Asymmetricity of ground-based GPS slant delay data

International audienceThe ground-based measurements of the Global Positioning System (GPS) allow estimation of the tropospheric delay along the slanted signal paths through the atmosphere. The meteorological exploitation of such slant delay (SD) observations relies on the hypothesis of azimuthal asymmetry of the information content. This article addresses the validity of the hypothesis. A new concept of asymmetricity is introduced for studying the SD observations and their model counterparts. The asymmetricity is defined as the ratio of the absolute asymmetric delay component to total SD. The model counterparts are determined from 3-h forecasts of a numerical weather prediction (NWP) model, run with four different horizontal resolutions. The SD observations are compared with their model counterparts with emphasis on cases of high asymmetricity in order to see whether the observed asymmetry is a real atmospheric signature. The asymmetricity is found to be of the order of a few parts per thousand. Thus, the asymmetric delay component barely exceeds the assumed standard deviation of the SD observation error. However, the observed asymmetric delay components show a statistically significant meteorological signal. Benefit of the asymmetric SD observations is therefore expected to be taken in future, when NWP systems will explicitly represent the small-scale atmospheric features revealed by the SD observations

Azimuthal asymmetry in ground-based GPS slant delay observations and their NWP model counterparts

International audienceThe ground-based measurements of the Global Positioning System (GPS) allow estimation of the tropospheric delay along the slanted signal paths through the atmosphere. The meteorological exploitation of such slant delay (SD) observations relies on the hypothesis of azimuthal asymmetry of the information content. This article addresses the validity of the hypothesis. The asymmetric properties of the SD observations and their model counterparts are investigated. In this study, the model counterparts are based on 3-h forecasts of a numerical weather prediction (NWP) model, run with four different horizontal resolutions. The SD observations are compared with their model counterparts with emphasis on cases of high asymmetry in order to see whether the observed asymmetry is a real atmospheric signature. The asymmetric delay component is found to be of the order of a few parts per thousand of the absolute SD value, thus barely exceeding the assumed standard deviation of the SD observation error. However, the observed asymmetric delay components show a statistically significant meteorological signal. Benefit of the asymmetric SD observations is therefore expected to be taken in future, when NWP systems will explicitly represent the small-scale atmospheric features revealed by the SD observations

Doppler radar radial winds in HIRLAM. Part I : observation modelling and validation

An observation operator for Doppler radar radial wind measurements is developed further in this article, based on the earlier work and considerations of the measurement characteristic. The elementary observation operator treats radar observations as point measurements at pre-processed observation heights. Here, modelling of the radar pulse volume broadening in vertical and the radar pulse path bending due to refraction is included to improve the realism of the observation modelling. The operator is implemented into the High Resolution Limited Area Model (HIRLAM) limited area numerical weather prediction (NWP) system. A data set of circa 133 000 radial wind measurements is passively monitored against the HIRLAM six-hourly background values in a 1-month experiment. No data assimilation experiments are performed at this stage. A new finding is that the improved modelling reduces the mean observation minus background (OmB) vector wind difference at ranges below 55 km, and the standard deviation of the radial wind OmB difference at ranges over 25 km. In conclusion, a more accurate and still computationally feasible observation operator is developed. The companion paper (Part II) considers optimal super-observation processing of Doppler radar radial winds for HIRLAM, with general applicability in NWP

Doppler radar radial winds in HIRLAM. Part II : optimizing the super-observation processing

Doppler radar radial wind observations are modelled in numerical weather prediction (NWP) within observation errors which consist of instrumental, modelling and representativeness errors. The systematic and random modelling errors can be reduced through a careful design of the observation operator (Part I). The impact of the random instrumental and representativeness errors can be decreased by optimizing the processing of the so-called super-observations (spatial averages of raw measurements; Part II). The super-observation processing is experimentally optimized in this article by determining the optimal resolution for the super-observations for different NWP model resolutions. A 1-month experiment with the HIRLAM data assimilation and forecasting system is used for radial wind data monitoring and for generating observation minus background (OmB) differences. The OmB statistics indicate that the super-observation processing reduces the standard deviation of the radial wind speed OmB difference, while the mean vector wind OmB difference tends to increase. The optimal parameter settings correspond at a measurement range of 50 km (100 km) to an averaging area of 1.7 km(2) (7.3 km(2)). In conclusion, an accurate and computationally feasible observation operator for the Doppler radar radial wind observations is developed (Part I) and a super-observation processing system is optimized (Part II)