The potential temporal shifts in the integrated water vapor (IWV) time series obtained from reprocessed data acquired from global navigation satellite systems (GNSS) were comprehensively investigated. A statistical test, the penalized maximal t test modified to account for first-order autoregressive noise in time series (PMTred), was used to identify the possible mean shifts (changepoints) in the time series of the difference between the GPS IWV and the IWV obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) data. The approach allows for identification of the changepoints not only in the GPS IWV time series but also in ERA-Interim. The IWV difference time series formed for 101 GPS sites were tested, where 47 of them were found to contain in total 62 changepoints. The results indicate that 45 detected changepoints were due to the inconsistencies in the GPS IWV time series, and 16 were related to ERA-Interim, while one point was left unverified. After the correction of the mean shifts for the GPS data, an improved consistency in the IWV trends is evident between nearby sites, while a better agreement is seen between the trends from the GPS and ERA-Interim data on a global scale. In addition, the IWV trends estimated for 47 GPS sites were compared to the corresponding IWV trends obtained from nearby homogenized radiosonde data. The correlation coefficient of the trends increases significantly by 38% after using the homogenized GPS data.
Abstract. Within the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) there is a need for an assessment of the uncertainty in the integrated water vapour (IWV) in the atmosphere estimated from ground-based global navigation satellite system (GNSS) observations. All relevant error sources in GNSS-derived IWV are therefore essential to be investigated. We present two approaches, a statistical and a theoretical analysis, for the assessment of the uncertainty of the IWV. The method is valuable for all applications of GNSS IWV data in atmospheric research and weather forecast. It will be implemented to the GNSS IWV data stream for GRUAN in order to assign a specific uncertainty to each data point. In addition, specific recommendations are made to GRUAN on hardware, software, and data processing practices to minimise the IWV uncertainty. By combining the uncertainties associated with the input variables in the estimations of the IWV, we calculated the IWV uncertainties for several GRUAN sites with different weather conditions. The results show a similar relative importance of all uncertainty contributions where the uncertainties in the zenith total delay (ZTD) dominate the error budget of the IWV, contributing over 75 % of the total IWV uncertainty. The impact of the uncertainty associated with the conversion factor between the IWV and the zenith wet delay (ZWD) is proportional to the amount of water vapour and increases slightly for moist weather conditions. The GRUAN GNSS IWV uncertainty data will provide a quantified confidence to be used for the validation of other measurement techniques.
[1] Ground-based GPS measurements can provide independent data for the assessment of climate models. We use the atmospheric integrated water vapor (IWV) obtained from GPS measurements at 99 European sites to evaluate the regional Rossby Centre Atmospheric climate model (RCA) driven at the boundaries by the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data (ERA Interim). The GPS data were compared to the RCA simulation and the ERA Interim data. The comparison was first made using the monthly mean values. Averaged over the domain and the 14 years covered by the GPS data, IWV differences of about 0.47 kg/m 2 and 0.39 kg/m 2 are obtained for RCA-GPS and ECMWF-GPS, respectively. The RCA-GPS standard deviation is 0.98 kg/m 2 whereas it is 0.35 kg/m 2 for the ECMWF-GPS comparison. The IWV differences for RCA are positively correlated to the differences for ECMWF. However, this is not the case for two sites in Italy where a wet bias is seen for ECMWF, while a dry bias is seen for RCA, the latter being consistent with a cold temperature bias found for RCA in that region by other authors. Comparisons of the estimated diurnal cycle and the spatial structure function of the IWV were made between the GPS data and the RCA simulation. The RCA captures the geographical variation of the diurnal peak in the summer. Averaged over all sites, a peak at 17 local solar time is obtained from the GPS data while it appears later, at 18, in the RCA simulation. The spatial variation of the IWV obtained for an RCA run with a resolution of 11 km gives a better agreement with the GPS results than does the spatial variation from a 50 km resolution run.Citation: Ning, T., G. Elgered, U. Wille´n, and J. M. Johansson (2013), Evaluation of the atmospheric water vapor content in a regional climate model using ground-based GPS measurements,
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.