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Potential increases in extreme rainfall induced hazards in a warming climate have motivated studies to link precipitation intensities to temperature. Increases exceeding the Clausius-Clapeyron (CC) rate of 6-7%/°C-1 are seen in short-duration, convective, high-percentile rainfall at mid latitudes, but the rates of change cease or revert at regionally variable threshold temperatures due to moisture limitations. It is unclear, however, what these findings mean in term of the actual risk of extreme precipitation on a regional to local scale. When conditioning precipitation intensities on local temperatures, key influences on the scaling relationship such as from the annual cycle and regional weather patterns need better understanding. Here we analyze these influences, using sub-hourly to daily precipitation data from a dense network of 189 stations in south-eastern Austria. We find that the temperature sensitivities in the mountainous western region are lower than in the eastern lowlands. This is due to the different weather patterns that cause extreme precipitation in these regions. Sub-hourly and hourly intensities intensify at super-CC and CC-rates, respectively, up to temperatures of about 17 °C. However, we also find that, because of the regional and seasonal variability of the precipitation intensities, a smaller scaling factor can imply a larger absolute change in intensity. Our insights underline that temperature precipitation scaling requires careful interpretation of the intent and setting of the study. When this is considered, conditional scaling factors can help to better understand which influences control the intensification of rainfall with temperature on a regional scale. [ABSTRACT FROM AUTHOR]

The first ground-based experiment to prove the concept of a novel space-based observation technique for microwave and infrared-laser occultation between low-Earthorbit satellites was performed in the Canary Islands between La Palma and Tenerife. For two nights from 21 to 22 July 2011 the experiment delivered the infrared-laser differential transmission principle for the measurement of greenhouse gases (GHGs) in the free atmosphere. Such global and long-term stable measurements of GHGs, accompanied also by measurements of thermodynamic parameters and line-of-sight wind in a self-calibrating way, have become very important for climate change monitoring. The experiment delivered promising initial data for demonstrating the new observation concept by retrieving volume mixing ratios of GHGs along a ∼ 144 km signal path at altitudes of ∼ 2:4 km. Here, we present a detailed analysis of the measurements, following a recent publication that introduced the experiment's technical setup and first results for an example retrieval of CO2. We present the observational and validation data sets, the latter simultaneously measured at the transmitter and receiver sites; the measurement data handling; and the differential transmission retrieval procedure. We also determine the individual and combined uncertainties influencing the results and present the retrieval results for 12CO2, 13CO2, C18OO, H2O and CH4. The new method is found to have a reliable basis for monitoring of greenhouse gases such as CO2, CH4, and H2O in the free atmosphere. [ABSTRACT FROM AUTHOR]

The radio occultation (RO) technique using signals from the Global Navigation Satellite System (GNSS), in particular from the Global Positioning System (GPS) so far, is meanwhile widely used to observe the atmosphere for applications such as numeri- cal weather prediction and global climate monitoring. The ionosphere is a major error source in RO measurements at stratospheric altitudes and a linear ionospheric correction of dual-frequency RO bending angles is commonly used to remove the first-order ionospheric effect. However, the residual ionopheric error (RIE) can still be significant so that it needs to be further mitigated for high accuracy applications, especially above about 30 km altitude where the RIE is most relevant compared to the magnitude of the neutral atmospheric bending angle. Quantification and careful analyses for better understanding of the RIE is therefore important towards enabling benchmark-quality stratospheric RO retrievals. Here we present such an analysis of bending angle RIEs covering the stratosphere and mesosphere, using quasi-realistic end-to-end simula tions for a full-day ensemble of RO events. Based on the ensemble simulations we assessed the variation of bending angle RIEs, both biases and SDs, with solar activity, latitudinal region, and with or without the assumption of ionospheric spherical symmetry and of co-existing observing system errors. We find that the bending angle RIE biases in the upper stratosphere and mesosphere, and in all latitudinal zones from low- to high-latitudes, have a clear negative tendency and a magnitude increasing with solar activity, in line with recent empirical studies based on real RO data. The maximum RIE biases are found at low latitudes during daytime, where they amount to with in μ0.03 to μ0.05 μrad, the smallest at high latitudes (0 to -0.01 μrad; quiet space weather and winter conditions). Ionospheric spherical symmetry or asymmetries about the RO event location have only a minor influence on RIE biases. The RIE SDs are markedly increased both by ionospheric asymmetries and increasing solar activity and amount to about 0.3 to 0.7 μrad in the upper stratosphere and mesosphere. Taking into account also realistic observation errors of a modern RO receiving system, amounting globally to about 0.4 μrad (un-biased; SD), shows that the random RIEs are typically comparable to the total observing system error. The results help to inform future RIE mitigation schemes that will improve upon the use of the linear ionospheric correction of bending angles and that will also provide explicit uncertainty estimates. [ABSTRACT FROM AUTHOR]

