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The Pyrenean Platform for Observation of the Atmosphere (P2OA) is a coupled plain-mountain instrumented platform in southwest France. It is composed of two physical sites: The 'Pic du Midi' mountain top observatory (2877 m a.s.l.) and the 'Centre de Recherches Atmosphériques' (600 m a.s.l). Both sites are complementarily instrumented for the monitoring of climate variables and the study of meteorological processes in a mountainous region. The scientific topics covered by the P2OA include surface-atmosphere interactions in heterogeneous landscape and complex terrain, physics and chemistry of atmospheric trace species at large scale, influence of local and regional-scale emissions and transport on the atmospheric composition, and transient luminous events above thunderstorms. With a large number of instruments and a high hosting capacity, the P2OA contributes to atmospheric sciences in (i) building long-term series of atmospheric observations, (ii) hosting experimental field campaigns and instrumental tests, (iii) educational training in atmospheric observation techniques. Here we present the complete instrumentation of the P2OA and the associated datasets, give a meteorological characterization of the platform, and illustrate the potential of the P2OA and its dataset with past or ongoing studies and projects. [ABSTRACT FROM AUTHOR]

Integrated Water Vapour (IWV) measurements from similar or different techniques are often inter-compared for calibration and validation purposes. Results are usually assessed in terms of bias (difference of the means), standard deviation of the differences, and linear fit slope and offset (intercept) estimates. When the instruments are located at different elevations, a correction must be applied to account for the vertical displacement between the sites. Empirical formulations are traditionally used for this correction. In this paper we show that the widely-used correction model based on a standard, exponential, profile for water vapour cannot properly correct the bias, slope, and offset parameters simultaneously. Correcting the bias with this model degrades the slope and offset estimates, and vice-versa. This paper proposes an improved correction model which overcomes these limitations. The model uses a multi-linear regression of slope and offset parameters from a radiosonde climatology. It is able to predict monthly parameters with a root-mean-square error smaller than 0.5 kg m-2 for height differences up to 500 m. The method is applied to the inter-comparison of GPS IWV data in a tropical mountainous area and to the inter-validation of GPS and satellite microwave radiometer data. This paper also emphasizes the need for using a slope and offset regression method that accounts for errors in both variables and for correctly specifying these errors. [ABSTRACT FROM AUTHOR]

A detailed investigation of calibration variation sources in the instrumental part of the detection-fibered, water vapor Raman lidar, Rameau, is presented. This lidar has been developed by the Institut National de l'Information Géographique et Forestière (IGN) together with the Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS) and aims at calibrating GNSS wet delay signals and thus at improving vertical positioning. Several measurements campaigns enabled to validate the capacity of the instrument to retrieve high accuracy water vapor measurements. However, in order to insure a good stability, regular calibrations were necessary and led us to seek for instability sources in each sub-system of the instrument. The calibration variations are shown to be induced by fiber mode fluctuations and spatial non-uniformity of the photomultiplier photocathodes, and are responsible for significant calibration coefficient drifts. Such drifts are incompatible with both the long term stability required for applications such as climatology and the absolute accuracy needed for wet path delay correction of GNSS signals. We show by means of experimental tests that variation sources can be mitigated by means of an optimization and re-design of the optical detection system, a careful alignment procedure, and the operational monitoring of the system with dedicated measurements. In order to validate the modifications of the system and the new procedure, measurements were repeated over a period of 5 months. The detection subsystem stability was monitored from lidar profiles measured with a unique nitrogen filter used for detecting the signal in the two measurement channels. Compared to the previous campaign (Development of Methodologies for Water Vapor Measurement, Demevap), we observe an improvement in the stability of the system based on the nitrogen measurements which showed a drift of less than 3 & % per month and a standard deviation of about 3 & % during the campaign. The water vapor calibration coefficients were determined from capacitive humidity sensor measurements and from GPS zenith wet delays measurements. They show a similar small drift of 3 & % per month and a standard deviation of ~ & 6 & %. Thanks to the N2 measurements, the drift can be completely removed. Lower standard deviation can be achieved by increasing the Signal to Noise Ratio and/or spatial and temporal integration window. [ABSTRACT FROM AUTHOR]