Monthly and zonally averaged zonal wind information in the equatorial stratosphere provided by GNSS radio occultation

Healy, S. B.; Polichtchouk, Inna; Horányi, Ándrás

doi:10.1002/qj.3870

Cited by 14 publications

(14 citation statements)

References 39 publications

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“…Departures decrease in amplitude towards the end of the period, when they benefit from assimilation of temperature‐sensitive data from GNSS radio occultation (Healy et al . (2020)), and perhaps also from improved radiance measurements and the increase in radiosonde numbers.…”

Section: Era5 Surface and Upper‐air Fieldsmentioning

confidence: 99%

“…Departures then become larger, presumably because of the influence on winds of the multi-variate analysis of radiance data from the VTPR and TOVS satellites. Departures decrease in amplitude towards the end of the period, when they benefit from assimilation of temperature-sensitive data from GNSS radio occultation (Healy et al (2020)), and perhaps also from improved radiance measurements and the increase in radiosonde numbers.…”

Section: Qbomentioning

confidence: 99%

See 1 more Smart Citation

The ERA5 global reanalysis: Preliminary extension to 1950

Bell

Hersbach

Simmons

et al. 2021

Quart J Royal Meteoro Soc

314

160

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The extension of the ERA5 reanalysis back to 1950 supplements the previously published segment covering 1979 to the present. It features the assimilation of additional conventional observations, as well as improved use of early satellite data. The number of observations assimilated increases from 53,000 per day in early 1950 to 570,000 per day by the end of 1978. Accordingly, the quality of the reanalysis improves throughout the period, generally joining seamlessly with the segment covering 1979 to the present. The fidelity of the extension is illustrated by the accurate depiction of the North Sea storm of 1953, and the events leading to the first discovery of sudden stratospheric warmings in 1952. Time series of ERA5 global surface temperature anomalies show temperatures to be relatively stable from 1950 until the late 1970s, in agreement with the other contemporary full-input reanalysis covering this period and with independent data sets, although there are significant differences in the accuracy of representing specific regions, Europe being well represented in the early period but Australia less so. The variability of ERA5 precipitation from month to month agrees well with observations for all continents, with correlations above 90% for most of Europe and generally in excess of 70% for North America, Asia and Australia. The evolution of upper air temperatures, humidities and winds shows smoothly varying behaviour, including tropospheric warming and stratospheric cooling, modulated by volcanic eruptions. The Quasi-Biennial Oscillation is well represented throughout. Aspects to be improved upon in future reanalyses include the assimilation of tropical cyclone data, the spin-up of soil moisture and stratospheric humidity, and the representation of surface temperatures over Australia.

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Section: Era5 Surface and Upper‐air Fieldsmentioning

confidence: 99%

Section: Qbomentioning

confidence: 99%

The ERA5 global reanalysis: Preliminary extension to 1950

Bell

Hersbach

Simmons

et al. 2021

Quart J Royal Meteoro Soc

314

160

View full text Add to dashboard Cite

show abstract

“…RO data show highest accuracy in the upper troposphere and lower stratosphere between about 5–35 km (Foelsche et al., 2011; Kursinski et al., 1997; Zeng et al., 2019). Enabling improved accuracy of RO data also at higher altitudes, where global and long‐term data are relatively scarce, results in improved value also as data source for numerical weather prediction (NWP), climate monitoring, and new stratospheric climate analyses such as, for example, deriving stratospheric wind fields (Healy et al., 2020; Scherllin‐Pirscher et al., 2014, 2017).…”

Section: Introductionmentioning

confidence: 99%

Performance of the Ionospheric Kappa‐Correction of Radio Occultation Profiles Under Diverse Ionization and Solar Activity Conditions

Danzer

Haas

Schwaerz

et al. 2021

Earth and Space Science

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“…For example, the data assimilation system of the European Centre for Medium‐Range Weather Forecasts (ECMWF) currently assimilates observations from about 100 satellite instruments, which is about three times as many as 20 years ago. Additional satellite observations provide better coverage of the global atmosphere and include new types of observations such as radio occultation measurements (Healy et al ., 2020) and vertical wind profiles from Aeolus , the Doppler wind lidar measuring horizontal line‐of‐sight (HLOS) winds (Stoffelen et al ., 2005).…”

Section: Introductionmentioning

confidence: 99%

Comparison of temperature and wind observations in the Tropics in a perfect‐model, global EnKF data assimilation system

Žagar

Raeder

et al. 2023

Quart J Royal Meteoro Soc

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Flow‐dependent errors in tropical analyses and short‐range forecasts are analysed using global observing‐system simulation experiments assimilating only temperature, only winds, and both data types using the ensemble Kalman filter (EnKF) Data Assimilation Research Testbed (DART) and a perfect model framework. The idealised, homogeneous observation network provides profiles of wind and temperature data from the nature run for January 2018 using the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM) forced by the observed sea‐surface temperature. The results show that the assimilation of abundant wind observations in a perfect model makes the temperature data in the Tropics largely uninformative. Furthermore, the assimilation of wind data reduces the background errors in specific humidity twice as much as the assimilation of temperature observations. In all experiments, the largest analysis uncertainties and the largest short‐term forecast errors are found in regions of strong vertical and longitudinal gradients in the background wind, especially in the upper troposphere and lower stratosphere over the Indian Ocean and Maritime Continent. The horizontal error correlation scales are on average short throughout the troposphere, just several hundred km. The correlation scales of the wind variables in precipitating regions are half of those in nonprecipitating regions. In precipitating regions, the correlations are elongated vertically, especially for the wind variables. Strong positive cross‐correlations between temperature and specific humidity in the precipitating regions are explained using the Clausius–Clapeyron equation.

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Monthly and zonally averaged zonal wind information in the equatorial stratosphere provided by GNSS radio occultation

Cited by 14 publications

References 39 publications

The ERA5 global reanalysis: Preliminary extension to 1950

The ERA5 global reanalysis: Preliminary extension to 1950

Performance of the Ionospheric Kappa‐Correction of Radio Occultation Profiles Under Diverse Ionization and Solar Activity Conditions

Comparison of temperature and wind observations in the Tropics in a perfect‐model, global EnKF data assimilation system

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