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

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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Retrieval of temperature and water vapor profiles from radio occultation refractivity and bending angle measurements using an optimal estimation approach: a simulation study

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-5-1585-2005 ◽

2005 ◽

Vol 5 (2) ◽

pp. 1585-1617 ◽

Cited By ~ 1

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 possible assimilation impacts of this data. High resolution ECMWF global fields are used by 5 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 24 h old analysis). Large improvements are found for temperature in the upper troposphere and 10 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 15 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 significantly more CPU intensive than refractivity profiles, but that they do 20 not provide significantly better results.

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A practical information-centered technique to remove a priori information from lidar optimal-estimation-method retrievals

Atmospheric Measurement Techniques ◽

10.5194/amt-12-3943-2019 ◽

2019 ◽

Vol 12 (7) ◽

pp. 3943-3961 ◽

Cited By ~ 1

Author(s):

Ali Jalali ◽

Shannon Hicks-Jalali ◽

Robert J. Sica ◽

Alexander Haefele ◽

Thomas von Clarmann

Keyword(s):

Water Vapor ◽

A Priori ◽

Estimation Method ◽

Optimal Estimation ◽

Mixing Ratio ◽

A Priori Information ◽

Fine Grid ◽

Large Power ◽

Priori Information ◽

Water Vapor Mixing Ratio

Abstract. Lidar retrievals of atmospheric temperature and water vapor mixing ratio profiles using the optimal estimation method (OEM) typically use a retrieval grid with a number of points larger than the number of pieces of independent information obtainable from the measurements. Consequently, retrieved geophysical quantities contain some information from their respective a priori values or profiles, which can affect the results in the higher altitudes of the temperature and water vapor profiles due to decreasing signal-to-noise ratios. The extent of this influence can be estimated using the retrieval's averaging kernels. The removal of formal a priori information from the retrieved profiles in the regions of prevailing a priori effects is desirable, particularly when these greatest heights are of interest for scientific studies. We demonstrate here that removal of a priori information from OEM retrievals is possible by repeating the retrieval on a coarser grid where the retrieval is stable even without the use of formal prior information. The averaging kernels of the fine-grid OEM retrieval are used to optimize the coarse retrieval grid. We demonstrate the adequacy of this method for the case of a large power-aperture Rayleigh scatter lidar nighttime temperature retrieval and for a Raman scatter lidar water vapor mixing ratio retrieval during both day and night.

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Detection of reflections in GNSS radio occultation measurements using phase matching

10.5194/amt-2017-216 ◽

2017 ◽

Author(s):

Thomas Sievert ◽

Joel Rasch ◽

Anders Carlström ◽

Mats I. Pettersson

Keyword(s):

Radio Occultation ◽

Complex Function ◽

Lower Troposphere ◽

Phase Matching ◽

Matching Method ◽

Bending Angle ◽

Abel Transform ◽

Lower Region ◽

Additional Information ◽

The Impact

Abstract. It is well-known that in the presence of super-refractive (SR) layers in the lower troposphere inversion of GNSS radio occultation (RO) measurements using the Abel transform yields biased refractivity profiles. As such it is problematic to reconstruct the true refractivity from the RO signal. Additional information about this lower region of the atmosphere might be embedded in reflected parts of the signal. To retrieve the bending angle, the phase matching operator can be used. This operator produces a complex function of the impact parameter, and from its phase we can calculate the bending angle. Instead of looking at the phase, in this paper we focus on the function's amplitude. The results in this paper show that the signatures of surface reflections in GNSS RO measurements can be significantly enhanced when using the phase matching method by processing only an appropriately selected segment of the received signal. We can then identify reflection signatures even in cases where they are normally obscured by the direct signal's influence on the phase matching amplitude. This signature enhancement is demonstrated by simulations and confirmed with real MetOp-A data.

