved from Geostationary Operational Environmental Satellite (GOES) radiances are assimilated using a one-dimensional (ID) variational analysis technique. The study is divided into two parts. First, collocations with radiosondes are performed to arm the quality of the satellite water vapor retrievals. Collocations are also performed with 6-h forecast Acids. Second, SSM/I TPW and GOES specific humidity are assimilated using a ID variational analysis technique that minimizes the error variance of the analyzed field. A global collocation study over the oceans for SSM/I TPW retrievals and 6-h forecasts of TPW shows that the rmse (with respect to radiosondes) are, respectively, 4.7 and 5.0 kg m−2. A separate collocation study over both the oceans and land for GOES retrieved TPW and 6-h forecasts of TPW yields rmse of 4.6 and 4.4 kg m−2, respectively, in the midlatitudes and 6.8 and 5.9 kg m−2 in the Tropics. The reduction of the 6-h forecast rmse when assimilating SSM/I TPW is 1 kg m−2, which is a reduction of 20% in the rmse. When GOES retrievals of specific humidity are assimilated, the elective reduction is 0.6 kg m−2. It is shown that in the upper levels of the troposphere (above 600 mb), the error reduction of specific humidity is largely due to the GOES retrievals, whereas in the lower troposphere (850 and 700 mb), the reduction is mostly due to the SSM/I TPW. This emphasizes the complementarity of the information contained at different wavelengths and the advantage of using multisensor retrievals in data analysis.

scholarly journals Retrieval of temperature and water vapor profiles from radio occultation refractivity and bending angle measurements using an Optimal Estimation approach: a simulation study

2005 ◽  
Vol 5 (6) ◽  
pp. 1665-1677 ◽  
Author(s):  
A. von Engeln ◽  
G. Nedoluha
Keyword(s):  
Water Vapor ◽  
Radio Occultation ◽  
A Priori ◽  
Estimation Method ◽  
Lower Troposphere ◽  
Optimal Estimation ◽  
Pronounced Difference ◽  
Bending Angle ◽  
Advantages And Disadvantages ◽  
The Impact

Abstract. The Optimal Estimation Method is used to retrieve temperature and water vapor profiles from simulated radio occultation measurements in order to assess how different retrieval schemes may affect the assimilation of this data. High resolution ECMWF global fields are used by a state-of-the-art radio occultation simulator to provide quasi-realistic bending angle and refractivity profiles. Both types of profiles are used in the retrieval process to assess their advantages and disadvantages. The impact of the GPS measurement is expressed as an improvement over the a priori knowledge (taken from a 24h old analysis). Large improvements are found for temperature in the upper troposphere and lower stratosphere. Only very small improvements are found in the lower troposphere, where water vapor is present. Water vapor improvements are only significant between about 1 km to 7 km. No pronounced difference is found between retrievals based upon bending angles or refractivity. Results are compared to idealized retrievals, where the atmosphere is spherically symmetric and instrument noise is not included. Comparing idealized to quasi-realistic calculations shows that the main impact of a ray tracing algorithm can be expected for low latitude water vapor, where the horizontal variability is high. We also address the effect of altitude correlations in the temperature and water vapor. Overall, we find that water vapor and temperature retrievals using bending angle profiles are more CPU intensive than refractivity profiles, but that they do not provide significantly better results.

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