The observational climate record is a cornerstone of our scientific understanding of climate changes and their potential causes. Existing observing networks have been designed largely in support of operational weather forecasting and continue to be run in this mode. Coverage and timeliness are often higher priorities than absolute traceability and accuracy. Changes in instrumentation used in the observing system, as well as in operating procedures, are frequent, rarely adequately documented and their impacts poorly quantified. For monitoring changes in upper-air climate, which is achieved through in-situ soundings and more recently satellites and ground-based remote sensing, the net result has been trend uncertainties as large as, or larger than, the expected emergent signals of climate change. This is more than simply academic with the tropospheric temperature trends issue having been the subject of intense debate, two international assessment reports and several US congressional hearings. For more than a decade the international climate science community has been calling for the instigation of a network of reference quality measurements to reduce uncertainty in our climate monitoring capabilities. This paper provides a brief history of GRUAN developments to date and outlines future plans. Such reference networks can only be achieved and maintained with strong continuing input from the global metrological community.

The technical successes in radio navigation and the availability of nu-merical algorithms have promoted the implementation of GPS-technology to atmo-spheric sciences. The tomographical contribution of Global Satellite Navigation Sys-tems (GNSS) is possible due to the methods of high precision detection of tropospheric delays of navigation signals from satellites to receivers. The principal specific char-acter in initial constraints, data collection and assimilation methods, the obtaining of final numerical results and their interpretation make the continuation of the success story for GPS-tomography very challenging. The authors use numerical simulation as the most time- and cost-efficient way to study different processes related to tro-pospheric water vapor tomography. This paper tends to give a short overview about some known methods in GPS-tomography for detection, monitoring and modeling of the tropospheric water vapor. The possible mathematical approach to the construc-tion of virtual network of ground-based sensors (GPS-receivers) for a real geographical location and discretization of the troposphere, also some aspects of raw data filtering and analysis are described. Output of tomographical modelling of the troposphere can be used to improve the results of large-scale numerical weather prediction models and also real-time navigation. The questions of voxel geometry and methods of data processing are supposed to be the key questions in constructing an effective network of GPS-receivers for water vapor tomography.

Despite different techniques for the estimation of column integrated water vapour (precipitable water, PW) no method has yet been identified as the most accurate or the reference one. In this work we report intercomparisons between four PW estimation methods -radiosonde, Aerosol Robotic Network (AERONET), Global Positioning System (GPS), and High Resolution Limited Area Model (HIRLAM). Two intensive observation periods at Tõravere, Estonia, were used: 22 June−6 November 2008 and 9−12 August 2010. During the longer campaign, only observations by GPS, AERONET, and HIRLAM were performed. An agreement with average difference less than 2.2% among all three methods was established. However, compared to HIRLAM and GPS, the AERONET method overestimated PW by 5-9% at PW < 12 mm and underestimated it by 6-10% at PW > 25 mm. In addition, the consistency test applied indicated that previously reported uncertainty in AERONET-measured PW is too high. During the shorter but more complex campaign, data obtained with all four methods were available. Although the average differences between PW from radiosonde and three other methods were < 5%, the discrepancy between single measurements reached 33%. Relatively low temporal and spatial resolution of the HIRLAM grid as well as launching sparseness of radiosondes caused higher scatter from the other methods. The study suggests that besides radiosonde, as a traditional meteorological tool, the most reliable PW estimation can be made by GPS.

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