We introduce a new dynamic statistical optimization algorithm to initialize ionospherecorrected bending angles of Global Navigation Satellite System (GNSS) based radio occultation (RO) measurements. The new algorithm estimates background and obser-vation error covariance matrices with geographically-varying uncertainty profiles and realistic global-mean correlation matrices. The error covariance matrices estimated by the new approach are more accurate and realistic than in simplified existing approaches and can therefore be used in statistical optimization to provide optimal bending angle profiles for high-altitude initialization of the subsequent Abel transform re trieval of refractivity. The new algorithm is evaluated against the existing Wegener Center Occultation Processing System version 5.6 (OPSv5.6) algorithm, using simulated data on two test days from January and July 2008 and real observed CHAMP and COSMIC measurements from the complete months of January and July 2008. The following is achieved for the new method's performance compared to OPSv5.6: (1) significant 15 reduction in random errors (standard deviations) of optimized bending angles down to about two-thirds of their size or more; (2) reduction of the systematic differences in optimized bending angles for simulated MetOp data; (3) improved retrieval of refractivity and temperature profiles; (4) produces realistically estimated global-mean correlation matrices and realistic uncertainty fields for the background and observations. Over all the results indicate high suitability for employing the new dynamic approach in the processing of long-term RO data into a reference climate record, leading to well characterized and high-quality atmospheric profiles over the entire stratosphere. [ABSTRACT FROM AUTHOR]

The first ground-based experiment to prove the concept of a novel space-based observation technique for microwave and infrared-laser occultation between Low Earth Orbit satellites (LMIO) was performed in the Canary Islands between La Palma and Tenerife in July 2011. This experiment aimed to demonstrate the infrared-laser differential transmission principle for the measurement of greenhouse gases (GHGs) in the free atmosphere. Such global and long-term stable measurements of GHGs, accompanied also by measurements of thermodynamic parameters and line-of-sight wind in a self-calibrating way, have become very important for climate change monitoring. The experiment delivered promising initial data for demonstrating the new observation concept by retrieving volume mixing ratios of GHGs along a ~ 144 km signal path at altitudes of ~ 2.4 km. Here, we present a detailed analysis of the measurements, following a recent publication that introduced the experiment's technical setup and first results for an example retrieval of CO2. We present the observational and validation datasets, the latter simultaneously measured at the transmitter and receiver sites, the measurement data handling, and the differential transmission retrieval procedure. We also determine the individual and combined uncertainties influencing the results and present the retrieval results for 12CO2, 13CO2, C18OO, H2O and CH4. The new method is found to have a reliable basis for monitoring of greenhouse gases such as CO2, CH4, and H2O in the free atmosphere. [ABSTRACT FROM AUTHOR]

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 focuses on the effectiveness of the Low Earth Orbit (LEO) satellites' infrared-laser occultation (LIO) in determining the atmospheric intervention. It mentions its relevance in ascertaining the LEO-LEO's thermodynamic and atmospheric influences in higher altitude levels of the atmosphere. The osculation method's capacity to collect data regarding the level of greenhouse gases is also mentioned.

The article presents a study on greenhouse gas (GHG) profiling using infrared-laser and microwave occultation. It discusses an algorithm for retrieving GHGs from LEO-LEO microwave occultation (LIO) data as there is reportedly no retrieval algorithm available. It offers information on the LEO-LEO microwave and infrared-laser occultation (LMIO) method which is a synergetic combination to retrieve thermodynamic profiles.

The article presents an empirical-analytical error model which measure uncertainty in climatological fields from Global Positioning System (GPS) radio occultation (RO). It reveals that RO climatologies are influenced by random errors, sampling errors, and systematic errors. The study concentrates on dry atmospheric parameters as retrieved from RO measurements.

The article presents a study which develops an analytical-empirical error model for measuring climatological errors affecting the global positioning system (GPS) radio occultation (RO). The model accounts for latitudinal, seasonal and vertical variations around the tropopause region. It is found out that the sampling error at low latitudes equatorwards of 40° is considered to be the smallest because of the atmospheric variability.

