[1] Global Navigation Satellite System (GNSS)-based radio occultation (RO) is a satellite remote sensing technique providing accurate profiles of the Earth’s atmosphere for weather and climate applications. Above about 30km altitude, however, statistical optimization is a critical process for initializing the RO bending angles in order to optimize the climate monitoring utility of the retrieved atmospheric profiles. Here we introduce an advanced dynamic statistical optimization algorithm, which uses bending angles from multiple days of European Centre for Medium-range Weather Forecasts (ECMWF) short-range forecast and analysis fields, together with averaged-observed bending angles, to obtain background profiles and associated error covariance matrices with geographically varying background uncertainty estimates on a daily updated basis. The new algorithm is evaluated against the existing Wegener Center Occultation Processing System version 5.4 (OPSv5.4) algorithm, using several days of simulated MetOp and observed CHAMP and COSMIC data, for January and July conditions. We find the following for the new method’s performance compared to OPSv5.4: 1.) it significantly reduces random errors (standard deviations), down to about half their size, and leaves less or about equal residual systematic errors (biases) in the optimized bending angles; 2.) the dynamic (daily) estimate of the background error correlation matrix alone already improves the optimized bending angles; 3.) the subsequently retrievedrefractivityprofilesandatmospheric(temperature)profilesbenefit by improvederror characteristics,especiallyabove about 30km. Based on theseencouraging results, we work to employ similar dynamic error covariance estimation also for the observed bending angles and to apply the method to full months and subsequently to entire climate data records.

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A new dynamic approach for statistical optimization of GNSS radio occultation bending angles for optimal climate monitoring utility

The Global Positioning System/Meteorology ( GPS/MET) Program was established in 1993 by the University Corporation for Atmospheric Research ( UCAR) to demonstrate active limb sounding of the Earth's atmosphere using the radio occultation technique. The demonstration system observes occulted GPS satellite signals received by a low Earth orbiting ( LEO) satellite, MicroLab-1, launched April 3,1995. The system can profile ionospheric electron density and neutral atmospheric properties. Neutral atmospheric refractivity, density, pressure, and temperature are derived at altitudes where the amount of water vapor is low. At lower altitudes, vertical profiles of density, pressure, and water vapor pressure can be derived from the GPS/MET refractivity profiles if temperature data from an independent source are available. This paper describes the GPS/MET data analysis procedures and validates GPS/MET data with statistics and illustrative case studies. We compare more than 1200 GPS/MET neutral atmosphere soundings to correlative data from operational global weather analyses, radiosondes, and the GOES, TOVS, UARS/MLS and HALOE orbiting atmospheric sensors. Even though many GPS/MET soundings currently fail to penetrate the lowest 5 km of the troposphere in the presence of significant water vapor, our results demonstrate 1°C mean temperature agreement with the best correlative data sets between 1 and 40 km. This and the fact that GPS/MET observations are all-weather and self-calibrating suggests that radio occultation technology has the potential to make a strong contribution to a global observing system supporting weather prediction and weather and climate research.

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Analysis and validation of GPS/MET data in the neutral atmosphere

The first radio occultation measurements of the CHAMP (CHAllenging Minisatellite Payload) satellite using Global Positioning System (GPS) signals have been performed on February 11, 2001. By the end of April 2001 more than 3000 occultations were recorded. Globally distributed vertical profiles of dry temperature and specific humidity are derived, of which a set of 438 vertical dry temperature profiles is compared with corresponding global weather analyses. The observed temperature bias is less than ∼1 K above the tropopause and even less than 0.5 K in the altitude interval from 12 to 20 km at latitudes >30°N. About 55% of the compared profiles reached the last kilometer above the Earth's surface. In spite of the activated anti-spoofing mode of the GPS system the state-of-the-art GPS flight receiver aboard CHAMP combined with favorable antenna characteristics allows for atmospheric sounding with high accuracy and vertical resolution.

