Impact of GPS zenith delay assimilation on convective‐scale prediction of Mediterranean heavy rainfall

From Lagrangian back trajectories it was found that the dust was mobilized from sources in Mauritania six days earlier, while the dry layer subsided over the north Atlantic. Off the Moroccan coasts, the dry layer folded down beneath the dusty air mass and the two-layer structure was advected to the Rhine valley in about two days. By heating the atmosphere, the dust layer changed the static stability of the atmosphere and thus the occurrence of convection. A study of sensitivity to the radiative effect of dust showed a better prediction of precipitation when a dust prognostic scheme was used rather than climatology or when dust effects were ignored. This result suggests that dust episodes that occur prior to convective events might be important for quantitative precipitation forecasts.

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confidence: 99%

Long‐range transport of Saharan dust and its radiative impact on precipitation forecast: a case study during the Convective and Orographically‐induced Precipitation Study (COPS)

Chaboureau

Richard

Pinty

et al. 2011

“…Retrieval of ZTD from geodetic GPS data processing makes use of fewer assumptions than the retrieval of PW; in fact, the retrieval of PW from GPS measurements requires the estimation of ZTD as an intermediate step. Therefore, significant attention has been placed on the data assimilation of ZTD observations, instead of PW, during the past decade (De Pondeca and Zou, 2001;Gustafsson, 2002;Vedel and Huang, 2004;Poli, et al, 2007;Macpherson, et al, 2008;Yan, et al, 2009). These studies differ from each other in terms of NWP system implementation, grid spacing, domain size and experiment time period.…”

Section: Introductionmentioning

confidence: 99%

“…It is possible to estimate ZTD at each receiver station with a temporal resolution of the order of a few minutes. These observations are nowadays assimilated in operational numerical weather prediction (NWP) systems at several meteorological institutes (Poli, et al, 2007;Yan, et al, 2009). The new observation type is considered welcome by the meteorological community, because of the limitations of traditional observing systems for atmospheric water vapour.…”

Section: Introductionmentioning

confidence: 99%

“…Instead, the OSEs have been based on the assumption of negligible observation-error correlations. In order to justify this assumption, horizontal thinning of the ZTD data is applied in some studies (Macpherson, et al, 2008;Yan, et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…The source of the biases is unknown, and the role of geodetic pre-processing cannot be excluded. In most impact studies, the ZTD observation biases are corrected by relatively simple algorithms, such as using a three-or ten-day running mean of ZTD observation minus background as an estimate of the bias at each receiver station (Gustafsson, 2002;Macpherson, et al, 2008), or applying a static bias correction at each receiver station (Poli, et al, 2007;Yan, et al, 2009). Air-massdependent bias-correction algorithms have also been tested (R. Randriamampianina, personal communication).…”

Section: Introductionmentioning

confidence: 99%

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An observing‐system experiment with ground‐based GPS zenith total delay data using HIRLAM 3D‐Var in the absence of satellite data

Eresmaa

Salonen

Järvinen

2010

Ground-based receiver networks of the Global Positioning System (GPS) provide observations of atmospheric water vapour with a high temporal and horizontal resolution. Variational data assimilation allows researchers to make use of zenith total delay (ZTD) observations, which comprise the atmospheric effects on microwave signal propagation. An observing-system experiment (OSE) is performed to demonstrate the impact of GPS ZTD observations on the output of the High Resolution Limited Area Model (HIRLAM). The GPS ZTD observations for the OSE are provided by the EUMETNET GPS Water Vapour Programme, and they are assimilated using three-dimensional variational data assimilation (3D-Var).The OSE covers a five-week period during the late summer of 2008. In parallel with GPS ZTD data assimilation in the regular mode, the impact of a static bias-correction algorithm for the GPS ZTD data is also assessed.Assimilation of GPS ZTD data, without bias correction of any kind, results in a systematic increase in the forecast water-vapour content, temperature and tropospheric relative topography. A slightly positive impact is shown in terms of decreased forecast-error standard deviation of lower and middle tropospheric humidity and lower tropospheric geopotential height. Moreover, verification of categorical forecasts of 12 h accumulated precipitation shows a positive impact. The application of the static bias-correction scheme is positively verified in the case of the mean forecast error of lower tropospheric humidity and when relatively high precipitation accumulations are considered.

A high‐quality reprocessed ground‐based GPS dataset for atmospheric process studies, radiosonde and model evaluation, and reanalysis of HyMeX Special Observing Period

Bock

Bosser

Pacione

et al. 2016

A special screening procedure is developed for the removal of outliers in the GPS Zenith Total Delay (ZTD) data. ZTD data are converted to integrated water vapour (IWV) using surface pressure information from an AROME-WMED operational analysis. The reprocessed ZTD and IWV data are used to assess the accuracy of the near-real time E-GVAP ZTD data assimilated in operational numerical weather prediction systems and to validate the IWV data from the AROME-WMED operational analysis and AROME-WMED reanalysis 1, and from radiosonde observations. The mean differences between E-GVAP and reprocessed ZTD data are not negligible and lie in the range from −3 to +3 mm. The standard deviations of differences are between 4 and 8 mm. The comparisons of IWV from AROME-WMED analyses and the reprocessed GPS data show high quality of the analyses where operational GPS data are assimilated and lower quality where no GPS data are assimilated. Small but significant biases are found in the radiosonde data during daytime (−0.5 to +1.4 kg m −2 ), but their origin is not determined so far. Thanks to the high spatial density of the reprocessed GPS stations, both the large-scale and small-scale variations in IWV can be documented. The case of HyMeX Intensive Observing Period 8 is presented as an example of a heavy precipitation event. This work suggests that improved quality of the humidity fields can be expected of the future AROME-WMED reanalysis 2 as a result of the assimilation of the reprocessed GPS data.