The article discusses the influences of atmospheric data characteristics on the transmission and differential transmission of signals used for low earth orbit (LEO)-LEO infrared-laser occultation (LIO). It analyzes how Rayleigh scattering, aerosol extinction, trace species absorption, clouds, scattered solar radiation and turbulence affect LIO signals. It is noted that the influences of thermal radiation and Rayleigh scattering on the received signal intensities are negligible.

The article discusses the retrieval algorithm of greenhouse gas (GHG) from Low Earth Orbit (LEO) microwave and infrared (IR)-laser occultation (LMIO) data. The retrieved profiles are considered unbiased as they point to climate benchmarking capability of the LMIO. The algorithm is part of a proposed occultation observing system to retrieve thermodynamic profiles and altitude levels from LMO and GHG profiles. It consists of a preparatory part, establishing IR refractivity and impact parameter.

The potential utility of radio occultation data in general, and of data from the Global Positioning System/Meteorology (GPS/MET) experiment in particular, for studying atmospheric gravity waves is discussed. Based on a validated set of ;270 GPS/MET-derived temperature profiles, the authors produced and analyzed mean vertical wavenumber power spectra of normalized temperature fluctuations in three latitude bands (low, middle, high) within the lower stratosphere (15-30 km), where data accuracy was proven highest. The Fresnel diffraction limited vertical resolution and the limited height range of the dataset restricted this initial investigation to medium-to large-scale waves with vertical wavelengths of about 2-5 km. The deduced vertical wavenumber power spectra were compared with a saturation spectrum predicted by gravity wave saturation theory and generally found consistent with the theoretical saturation limit. The low-latitude power spectra exhibited almost saturation, with spectral power about twice as high than at mid- to high latitudes. Dominant fluctuations were observed to occur at wavelengths of about 3-5 km, indicating the wave structures to be interpreted either as inertio-gravity waves or Rossby-gravity waves. A tendency was found, though, of increasingly underestimating spectral power toward shorter wavelengths. This very likely roots in weaknesses of the 'standard' GPS/MET temperature retrieval applied here, which involves a geometrical optics, a local spherical symmetry, and a hydrostatic equilibrium assumption, all of which are increasingly violated toward smaller-scale wave structures and lead to an (artificial) wave smoothing in the retrieved temperature profiles. More elaborated future wave analyses should therefore employ improved retrieval methodology alleviating these assumptions and the authors indicate clear directions to this end. Generally, the results demonstrate that radio occultation data indeed bear high potential not only for field. [ABSTRACT FROM AUTHOR]

A new model was recently introduced to correct for higher‐order ionospheric residual biases in radio occultation (RO) data. The model depends on the α1 and α2 dual‐frequency bending angle difference squared, and a factor κ, which varies with time, season, solar activity, and height, needing only the F10.7 solar radio flux index as additional background information. To date, this kappa‐correction was analyzed in simulation studies. In this study, we test it on real observed Metop‐A RO data. The goal is to improve the accuracy of monthly mean RO climate records, potentially raising the accuracy of RO data toward higher stratospheric altitudes. We performed a thorough analysis of the kappa‐correction, evaluating its ionospheric sensitivity during the solar cycle for monthly RO climatologies and comparing the kappa‐corrected RO stratospheric climatologies to three other data sets from reanalysis and passive infrared sounding. We find a clear dependence of the kappa‐correction on solar activity, geographic location, and altitude; hence, it reduces systematic errors that vary with the solar cycle. From low to high solar activity conditions, the correction can increase from values of about 0.2 K to more than 2.0 K at altitudes between 40 to 45 km. The correction shifts RO climatologies toward warmer temperatures. With respect to other data sets, however, we found it difficult to draw firm conclusions, because the biases in the other data sets appear to be at similar magnitude as the size of the kappa‐correction. Further validation with more accurate data will be useful. Key Points: The kappa‐correction model is tested for the impact of its correction of higher‐order ionospheric biases in radio occultation dataThe magnitude of the kappa‐correction varies over the solar cycle from 0.2 K to more than 2.0 K at about 40 kmThe correction shifts the stratospheric data toward warmer temperatures; firm validation based on other data sets was difficult [ABSTRACT FROM AUTHOR]