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Analysis of reflections in GNSS radio occultation measurements using the phase matching amplitude

Atmospheric Measurement Techniques ◽

10.5194/amt-11-569-2018 ◽

2018 ◽

Vol 11 (1) ◽

pp. 569-580 ◽

Cited By ~ 2

Author(s):

Thomas Sievert ◽

Joel Rasch ◽

Anders Carlström ◽

Mats Ingemar Pettersson

Keyword(s):

Radio Occultation ◽

Complex Function ◽

Lower Troposphere ◽

Phase Matching ◽

Matching Method ◽

Bending Angle ◽

Abel Transform ◽

Lower Region ◽

Additional Information ◽

The Impact

Abstract. It is well-known that in the presence of super-refractive layers in the lower-tropospheric inversion of GNSS radio occultation (RO) measurements using the Abel transform yields biased refractivity profiles. As such it is problematic to reconstruct the true refractivity from the RO signal. Additional information about this lower region of the atmosphere might be embedded in reflected parts of the signal. To retrieve the bending angle, the phase matching operator can be used. This operator produces a complex function of the impact parameter, and from its phase we can calculate the bending angle. Instead of looking at the phase, in this paper we focus on the function's amplitude. The results in this paper show that the signatures of surface reflections in GNSS RO measurements can be significantly enhanced when using the phase matching method by processing only an appropriately selected segment of the received signal. This signature enhancement is demonstrated by simulations and confirmed with 10 hand-picked MetOp-A occultations with reflected components. To validate that these events show signs of reflections, radio holographic images are generated. Our results suggest that the phase matching amplitude carries information that can improve the interpretation of radio occultation measurements in the lower troposphere.

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Improved Analyses and Forecasts of Hurricane Ernesto’s Genesis Using Radio Occultation Data in an Ensemble Filter Assimilation System

Monthly Weather Review ◽

10.1175/mwr-d-11-00024.1 ◽

2012 ◽

Vol 140 (1) ◽

pp. 151-166 ◽

Cited By ~ 22

Author(s):

Hui Liu ◽

Jeffrey Anderson ◽

Ying-Hwa Kuo

Keyword(s):

Water Vapor ◽

Radio Occultation ◽

Lower Troposphere ◽

Weather Conditions ◽

Wind Analysis ◽

Added Water ◽

Occultation Data ◽

The Impact ◽

Mean Square Errors ◽

Assimilation System

Abstract Radio occultation (RO) refractivity observations provide information about tropospheric water vapor and temperature in all weather conditions. The impact of using RO refractivity observations on analyses and forecasts of Hurricane Ernesto’s genesis (2006) using an ensemble Kaman filter data assimilation system is investigated. Assimilating RO refractivity profiles in the vicinity of the storm locally moistens the analysis of the lower troposphere and also adjusts the wind analysis in both the lower and upper troposphere through forecast multivariate correlations of RO refractivity and wind. The model forecasts propagate and enhance the added water vapor and the wind adjustments leading to more accurate analyses of the later stages of the genesis of the storm. The root-mean-square errors of water vapor and wind forecasts compared to dropsonde and radiosonde observations are reduced consistently. As a result, assimilating RO refractivity data in addition to traditional observations leads to a stronger initial vortex of the storm and improved forecasts of the storm’s intensification. The benefits of the RO data are much reduced when the RO data in the lower troposphere (below 6 km) are ignored.

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Generalized Canonical Transform method for radio occultation sounding with improved retrieval in the presence of horizontal gradients

10.5194/amt-2020-147 ◽

2020 ◽

Author(s):

Michael Gorbunov ◽

Gottfried Kirchengast ◽

Kent B. Lauritsen

Keyword(s):

