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 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 Sensitivity of airborne radio occultation to tropospheric properties over ocean and land

2018 ◽  
Vol 11 (2) ◽  
pp. 763-780 ◽  
Author(s):  
Feiqin Xie ◽  
Loknath Adhikari ◽  
Jennifer S. Haase ◽  
Brian Murphy ◽  
Kuo-Nung Wang ◽  
...  
Keyword(s):  
Land Surface ◽  
Radio Occultation ◽  
Prediction Models ◽  
Weather Prediction ◽  
Method Comparison ◽  
Lower Troposphere ◽  
Negative Bias ◽  
Tropospheric Temperature ◽  
Atmospheric Conditions ◽  
Full Spectrum

Abstract. Airborne radio occultation (ARO) measurements collected during a ferry flight at the end of the PRE-Depression Investigation of Cloud-systems in the Tropics (PREDICT) field campaign from the Virgin Islands to Colorado are analyzed. The large contrast in atmospheric conditions along the flight path from the warm and moist Caribbean Sea to the much drier and cooler continental conditions provides a unique opportunity to address the sensitivity of ARO measurements to the tropospheric temperature and moisture changes. This long flight at nearly constant altitude (∼ 13 km) provided an optimal configuration for simultaneous high-quality ARO measurements from two high-gain side-looking antennas, as well as one relatively lower gain zenith (top) antenna. The omnidirectional top antenna has the advantage of tracking robustly more occulting satellites in all direction as compared to the limited-azimuth tracking of the side-looking antennas. Two well-adapted radio-holographic bending angle retrieval methods, full-spectrum inversion (FSI) and phase matching (PM), were compared with the standard geometric-optics (GO) retrieval method. Comparison of the ARO retrievals from the top antenna with the near-coincident ECMWF reanalysis-interim (ERA-I) profiles shows only a small root-mean-square (RMS) refractivity difference of ∼ 0.3 % in the drier upper troposphere from ∼ 5 to ∼ 11.5 km over both land and ocean. Both the FSI and PM methods improve the ARO retrievals in the moist lower troposphere and reduce the negative bias found in the GO retrieval due to atmospheric multipath. In the lowest layer of the troposphere, the ARO refractivity derived using FSI shows a negative bias of about −2 %. The increase of the refractivity bias occurs below 5 km over the ocean and below 3.5 km over land, corresponding to the approximate altitude of large vertical moisture gradients above the ocean and land surface, respectively. In comparisons to radiosondes, the FSI ARO soundings capture well the height of layers with sharp refractivity gradients but display a negative refractivity bias inside the boundary layer. The unique opportunity to make simultaneous independent recordings of occultation events from multiple antennas establishes that high-precision ARO measurements can be achieved corresponding to an RMS difference better than 0.2 % in refractivity (or ∼ 0.4 K). The surprisingly good quality of recordings from a very simple zenith antenna increases the feasibility of developing an operational tropospheric sounding system onboard commercial aircraft in the future, which could provide a large number of data for direct assimilation in numerical weather prediction models.

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.

scholarly journals Challenges of Increased Resolution for the Local Ensemble Tangent Linear Model

2020 ◽  
Vol 148 (6) ◽  
pp. 2549-2566
Author(s):  
Douglas R. Allen ◽  
Sergey Frolov ◽  
Rolf Langland ◽  
Craig H. Bishop ◽  
Karl W. Hoppel ◽  
...  
Keyword(s):  
Linear Model ◽  
Fast Moving ◽  
Weather Prediction ◽  
Lower Troposphere ◽  
Forecast Model ◽  
Nonlocal Operators ◽  
Upper Troposphere ◽  
Global Environmental ◽  
Nonlinear Normal ◽  
Normal Mode Initialization