Eight years of daily rainfall data from WegenerNet were analyzed by comparison with data from Austrian national weather stations. WegenerNet includes 153 ground level weather stations in an area of about 15 km × 20 km in the Feldbach region in southeast Austria. Rainfall has been measured by tipping bucket gauges at 150 stations of the network since the beginning of 2007. Since rain gauge measurements are considered close to true rainfall, there are increasing needs for WegenerNet data for the validation of rainfall data products such as remote sensing based estimates or model outputs. Serving these needs, this paper aims at providing a clearer interpretation on WegenerNet rainfall data for users in hydro-meteorological communities. Five clusters – a cluster consists of one national weather station and its four closest WegenerNet stations – allowed us close comparison of datasets between the stations. Linear regression analysis and error estimation with statistical indices were conducted to quantitatively evaluate the WegenerNet daily rainfall data. It was found that rainfall data between the stations show good linear relationships with an average correlation coefficient ( r ) of 0.97 , while WegenerNet sensors tend to underestimate rainfall according to the regression slope (0.87). For the five clusters investigated, the bias and relative bias were - 0.97 mm d −1 and - 11.5 % on average (except data from new sensors). The average of bias and relative bias, however, could be reduced by about 80 % through a simple linear regression-slope correction, with the assumption that the underestimation in WegenerNet data was caused by systematic errors. The results from the study have been employed to improve WegenerNet data for user applications so that a new version of the data (v5) is now available at the WegenerNet data portal ( www.wegenernet.org ). [ABSTRACT FROM AUTHOR]

The new mission concept of microwave and infrared-laser occultation between low-Earth-orbit satellites (LMIO) is designed to provide accurate and long-term stable profiles of atmospheric thermodynamic variables, greenhouse gases (GHGs), and line-of-sight (l.o.s.) wind speed with focus on the upper troposphere and lower stratosphere (UTLS). While the unique quality of GHG retrievals enabled by LMIO over the UTLS has been recently demonstrated based on end-to-end simulations, the promise of l.o.s. wind retrieval, and of joint GHG and wind retrieval, has not yet been analyzed in any realistic simulation setting. Here we use a newly developed l.o.s. wind retrieval algorithm, which we embedded in an end-to-end simulation framework that also includes the retrieval of thermodynamic variables and GHGs, and analyze the performance of both stand-alone wind retrieval and joint wind and GHG retrieval. The wind algorithm utilizes LMIO laser signals placed on the inflection points at the wings of the highly symmetric C18OO absorption line near 4767 cm-1 and exploits transmission differences from a wind-induced Doppler shift. Based on realistic example cases for a diversity of atmospheric conditions, ranging from tropical to high-latitude winter, we find that the retrieved l.o.s. wind profiles are of high quality over the lower stratosphere under all conditions, i.e., unbiased and accurate to within about 2ms-1 over about 15 to 35 km. The wind accuracy degrades into the upper troposphere due to the decreasing signal-to-noise ratio of the wind-induced differential transmission signals. The GHG retrieval in windy air is not vulnerable to wind speed uncertainties up to about 10ms-1 but is found to benefit in the case of higher speeds from the integrated wind retrieval that enables correction of wind-induced Doppler shift of GHG signals. Overall both the l.o.s. wind and GHG retrieval results are strongly encouraging towards further development and implementation of a LMIO mission. [ABSTRACT FROM AUTHOR]

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.

Radio occultation (RO) is a new technique to observe the upper troposphere and lower stratosphere (UTLS), a region that reacts particularly sensitive to climate change. Featuring characteristics such as long-term stability, SI traceability, all-weather capability, global coverage, and high accuracy and vertical resolution, RO data fulfill the requirements for climate monitoring in the UTLS. However, while a range of studies has shown the climate utility of RO it has not yet been explored sytematically where to see climate change best in RO variables. Therefore we perform here a systematic trend study for the RO variables refractivity, pressure, and temperature (bending angle, not depending on height but impact parameter, is left for separate study). The trends, given at geopotential height levels and for layer gradients, are explored to determine seasons, geographic regions, and height domains, which show a significant trend signal. Because continuous RO data are available since 2001 only, reanalyses (ERA-40 and ERA-Interim) and global circulation model simulations of the Intergovernmental Panel on Climate Change Assessment Report 4 (CCSM3, ECHAM5, HadCM3) are used as proxy data for RO. It is shown that RO data are sensitive at different height ranges and that thus several indicators of climate change can be retrieved. Refractivity emerges as indicator in the lower stratosphere (LS) and tropopause region at about 14 km to 24 km, pressure over the whole UTLS, and both in all large-scale regions except the polar caps. Temperature qualifies as indicator in the upper troposphere below about 16 km and in the LS above about 21 km. Overall, refractivity and pressure alone are adequate indicators for the UTLS, but temperature as commonly used variable facilitates easy interpretation of results. Layer gradients were found to be further sensitive indicators providing additional information. Besides large-scale global and hemi-spheric means the tropics and the mid-latitudes appear as regions suitable to track climate change with RO data. The results also point to the value of utilizing in addition to annual means specific seasons, such as northern hemispheric fall and summer, for early climate signal detection. Since RO data feature much better vertical resolution than the proxy data of this study, more detailed insights can be expected when a longer RO record will be available [ABSTRACT FROM AUTHOR]

