The COSMIC/FORMOSAT-3 Radio Occultation Mission after 12 Years: Accomplishments, Remaining Challenges, and Potential Impacts of COSMIC-2

Ho, Shu-peng; Anthes, Richard A.; Ao, C. O.; Healy, S. B.; Horányi, Ándrás; Hunt, Douglas; Mannucci, A. J.; Pedatella, Nicholas; Randel, William J.; Simmons, A. J.; Steiner, Andrea; Xie, Feiqin; Yue, Xinan; Zeng, Zhen

doi:10.1175/bams-d-18-0290.1

Cited by 107 publications

(111 citation statements)

References 208 publications

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“…The consistency of global atmospheric temperature reanalyses-including ERA5 and ERA-Interim-in the lower and middle stratosphere has improved since around 2006 with the assimilation of GNSS-RO (Ho et al, 2019;Long et al, 2017;Luntama et al, 2008), but ERA-Interim is still around ∼1.5 K warmer than ERA5 globally at 1 hPa. The ERA-Interim and ERA5 data used here are monthly means of daily averages (reanalysis stream = "MODA"), computed at fixed pressure levels.…”

Section: Datamentioning

confidence: 99%

Sensitivity Analysis and Impact of the Kappa‐Correction of Residual Ionospheric Biases on Radio Occultation Climatologies

Danzer

Schwaerz

Kirchengast

et al. 2020

Earth and Space Science

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A new model was recently introduced to correct for higher-order ionospheric residual biases in radio occultation (RO) data. The model depends on the α 1 and α 2 dual-frequency bending angle difference squared, and a factor κ, which varies with time, season, solar activity, and height, needing only the F 10.7 solar radio flux index as additional background information. To date, this kappa-correction was analyzed in simulation studies. In this study, we test it on real observed Metop-A RO data. The goal is to improve the accuracy of monthly mean RO climate records, potentially raising the accuracy of RO data toward higher stratospheric altitudes. We performed a thorough analysis of the kappa-correction, evaluating its ionospheric sensitivity during the solar cycle for monthly RO climatologies and comparing the kappa-corrected RO stratospheric climatologies to three other data sets from reanalysis and passive infrared sounding. We find a clear dependence of the kappa-correction on solar activity, geographic location, and altitude; hence, it reduces systematic errors that vary with the solar cycle. From low to high solar activity conditions, the correction can increase from values of about 0.2 K to more than 2.0 K at altitudes between 40 to 45 km. The correction shifts RO climatologies toward warmer temperatures. With respect to other data sets, however, we found it difficult to draw firm conclusions, because the biases in the other data sets appear to be at similar magnitude as the size of the kappa-correction. Further validation with more accurate data will be useful. Recently, a new model approach for the correction of higher-order ionospheric residuals was introduced by Healy and Culverwell (2015), the so-called kappa-correction. Healy and Culverwell (2015) derived the kappa-correction from an integral expression for the RIE based on the original work by Vorob'ev and Krasil'nikova (1994). The resulting kappa-correction consists of a product of two factors: The first factor, κ, shows only moderate variations, dependent on altitude, solar activity, local time, and season, while the

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Section: Datamentioning

confidence: 99%

Sensitivity Analysis and Impact of the Kappa‐Correction of Residual Ionospheric Biases on Radio Occultation Climatologies

Danzer

Schwaerz

Kirchengast

et al. 2020

Earth and Space Science

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“…Since RO observations can be derived to obtain atmospheric temperature and humidity information with high accuracy and precision, have a high vertical resolution, and are bias-free [6], they are a good complement to satellite microwave and infrared observations. The observation error variance is required when assimilating RO data.…”

Section: Global Error Variances Of Ro Observationsmentioning

confidence: 99%

“…RS stations are distributed more densely in East Asia, Europe, and North America than elsewhere. Satellite missions, such as the Constellation Observing System for Meteorology, Ionosphere, and Climate-1, -2 [5][6][7], provide nearly evenly and densely distributed RO profiles over the world, making up for the lack of conventional observations over the ocean.…”

Section: Introductionmentioning

confidence: 99%

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

Zou

2020

Remote Sensing

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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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“…As a highly recognized standard in the ionospheric occultation observation field, COSMIC data were selected as the comparative IRO dataset for IRI-2016. Because of its performance degradation in obtaining occultation events after 2014 [36], the occultation data of FY3C-GNOS, which slightly deviate from COSMIC data, were also added to the IRO dataset. Specifically, there are currently two foF2 model options: CCIR and URSI.…”

Section: Introductionmentioning

confidence: 99%

Global Comparison of F2-Layer Peak Parameters Estimated by IRI-2016 With Ionospheric Radio Occultation Data During Solar Minimum

et al. 2021

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The COSMIC/FORMOSAT-3 Radio Occultation Mission after 12 Years: Accomplishments, Remaining Challenges, and Potential Impacts of COSMIC-2

Abstract: Capsule Summary Contributions and the remaining challenges of COSMIC and other RO observations to weather, climate, and space weather since 2011 and potential contributions to research and operations of COSMIC-2 are summarized.

Cited by 107 publications

References 208 publications

Sensitivity Analysis and Impact of the Kappa‐Correction of Residual Ionospheric Biases on Radio Occultation Climatologies

Sensitivity Analysis and Impact of the Kappa‐Correction of Residual Ionospheric Biases on Radio Occultation Climatologies

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

Global Comparison of F2-Layer Peak Parameters Estimated by IRI-2016 With Ionospheric Radio Occultation Data During Solar Minimum

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