Linear Combination ◽

Impact Parameter ◽

Radio Occultation ◽

Lower Troposphere ◽

General Idea ◽

Fourier Integral Operators ◽

Full Spectrum ◽

Bending Angle ◽

Horizontal Gradients ◽

The Impact

Abstract. By now, a series of advanced Wave Optical (WO) approaches to the processing of Radio Occultation (RO) observations are widely used. In particular, the Canonical Transform (CT) method and its further developments need to be mentioned. The latter include the Full Spectrum Inversion (FSI) method, the Geometric Optical (GO) Phase Matching (PM) method, and the general approach based on the Fourier Integral Operators (FIOs), also referred to as the CT type 2 (CT2) method. The general idea of these methods is the application of a canonical transform that changes the coordinates in the phase space from time and Doppler frequency to impact parameter and bending angle. For the spherically symmetric atmosphere, the impact parameter, being invariant for each ray, is a unique coordinate of the ray manifold. Therefore, the derivative of the phase of the wave field in the transformed space is directly linked to the bending angle, as a single-valued function of the impact parameter. However, in the presence of horizontal gradients, this approach may not work. Here we introduce a further generalization of the CT methods in order to reduce the errors due to horizontal gradients. We describe, in particular, the modified CT2 method denoted CT2A, which complements the former with one more affine transform: a new coordinate that is a linear combination of the impact parameter and bending angle. The linear combination coefficient is a tunable parameter. We derive the explicit formulas for the CT2A and develop the updated numerical algorithm. For testing the method, we performed statistical analyses based on COSMIC RO retrievals and (collocated) ECMWF analysis profiles. We demonstrate that it is possible to find a reasonably optimal value of the new tunable CT2A parameter that mitigates systematic errors in the lower troposphere and allows the practical realization of the improved capability to cope with horizontal gradients.

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Generalized canonical transform method for radio occultation sounding with improved retrieval in the presence of horizontal gradients

Atmospheric Measurement Techniques ◽

10.5194/amt-14-853-2021 ◽

2021 ◽

Vol 14 (2) ◽

pp. 853-867

Author(s):

Michael Gorbunov ◽

Gottfried Kirchengast ◽

Kent B. Lauritsen

Keyword(s):

Linear Combination ◽

Impact Parameter ◽

Radio Occultation ◽

Lower Troposphere ◽

General Idea ◽

Control Procedure ◽

Fourier Integral Operators ◽

Bending Angle ◽

Horizontal Gradients ◽

The Impact

Abstract. By now, a series of advanced wave optical approaches to the processing of radio occultation (RO) observations are widely used. In particular, the canonical transform (CT) method and its further developments need to be mentioned. The latter include the full spectrum inversion (FSI) method, the geometric optical phase matching (PM) method, and the general approach based on the Fourier integral operators (FIOs), also referred to as the CT type 2 (CT2) method. The general idea of these methods is the application of a canonical transform that changes the coordinates in the phase space from time and Doppler frequency to impact parameter and bending angle. For the spherically symmetric atmosphere, the impact parameter, being invariant for each ray, is a unique coordinate of the ray manifold. Therefore, the derivative of the phase of the wave field in the transformed space is directly linked to the bending angle as a single-valued function of the impact parameter. However, in the presence of horizontal gradients, this approach may not work. Here we introduce a further generalization of the CT methods in order to reduce the errors due to horizontal gradients. We describe, in particular, the modified CT2 method, denoted CT2A, which complements the former with one more affine transform: a new coordinate that is a linear combination of the impact parameter and bending angle. The linear combination coefficient is a tunable parameter. We derive the explicit formulas for the CT2A and develop the updated numerical algorithm. For testing the method, we performed statistical analyses based on RO retrievals from data acquired by the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) and collocated analysis profiles of the European Centre for Medium-Range Weather Forecasts (ECMWF). We demonstrate that it is possible to find a reasonably optimal value of the new tunable CT2A parameter that minimizes the root mean square difference between the RO retrieved and the ECMWF refractivity in the lower troposphere and allows the practical realization of the improved capability to cope with horizontal gradients and serve as the basis of a new quality control procedure.

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Global 3D Features of Error Variances of GPS Radio Occultation and Radiosonde Observations

Remote Sensing ◽

10.3390/rs13010001 ◽

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.

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Evaluating the Impact of the COSMIC RO Bending Angle Data on Predicting the Heavy Precipitation Episode on 16 June 2008 during SoWMEX-IOP8

Monthly Weather Review ◽

10.1175/mwr-d-13-00275.1 ◽

2014 ◽

Vol 142 (11) ◽

pp. 4139-4163 ◽

Cited By ~ 15

Author(s):

Shu-Chih Yang ◽

Shu-Hua Chen ◽

Shu-Ya Chen ◽

Ching-Yuang Huang ◽

Ching-Sen Chen

Keyword(s):