The article discusses the findings of an empirical error analysis of Global Positioning System (GPS) radio occultation (RO) bending angle, refractivity, dry pressure, dry geopotential height, and dry temperature. It notes that the use of RO data in atmospheric studies requires accurate knowledge of error characteristics. It reveals that larger errors appears in hemispheric wintertime.

The article presents an empirical error analysis of atmospheric profiles from global positioning system (GPS) radio occultation (RO). It analyzes the GPS RO bending angle, dry pressure, refractivity, dry temperature, and dry geopotential height, and compares these data characteristics to those of different missions such as GRACE-A and Formosat-3/COSMIC (F3C). It further offers an analytical error model for GPS RO atmospheric parameters which spans the altitude range from 4 to 35 kilometers.

The usual geometry for radio occultation sounding using global navigation satellite system (GNSS) signals has the receiver placed on a low earth orbit (LEO) satellite. We investigate a new geometric approach, assuming an airborne rather than a spaceborne receiver. Information on the refractivity structure and hence the pressure, temperature, and humidity can be retrieved from accurate airborne measurements of amplitude and phase delay of the signals occulted by the troposphere. We present some advantages and disadvantages for the concept of making measurements from commercial aircraft equipped with proper GNSS receivers and antennae compared to the spaceborne case. We simulated realistic airborne occultation observations and assessed the characteristics of their geometry and sampling. We also compared the dynamic range of the signal with the magnitude of error sources that affect the measurements. Findings include that an airborne system has the potential to provide more profiles per unit area below 10 km height than a constellation of up to 25 satellites over the North Atlantic (though with inferior global coverage), and that the signal to noise ratio (SNR) should be better below 5 km than in the LEO case. Though the receiver velocity error is larger than for the LEO system, it is still small enough relative to the signal level to retrieve useful information. The estimated sensitivity of the technique is better than 0.1% refractivity at 3 km altitude increasing to 0.5% refractivity at 11 km. Because of the large horizontal drift of the tangent point of up to 450 km, the assumption of spherical symmetry in the existence of significant 3D variations in structure is expected to be a major error source, in addition to the airplane velocity uncertainty. [Copyright &y& Elsevier]

The kappa‐correction is an easy‐to‐use method to correct for residual ionospheric errors in radio occultation (RO) data. It is a simple empirical model term that only depends on readily available data. While its basic utility was well proven in previous studies, including a recent predecessor study on RO climatologies under solar cycle variations, its performance for individual RO profile correction under diverse and extreme ionization conditions is unclear so far. Here we tackle this gap and focus on investigating (extremely) low and high solar activity and ionization conditions of individual RO events, including inspection of ionospheric symmetry between inbound and outbound raypaths. Using a global multi‐year ensemble of MetOp‐A and GRACE‐A RO events over 2008–2015 as basis, we applied a sampling approach leading to six characteristic condition cases. These cases also relate to day and night time variations and geographic variations from the equatorial to the high latitude region. We inspected the kappa‐correction and its performance relative to the standard bending angle correction for RO‐retrieved stratospheric profiles and found mean deviations in temperature of near −0.3 K in the upper stratosphere (40–45 km) for high ionization conditions, with extreme deviations exceeding −2 K for strong inbound/outbound asymmetry. The kappa‐correction term itself reaches a mean value near 0.05 μrad under these high conditions. Low solar activity and ionization conditions lead to a mean correction smaller than 0.005 μrad and mean temperature deviations smaller than 0.02 K. An intercomparison to other quality datasets, predominantly showed a decrease in mean temperature difference when applying the kappa‐correction. Key Points: The kappa‐correction of radio occultation profiles is explored for low and high ionization, solar activity, and asymmetryThe mean correction is most relevant under high ionization and symmetry, reaching near 0.05 μrad around 50 kmIntercomparison with other datasets shows it predominantly decreases retrieved stratospheric temperature errors [ABSTRACT FROM AUTHOR]

