Evaluation of the 15-year ROM SAF monthly mean GPS radio occultation climate data record

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.

The 2019/20 Australian wildfires generated a persistent smoke-charged vortex rising up to 35 km altitude

“…GNSS-RO. We use Global Navigation Satellite System (GNSS) radio occultation (RO) dry temperature profiles acquired onboard Metop A/B/C satellites and processed in near real time mode at EUMETSAT RO Meteorology Satellite Application Facility (ROM SAF) 35 . For computing the composited temperature perturbation within the smoke bubble we use temperature profiles collocated with the vortex centroid as identified using IFS analyses (8 h, 400 km collocation criteria).…”

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

“…This includes Metop-A GRAS data for the whole period, and Metop-B GRAS measurements from 2012. The ROM SAF geopotential data used here do not include a correction for sampling error (Gleisner et al, 2019). The Metop GRAS geopotential heights are produced with a standard GNSS-RO retrieval (e.g., Kursinski et al, 1997;Leroy, 1997;Gleisner et al, 2019).…”

“…The ROM SAF geopotential data used here do not include a correction for sampling error (Gleisner et al, 2019). The Metop GRAS geopotential heights are produced with a standard GNSS-RO retrieval (e.g., Kursinski et al, 1997;Leroy, 1997;Gleisner et al, 2019). Briefly explained, an Abel transform is used to map bending angles given as function of impact parameter to refractive index as a function of height.…”

“…The monthly mean GNSS-RO geopotential heights are given on a fixed pressure grid which equates to roughly 200 m spacing in the vertical. They are area weighted and zonally averaged into 5 • latitude bins (Gleisner et al, 2019). The 5 • spacing is not ideal for computing the second derivative of the geopotential heights (Equation ( 2)), but this application was not anticipated when the CDR was originally constructed.…”

Assessment of the Homogeneity of Long-Term Multi-Mission RO-Based Temperature Climatologies

“…Angerer et al [16] evaluated the consistency among various RO missions by calculating the deviations between the monthly mean temperature in RO data from different satellites and found a high level of consistency in the altitude range of 8 to 25 km, in which the deviations of the monthly mean temperature were less than 0.1 K. Steiner et al [17] performed a rigorous intercomparison of a full set of RO data products from multiple satellites provided by different RO processing centers and found that all RO data products were highly consistent in the altitude range of 8 to 25 km, while more uncertainty was observed in CHAMP RO data at altitudes above 25 km. Gleisner et al [18] evaluated the consistency of 15 years of climate data records from the CHAMP, Gravity Recovery and Climate, COSMIC, and METOP missions by comparing them with ERA-Interim reanalysis data. The results of the comparison suggest that the RO bending angle, refractivity, and dry temperature records show good overall agreement with the reanalysis at altitudes of 830 km, while large time-varying biases were observed for altitudes of 30-40 km and below 8 km.…”