Lower Troposphere ◽

Heavy Precipitation ◽

Southwest Monsoon ◽

Weather Research And Forecasting ◽

Heavy Rainfall Event ◽

Bending Angle ◽

Angle Data ◽

Ensemble Transform Kalman Filter ◽

The Impact ◽

Better Than

Abstract Global positioning system (GPS) radio occultation (RO) data have been broadly used in global and regional numerical weather predictions. Assimilation with the bending angle often performs better than refractivity, which is inverted from the bending angle under spherical assumption and is sometimes associated with negative biases at the lower troposphere; however, the bending angle operator also requires a higher model top as used in global models. This study furnishes the feasibility of bending-angle assimilation in the prediction of heavy precipitation systems with a regional model. The local RO operators for simulating bending angle and refractivity are implemented in the Weather Research and Forecasting (WRF)–local ensemble transform Kalman filter (LETKF) framework. The impacts of assimilating RO data from the Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC) using both operators are evaluated on the prediction of a heavy precipitation episode during Southwest Monsoon Experiment intensive observing period 8 (SoWMEX-IOP8) in 2008. Results show that both the refractivity and bending angle provide a favorable condition for generating this heavy rainfall event. In comparison with the refractivity data, the advantage of assimilating the bending angle is identified in the midtroposphere for deepening of the moist layer that leads to a rainfall forecast closer to the observations.

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Precipitable Water Vapor Retrieval and Analysis by Multiple Data Sources: Ground-Based GNSS, Radio Occultation, Radiosonde, Microwave Satellite, and NWP Reanalysis Data

Journal of Sensors ◽

10.1155/2018/3428303 ◽

2018 ◽

Vol 2018 ◽

pp. 1-13 ◽

Cited By ~ 6

Author(s):

Qin Zhang ◽

Junhua Ye ◽

Shuangcheng Zhang ◽

Fei Han

Keyword(s):

Water Vapor ◽

Radio Occultation ◽

Weather Prediction ◽

Precipitable Water ◽

Reanalysis Data ◽

Precipitable Water Vapor ◽

Reanalysis Dataset ◽

High Positive Correlation ◽

Advantages And Disadvantages ◽

Ecmwf Reanalysis

Precipitable water vapor (PWV) content detection is vital to heavy rain prediction; up to now, lots of different measuring methods and devices are developed to observe PWV. In general, these methods can be divided into two categories, ground-based or space-based. In this study, we analyze the advantages and disadvantages of these technologies, compare retrieved atmosphere parameters by different RO (radio occultation) observations, like FORMOSAT-3/COSMIC (Formosa Satellite-3 and Constellation Observing System for Meteorology, Ionosphere, and Climate) and FY3C (China Feng Yun 3C), and assess retrieved PWV precision with a radiosonde. Besides, we interpolate PWV from NWP (numerical weather prediction) reanalysis data for more comparison and analysis with RO. Specifically, ground-based GNSS is of high precision and continuous availability to monitor PWV distribution; in our paper, we show cases to validate and compare GNSS retrieving PWV with a radiosonde. Except GNSS PWV, we give two different radio occultation sounding results, COSMIC and FY3C, to validate the precision to monitor PWV from space in a global area. FY3C results containing Beidou (China Beidou Global Satellite Navigation System) radio occultation events need to be emphasized. So, in our study, we get the retrieved atmospheric profiles from GPS and Beidou radio occultation observations and derive atmosphere PWV by a variational retrieval method based on these data over a global area. Besides, other space-based methods, such as microwave satellite, are also useful in detecting PWV distribution situations in a global area from space; in this study, we present a case of retrieved PWV using microwave satellite observation. NWP reanalysis data ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-Interim and the new-generation reanalysis data ERA5 provide global grid atmosphere parameters, like surface temperature, different-level pressures, and precipitable water. We show cases of retrieved PWV and validate the precision with radiosonde results and compare new reanalysis dataset ERA5 with ERA-Interim, finding that ERA5 can get higher precision-retrieved atmosphere parameters and PWV. In the end, from our comparison, we find that the retrieved PWV from RO (FY3C and COSMIC) and ECMWF reanalysis data (ERA-Interim and ERA5) have a high positive correlation and that almost all R2 values exceed 0.9, compare retrieved PWV with a radiosonde, and find that whether it is RO and ECMWF reanalysis data, ground-based GNSS, or microwave satellite, they all show small biases.

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