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Atmosphere sounding by GPS radio occultation: First results from CHAMP

/pdf/a-technical-description-of-atmospheric-sounding-by-gps-3ajrhe4wq1.pdf

A technical description of atmospheric sounding by GPS occultation

In this paper, we describe the GPS radio occultation (RO) inversion process currently used at the University Corporation for Atmospheric Research (UCAR) COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate) Data Analysis and Archive Center (CDAAC). We then evaluate the accuracy of RO refractivity soundings of the CHAMP (CHAllenging Minisatellite Payload) and SACC (Satellite de Aplicaciones Cientificas-C) missions processed by CDAAC software, using data primarily from the month of December 2001. Our results show that RO soundings have the highest accuracy from about 5 km to 25 km. In this region of the atmosphere, the observational errors (which include both measurement and representativeness errors) are generally in the range of 0.3% to 0.5% in refractivity. The observational errors in the tropical lower troposphere increase toward the surface, and reach @3% in the bottom few kilometers of the atmosphere. The RO observational errors also increase above 25 km, particularly over the higher latitudes of the winter hemisphere. These error estimates are, in general, larger than earlier theoretical predictions. The larger observational errors in the lower tropical troposphere are attributed to the complicated structure of humidity, superrefraction and receiver tracking errors. The larger errors above 25 km are related to observational noise (mainly, uncalibrated ionospheric effects) and the use of ancillary data for noise reduction through an optimization procedure. We demonstrate that RO errors above 25 km can be substantially reduced by selecting only low-noise occultations. Our results show that RO soundings have smaller observational errors of refractivity than radiosondes when compared to analyses and short-term forecasts, even in the tropical lower troposphere. This difference is most likely related to the larger representativeness errors associated with the radiosonde, which provides in situ (point) measurements. The RO observational errors are found to be comparable with or smaller than 12-hour forecast errors of the NCEP (National Centers for Environmental Prediction) Aviation (AVN) model, except in the tropical lower troposphere below 3 km. This suggests that RO observations will improve global weather analysis and prediction. It is anticipated that with the use of an advanced signal tracking technique (open-loop tracking) in future missions, such as COSMIC, the accuracy of RO soundings can be further improved.

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Inversion and error estimation of GPS radio occultation Data

[1] One of the most significant error sources in radio occultation soundings are residual errors of the ionospheric correction originating from small scale ionospheric turbulence and receiver noise. These errors degrade the quality of retrievals above 35–40 km. We describe a combined algorithm of the ionospheric correction and noise reduction including the following important details: (1) fitting of climatological model, (2) dynamical estimation of signal and noise covariances using radio occultation signals above 50 km, and (3) statistically optimized retrieval of neutral atmospheric and ionospheric refraction angles from L1 and L2 measurements using background refraction angles and signal and noise covariances (optimal linear combination). This method allows for the estimation of the error covariances of the retrieved neutral atmospheric and ionospheric refraction angles. We show some examples of GPS/MET data processing and perform a statistical comparison with the retrievals obtained by UCAR and DMI/IGAM algorithms. Our algorithm was previously used in the statistical validation of GPS/MET data on the basis of ECMWF analyses.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2000RS002370

Ionospheric correction and statistical optimization of radio occultation data

This paper describes the results of the statistical comparison of the inversions of GPS/MET radio occultation data with analysis data of the European Centre for Medium-Range Weather Forecast (ECMWF). The Prime Time 4 period (February 2-16, 1997) GPS/MET data were analyzed. The data analysis algorithms include the derivation of refraction angles from the measured phase excess, the back-propagation method for handling data in multipath regions, ionospheric correction and noise reduction, and the Abel inversion of the refraction angle profiles and the derivation of dry temperature. We use a forward model of radio occultation experiments in order to produce artificial occultation data for the ECMWF global fields of atmospheric variables. The forward model exists in two variants, which are geometric optics propagator and wave optics propagator. The wave optics propagator allows for the simulation of diffraction effects and multipath propagation, which made this operator the choice for the validation. The artificial occultation data are processed by exactly the same inversion algorithm as the GPS/MET data. This allows for the adequate comparison of the retrieved temperatures. For regions with dense observational networks (Europe, China, and United States), the comparison between the satellite data inversions and the model analysis fields is characterized by biases inside 0.5 K and mean square deviations of 1.5-2 K. In the Southern Hemisphere, where observational data are sparse, the bias can reach 2 K, and the mean square deviation is 2-3 K. Because the quality of GPS/MET data must not be different in different hemispheres, the difference in the bias is assumed to be based on the used ECMWF analysis data.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2000JD900816