Abstract An ensemble-based linearized forecast model has been developed for data assimilation applications for numerical weather prediction. Previous studies applied this local ensemble tangent linear model (LETLM) to various models, from simple one-dimensional models to a low-resolution (~2.5°) version of the Navy Global Environmental Model (NAVGEM) atmospheric forecast model. This paper applies the LETLM to NAVGEM at higher resolution (~1°), which required overcoming challenges including 1) balancing the computational stencil size with the ensemble size, and 2) propagating fast-moving gravity modes in the upper atmosphere. The first challenge is addressed by introducing a modified local influence volume, introducing computations on a thin grid, and using smaller time steps. The second challenge is addressed by applying nonlinear normal mode initialization, which damps spurious fast-moving modes and improves the LETLM errors above ~100 hPa. Compared to a semi-Lagrangian tangent linear model (TLM), the LETLM has superior skill in the lower troposphere (below 700 hPa), which is attributed to better representation of moist physics in the LETLM. The LETLM skill slightly lags in the upper troposphere and stratosphere (700–2 hPa), which is attributed to nonlocal aspects of the TLM including spectral operators converting from winds to vorticity and divergence. Several ways forward are suggested, including integrating the LETLM in a hybrid 4D variational solver for a realistic atmosphere, combining a physics LETLM with a conventional TLM for the dynamics, and separating the LETLM into a sequence of local and nonlocal operators.

scholarly journals A modification to the standard ionospheric correction method used in GPS radio occultation

2015 ◽  
Vol 8 (8) ◽  
pp. 3385-3393 ◽  
Author(s):  
S. B. Healy ◽  
I. D. Culverwell
Keyword(s):  
Impact Parameter ◽  
Radio Occultation ◽  
Order Term ◽  
Weather Prediction ◽  
Implicit Assumption ◽  
Ionospheric Correction ◽  
Gps Radio Occultation ◽  
Uncertainty Estimates ◽  
The Impact ◽  
Bending Angles

Abstract. A modification to the standard bending-angle correction used in GPS radio occultation (GPS-RO) is proposed. The modified approach should reduce systematic residual ionospheric errors in GPS radio occultation climatologies. A new second-order term is introduced in order to account for a known source of systematic error, which is generally neglected. The new term has the form κ(a) × (αL1(a)-αL2(a))2, where a is the impact parameter and (αL1, αL2) are the L1 and L2 bending angles, respectively. The variable κ is a weak function of the impact parameter, a, but it does depend on a priori ionospheric information. The theoretical basis of the new term is examined. The sensitivity of κ to the assumed ionospheric parameters is investigated in one-dimensional simulations, and it is shown that κ &amp;simeq; 10–20 rad−1. We note that the current implicit assumption is κ=0, and this is probably adequate for numerical weather prediction applications. However, the uncertainty in κ should be included in the uncertainty estimates for the geophysical climatologies produced from GPS-RO measurements. The limitations of the new ionospheric correction when applied to CHAMP (Challenging Minisatellite Payload) measurements are noted. These arise because of the assumption that the refractive index is unity at the satellite, made when deriving bending angles from the Doppler shift values.

scholarly journals GPS Radio Occultation Data Assimilation in the AREM Regional Numerical Weather Prediction Model for Flood Forecasts

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Wei Cheng ◽  
Youping Xu ◽  
Zhiwu Deng ◽  
Chunli Gu
Keyword(s):  
Data Assimilation ◽  
Radio Occultation ◽  
Weather Prediction ◽  
Radiosonde Data ◽  
Light Rain ◽  
Gps Radio Occultation ◽  
Study Results ◽  
Occultation Data ◽  
Radio Occultation Data

Based on the Backward Four-Dimensional Variational Data Assimilation (Backward-4DVar) system with the Advanced Regional Eta-coordinate Model (AREM), which is capable of assimilating radio occultation data, a heavy rainfall case study is performed using GPS radio occultation (GPS RO) data and routine GTS data on July 5, 2007. The case study results indicate that the use of radio occultation data after quality control can improve the quality of the analysis to be similar to that of the observations and, thus, have a positive effect when improving 24-hour rainfall forecasts. Batch tests for 119 days from May to August during the flood season in 2009 show that only the use of GPS RO data can make positive improvements in both 24-hour and 48-hour regional rainfall forecasts and obtain a better B score for 24-hour forecasts and better TS score for 48-hour forecasts. When using radio occultation refractivity data and conventional radiosonde data, the results indicate that radio occultation refractivity data can achieve a better performance for 48-hour forecasts of light rain and heavy rain.

GPS radio occultation: A potential new data source for improvement of antarctic pressure field

2003 ◽  
Vol 8 (2) ◽  
pp. 636-648 ◽  
Author(s):  
Ge Sheng-jie ◽  
C. K. Shum ◽  
J. Wickert ◽  
Ch. Reigber
Keyword(s):  
Radio Occultation ◽  
Pressure Field ◽  
Gps Radio Occultation ◽  
Data Source
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