Observations from the GPS radio occultation (GPSRO) satellite technique and from the newly established GCOS Reference Upper Air Network (GRUAN) are both candidates to serve as reference observations in the Global Climate Observing System (GCOS). Such reference observations are key to decrease existing uncertainties in upperair climate research. There are now more than 12 years of data available from GPSRO, with the recognized properties high accuracy, global coverage, high vertical resolution, and long-term stability. These properties make GPSRO a suitable choice for comparison studies with other upper-air observational systems. The GRUAN network consists of reference radiosonde ground stations (16 at present), which adhere to the GCOS climate monitoring principles. In this study, we intercompare GPSRO temperature and humidity profiles and Vaisala RS90/92 data from the "standard" global radiosonde network over the whole 2002 to 2013 time frame. Additionally, we include the first years of GRUAN data (using Vaisala RS92), available since 2009. GPSRO profiles which occur within 3 h and 300 km of radiosonde launches are used. Overall very good agreement is found between all three data sets with temperature differences usually less than 0.2 K. In the stratosphere above 30 hPa, temperature differences are larger but still within 0.5 K. Day/night comparisons with GRUAN data reveal small deviations likely related to a warm bias of the radiosonde data at high altitudes, but also residual errors from the GPSRO retrieval process might play a role. Vaisala RS90/92 specific humidity exhibits a dry bias of up to 40% in the upper troposphere, with a smaller bias at lower altitudes within 15 %. GRUAN shows a marked improvement in the bias characteristics, with less than 5% difference to GPSRO, up to 300 hPa. GPSRO dry temperature and physical temperature are validated using radiosonde data as reference. We find that GPSRO provides valuable long-term stable reference observations with well-defined error characteristics for climate applications and for anchoring other upperair measurements. [ABSTRACT FROM AUTHOR]

A correction to the article "Greenhouse gas measurements over a 144 km open path in the Canary Islands," by J. S. A. Brooke and colleagues that was published in the 2012 issue is presented.

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.

The article presents a comparative study, examining difference in lower stratospheric temperature records from (A)MSU, radiosondes, and Global Positioning System (GPS) radio occultation (RO). The difference of anomalies of the (A)MSU datasets in relation to RO depicts a significant trend. It measures the error that results from sparse sampling.

The article compares the (Advanced) Microwave Sounding Unit ((A)MSU) data and radiosonde data to radio occultation (RO) data to determine uncertainties for upper-air trend patterns. The error that results from sparse sampling is caused by subtracting it from radiosonde and RO datasets. The (A)MSU data provides dense horizontal sampling. Differences detected in the radiosonde and RO trends stem from the (A)MSU data.

The article analyzes the consistency of radio occultation (RO) climatologies derived from different satellites. Testing for consistency is made possible through the presence of multiple RO receiving satellites in orbit over the same time period. The influence of different sampling characteristics in the analysis is noted due to latitude- and altitude-resolved refractivity and dry temperature climatologies. There is a reduction of refractivity and dry temperature deviations in almost any month.

The article examines the relation of measurement geometry and obliquity of profiles concerning errors in global navigation satellite system (GNSS) radio occultation (RO) measurements. It states that atmospheric profiles retrieved from GNSS RO measurements are increasingly used to validate other measurement data. It discusses an end-to-end simulation study using high-resolution analysis fields from the European Centre for Medium Range Weather Forecasts.

The article offers information on the WegenerNet climate station network in Feldbach, Austria. The said station network has at least 151 meteorological stations and it has weather and climate-related experiments with high resolution. The WegenerNet also consists instrument used in climatic and meteorological observations including air temperature, amount of precipitation, and relative humidity.

The article presents a study which investigates the temperature errors in Global Navigation Satellite System (GNSS) radio occultation (RO) data in the troposphere and lower stratosphere. The study focused on the dependence systematic and random errors on the measurement geometry particularly on the azimuth angle of the RO measurements. It determines the errors on the reference profile to see whether the mean tangent point is not being taken.

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]