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Random uncertainties and vertical error correlations are estimated for three independent data sets. The three collocated data sets are (1) refractivity profiles of radio occultation measurements retrieved from the Metop-A and B and COSMIC-1 missions, (2) refractivity derived from GRUAN-processed RS92 sondes, and (3) refractivity profiles derived from ERA5 forecast fields. The analysis is performed using a generalization of the so-called three-cornered hat method to include off-diagonal elements such that full error covariance matrices can be calculated. The impacts from various sources of representativeness error on the uncertainty estimates are analysed. The estimated refractivity uncertainties of radio occultations, radiosondes, and model data are stated with reference to the vertical representation of refractivity in these data sets. The existing theoretical estimates of radio occultation uncertainty are confirmed in the middle and upper troposphere and lower stratosphere, and only little dependence on latitude is found in that region. In the lower troposphere, refractivity uncertainty decreases with latitude. These findings have implications for both retrieval of tropospheric humidity from radio occultations and for assimilation of radio occultation data in numerical weather prediction models and reanalyses.

Many studies have by now demonstrated the accuracy of GNSS Radio Occultation (RO) data, and their usefulness as a stable climate reference. Homogeneity of the data records are obtained by reprocessing of the data using uniform processing software throughout the length of the climate record. Version 1 of the ROM SAF Climate Data Record (CDR), based on Metop, CHAMP, GRACE, and COSMIC data, covers a continuous 15-year period from 2002 to 2016. The CDR is extended in time by an Interim CDR (ICDR) which is regularly updated nearly up to present time, and the combined time series is now long enough (20 years) to begin detection of climate trends. We here present results from recent climate applications of RO data: bending angle and temperature trends in the upper troposphere and stratosphere, including the first RO contribution to the IPCC 6th Assessment Report. Furthermore, we outline ROM SAF plans for generating RO climate data records. This includes calculating uncertainty estimates and generating homogenized water vapour climate data records based on a one-dimensional variational retrieval using detrended background data.The Radio Occultation Meteorology Satellite Application Facility (ROM SAF) is a decentralized operational processing facility under EUMETSAT. The main objective of the ROM SAF is to generate and deliver operational radio occultation products from GNSS RO instruments onboard Metop, Metop-SG, Sentinel-6 Michael Freilich and other satellites for NWP and climate applications. The ROM SAF CDR and ICDR is publically available from: http://www.romsaf.org. Further information about the ROM SAF products and services are available at this website.

The Radio Occultation (RO) technique is based on measurements of phase shifts of GNSS radio waves by an instrument onboard a low-Earth orbiting satellite. The processing of the measurements yields the refractive index of the Earth’s atmosphere, from which the temperature, pressure, and humidity fields can be retrieved. It is a limb-sounding technique, with a high vertical resolution, and with observational information retrieved from near-surface to the upper stratosphere. Numerous studies have demonstrated the accuracy of GNSS Radio Occultation (RO) data, and their usefulness as a stable climate reference. Homogeneity of the data records are obtained by reprocessing of the data using uniform processing software and a priori data throughout the length of the climate record. We here present results from a validation of the 17-year ROM SAF RO Climate Data Record (CDR), based on a new reprocessing of Metop, CHAMP, GRACE, and COSMIC data using excess-phase and amplitude data from EUMETSAT (the Metop mission) and UCAR/CDAAC (the CHAMP, GRACE, COSMIC, and Metop missions).A central issue for the generation of RO-based CDRs is whether data from different satellite missions can be combined to form long time series of multi-mission data. This presentation explores the consistency of gridded monthly-mean data from different RO missions through comparison with ERA-Interim reanalysis data, and through a study of mission differences during mission overlap periods. It is shown that within a core region from the upper troposphere to the middle stratosphere, roughly 8 to 35-40 kilometers (depending on latitude and geophysical variable), there is a high consistency amongst the RO missions, allowing for the construction of long-term stable data sets for use in climate studies and climate monitoring.

Temperature changes in the lower and middle stratosphere during 2001-2016 are evaluated using measurements from GPS Radio Occultation (RO) and Advanced Microwave Sounding Unit (AMSU) aboard the Aqua satellite. After downsampling of GPS-RO profiles according to the AMSU weighting functions, the spatially and seasonally resolved trends from the two data sets are in excellent agreement. The observations indicate that the middle stratosphere has cooled in the time period 2002-2016 at an average rate of –0.14±0.12 to –0.36±0.14 K/decade, while no significant change was found in the lower stratosphere. The meridionally and vertically resolved trends from high-resolution GPS-RO data exhibit a marked inter-hemispheric asymmetry and highlight a distinct boundary between tropospheric and stratospheric temperature change regimes matching the tropical thermal tropopause. The seasonal pattern of trend reveals significant opposite-sign structures at high and low latitudes, providing indication of seasonally varying change in stratospheric circulation.

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 fact that fluctuations of refractivity may result in a systematic negative shift of the phase of waves propagating in a random medium is known for a long time. Tatarskii was the first to reveal it, and von Eshleman put this into the context of the radio occultation sounding of planetary atmospheres. In this paper, we show that this effect may also be one of the causes of the negative bias of refractivity retrieved for radio occultation observations of the Earth's atmosphere. We perform theoretical estimates of this effect based on the Rytov approximation. These estimates, however, do not consider the regular refraction, which may significantly change the magnitude of this effect. We perform numerical simulations of radio occultations, based on the Kolmogorov-von Karman isotropic spectrum of refractivity fluctuations, with the internal and external scales and magnitude tuned so as to reproduce the realistic level of the variance of retrieved refractivity and the amplitude fluctuations of the modeled signals. The model of the regular atmosphere is based on analyses of the European Centre for Medium-Range Weather Forecasts. We show that it is possible to set up a vertical profile of the structural constant of the fluctuation spectrum such that it will result in a systematic shift and variances of the retrieved refractivity consistent with those observed for COSMIC measurements.

Instrument GRAS (Global Navigation Satellite System Receiver for Atmospheric Sounding) on-board of the Metop-A satellite was activated on 27 October 2006. Currently, Metop-A is a fully operational satellite with GRAS providing from 650–700 occultations per day. We describe our processing of GRAS data based on the modification of our OCC software, which was modified to become capable of reading and processing GRAS data. We perform a statistical comparison of bending angles and refractivities derived from GRAS data with those derived from ECMWF analyses. We conclude that GRAS data have error characteristics close to those of COSMIC data. In the height range 10–30 km, the systematic refractivity difference GRAS–ECMWF is of the order of 0.1–0.2 %, and the standard deviation is 0.3–0.6 %. In the lower troposphere GRAS refractivity and bending angle indicate a negative bias, which reaches its maximum value in the tropics. In particular the retrieved refractivity is biased by up to 2.5 %. The negative bias pattern is similar to that found in the statistical validation of COSMIC data. This makes it probable that the bias should not be attributed to the instrument design or hardware.