Abstract

Abstract. We here present results from an evaluation of the Radio Occultation Meteorology Satellite Application Facility (ROM SAF) gridded monthly mean climate data record (CDR v1.0), based on Global Positioning System (GPS) radio occultation (RO) data from the CHAMP (CHAllenging Minisatellite Payload), GRACE (Gravity Recovery and Climate Experiment), COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate), and Metop satellite missions. Systematic differences between RO missions, as well as differences of RO data relative to ERA-Interim reanalysis data, are quantified. The methods used to generate gridded monthly mean data are described, and the correction of monthly mean RO climatologies for sampling errors, which is essential for combining data from RO missions with different sampling characteristics, is evaluated. We find good overall agreement between the ROM SAF gridded monthly mean CDR and the ERA-Interim reanalysis, particularly in the 8–30 km height interval. Here, the differences largely reflect time-varying biases in ERA-Interim, suggesting that the RO data record has a better long-term stability than ERA-Interim. Above 30–40 km altitude, the differences are larger, particularly for the pre-COSMIC era. In the 8–30 km altitude region, the observational data record exhibits a high degree of internal consistency between the RO satellite missions, allowing us to combine data into multi-mission records. For global mean bending angle, the consistency is better than 0.04 %, for refractivity it is better than 0.05 %, and for global mean dry temperature the consistency is better than 0.15 K in this height interval. At altitudes up to 40 km, these numbers increase to 0.08 %, 0.11 %, and 0.50 K, respectively. The numbers can be up to a factor of 2 larger for certain latitude bands compared to global means. Below about 8 km, the RO mission differences are larger, reducing the possibilities to generate multi-mission data records. We also find that the residual sampling errors are about one-third of the original and that they include a component most likely related to diurnal or semi-diurnal cycles.

Highlights

  • Radio occultation (RO) measurements, exploiting radio signals emitted by Global Navigation Satellite System (GNSS) satellites, are increasingly making important contributions to the global observing system

  • The RO measurement technique has a number of attractive features: it provides geophysical information with high vertical resolution throughout the troposphere and stratosphere, it is insensitive to clouds and the underlying surface, and it has an intrinsic long-term stability that does not rely on intercalibration between satellites or instruments (Kursinski et al, 1997; Leroy et al, 2006)

  • We present results from an evaluation of the 15year Radio Occultation Meteorology Satellite Application Facility (ROM SAF) climate data records (CDRs) v1.0 consisting of separate data records from four different RO satellite missions: CHAMP, GRACE, COSMIC, and Metop

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Summary

Introduction

Radio occultation (RO) measurements, exploiting radio signals emitted by Global Navigation Satellite System (GNSS) satellites, are increasingly making important contributions to the global observing system. The RO measurement technique has a number of attractive features: it provides geophysical information with high vertical resolution throughout the troposphere and stratosphere, it is insensitive to clouds and the underlying surface, and it has an intrinsic long-term stability that does not rely on intercalibration between satellites or instruments (Kursinski et al, 1997; Leroy et al, 2006) The latter feature is important for climate applications where small differences in atmospheric properties that develop over decades are monitored. We present results from an evaluation of the ROM SAF monthly mean climate data records (CDRs) provided on a two-dimensional latitude–height grid, with a focus on the temporal stability of the data series and on the differences between the RO missions.

GPS radio occultation measurements
ERA-Interim reanalysis data
ROM SAF processing of RO data
Processing to atmospheric profiles
Bending angle quality
Data quality screening
Monthly averaging in latitude bins
Sampling errors and sampling-error correction
Anomaly data time series
Comparison with ERA-Interim reanalyses
Differences between RO missions
Time–altitude bending angle plots
Anomaly time series
Bending angle
Refractivity
Dry temperature
Evaluation of the sampling-error correction
Findings
Summary and conclusions

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