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Abstract: Global Navigation Satellite System (GNSS) radio occultation (RO) is an innovative meteorological remote sensing technique for measuring atmospheric parameters such as refractivity, temperature, water vapour and pressure for the improvement of numerical weather prediction (NWP) and global climate monitoring (GCM). GNSS RO has many unique characteristics including global coverage, long-term stability of observations, as well as high accuracy and high vertical resolution of the derived atmospheric profiles. One of the main error sources in GNSS RO observations that significantly affect the accuracy of the derived atmospheric parameters in the stratosphere is the ionospheric error. In order to mitigate the effect of this error, the linear ionospheric correction approach for dual-frequency GNSS RO observations is commonly used. However, the residual ionospheric errors (RIEs) can be still significant, especially when large ionospheric disturbances occur and prevail such as during the periods of active space weather. In this study, the RIEs were investigated under different local time, propagation direction and solar activity conditions and their effects on RO bending angles are characterised using end-to-end simulations. A three-step simulation study was designed to investigate the characteristics of the RIEs through comparing the bending angles with and without the effects of the RIEs. This research forms an important step forward in improving the accuracy of the atmospheric profiles derived from the GNSS RO technique. [Copyright &y& Elsevier]

The article presents a study which examines the use of new infrared-laser occultation method for the measurement of satellite remote sensing of greenhouse gases in the Canary Islands. The study performs first ground-based experimental demonstration to determine the efficacy of the new technique in measuring the atmospheric absorption of carbon dioxide (CO2) over a 144km path length. Results show that the method is a useful tool in monitoring CO2 in the free atmosphere.

The article presents a study which focuses on the development of a technique for the satellite remote sensing of greenhouse gases in the Canary Islands. It outlines the acquisition of global set of altitude-resolved concentration measurements via the absorption of short-wave infrared (SWIR) laser signals transmitted between counter-rotating satellites in low earth orbit. The measurement of carbon dioxide over an open path of 144 kilometers is also discussed.

The article discusses the importance of data consistency in building radio occultation (RO) climatologies from combined record of information from different satellites. It mentions the use of RO record from Challenging Minisatellite Payload for Geoscientific Research (CHAMP) and Gravity Recovery and Climate Experiment (GRACE-A). The reduction of refractivity deviations to <0.05% is depicted.

State of the arte assimilation techniques, such as 3D-Var, are relatively seldom used within climate analysis frameworks, partly because of the enormous numerical costs. In order to face this issue ESA''s high performance computing Grid on-Demand (G-POD) is used. We assimilate Global Navigation Satellite System (GNSS) based radio occultations (RO). RO data in general exhibit some favorable properties, like global coverage, all-weather capability expected long-term stability and accuracy. These properties and the continuity of data offered by the Meteorological Operational Satellite (MetOp) program and other RO missions are an ideal opportunity to study the long term atmospheric and climate variability. This paper investigates the assimilation of RO refractivity profiles into first guess fields derived from 21 years of ECMWF''s ERA40 dataset on a monthly mean basis divided into four synoptic time layers in order to take the diurnal cycle into account. In contrast to NWP systems, the assimilation procedure is applied without cycling, thus enabling us to run our 3D-Var implementation within G-POD parallel for different time layers. Results indicate a significant analysis increment which is partly systematic, emphasizing the ability of RO data to add independent information to ECMWF analysis fields, with a potential to correct biases. This work lays the ground for further studies using data from existing instruments within a framework based on a mature methodology. [Copyright &y& Elsevier]