Analysis and validation of GPS/MET radio occultation data

Two methods for the determination of refraction angle profiles from radio occultation measurements in multipath areas are analyzed and compared: (1) the radio-optic method based on the analysis of the local spatial spectra of the measured wave field and (2) the back propagation of the received wave field to a single-ray region. The basic limitations of the radio-optic method are (1) the restriction of the resolution of refraction angle profiles due to the uncertainty relation of refraction angle and impact parameter and (2) diffractive effects in subcaustic areas, where the spatial spectra cannot be interpreted in terms of geometric optical rays. The basic limitation of the back propagation method is related to ray and caustic structures, which may not contain single-ray areas. It is shown that strong refraction reduces the uncertainties of refraction angle and impact parameter. On the other hand, strong refraction or superrefraction is responsible for complicated caustic structures that cannot be resolved by the back propagation technique. The two methods are thus complementary to each other and can be combined for processing lower tropospheric occultation data. This analysis is corroborated by numerical simulations based on global fields of atmospheric variables from analyses of the European Centre for Medium Range Weather Forecast.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/1999RS002247

Comparative analysis of radioholographic methods of processing radio occultation data

[1] Processing of radio occultation data requires filtering and quality control for the noise reduction and sorting out corrupted data samples. We introduce a radio holographic filtering algorithm based on the synthesis of canonical transform (CT2) and radio holographic focused synthesized aperture (RHFSA) methods. The field in the CT2-transformed space is divided by a reference signal to subtract the regular phase variation and to compress the spectrum. Next, it is convolved with a Gaussian filter window and multiplied by the reference signal to restore the phase variation. This algorithm is simple to implement, and it is numerically efficient. Numerical simulation of processing radio occultations with a realistic receiver noise indicates a good performance of the method. We introduce a new technique of the error estimation of retrieved bending angle profiles based on the width of the running spectra of the transformed wavefield multiplied with the reference signal. We describe a quality control method for the discrimination of corrupted samples in the L2 channel, which is most susceptible to signal tracking errors. We apply the quality control and error estimation techniques for the processing of data acquired by Challenging Minisatellite Payload (CHAMP) and perform a statistical comparison of CHAMP data with the analyses of the German Weather Service (DWD). The statistical analysis shows a good agreement between the CHAMP and DWD error estimates and the observed CHAMP–DWD differences. This corroborates the efficiency of the proposed quality control and error estimation techniques.

Radio holographic filtering, error estimation, and quality control of radio occultation data

Refractometric sounding of the Earth's atmosphere using a multiorbit system of Global Positioning System (GPS) and low-Earth orbit (LEO) satellites is modeled on the basis of data from the model of global atmospheric circulation (ECHAM3). The errors of the tomographic reconstruction of meteorological fields are investigated because of insufficient measured refractometric data. For a system of 100 LEO and 18 GPS satellites the estimates of errors of geopotential and temperature is obtained, which are 3—5 m and 0.3 K, respectively, in the pressure range 10—200 mbar.

M. E. Gorbunov

Papers

Ionospheric correction and statistical optimization of radio occultation data

Analysis and validation of GPS/MET radio occultation data

Comparative analysis of radioholographic methods of processing radio occultation data

Radio holographic filtering, error estimation, and quality control of radio occultation data

Three-dimensional satellite refractive tomography of the atmosphere: Numerical simulation