Articles | Volume 21, issue 1
Nat. Hazards Earth Syst. Sci., 21, 463–480, 2021
https://doi.org/10.5194/nhess-21-463-2021

Special issue: Hydrological cycle in the Mediterranean (ACP/AMT/GMD/HESS/NHESS/OS...

Nat. Hazards Earth Syst. Sci., 21, 463–480, 2021
https://doi.org/10.5194/nhess-21-463-2021

Research article 01 Feb 2021

Research article | 01 Feb 2021

Data assimilation impact studies with the AROME-WMED reanalysis of the first special observation period of the Hydrological cycle in the Mediterranean Experiment

Nadia Fourrié et al.

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Cited articles

Benjamin, S. G., Schwartz, B. E., Szoke, E. J., and Koch, S. E.: The Value of Wind Profiler Data in U.S. Weather Forecasting, B. Am. Meteorol. Soc., 85, 1871–1886, https://doi.org/10.1175/BAMS-85-12-1871, 2004. a
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Bielli, S., Grzeschik, M., Richard, E., Flamant, C., Champollion, C., Kiemle, C., Dorninger, M., and Brousseau, P.: Assimilation of water-vapour airborne lidar observations: impact study on the COPS precipitation forecasts, Q. J. Roy. Meteorol. Soc., 138, 1652–1667, https://doi.org/10.1002/qj.1864, 2012. a, b
Bock, O., Bosser, P., Pacione, R., Nuret, M., Fourrié, N., and Parracho, A.: A high-quality reprocessed ground-based GPS dataset for atmospheric process studies, radiosonde and model evalu ation, and reanalysis of HyMeX Special Observing Period, Q. J. Roy. Meteorol. Soc., 142, 56–71, https://doi.org/10.1002/qj.2701, 2016. a, b, c, d, e, f, g, h
Boniface, K., Ducrocq, V., Jaubert, G., Yan, X., Brousseau, P., Masson, F., Champollion, C., Chéry, J., and Doerflinger, E.: Impact of high-resolution data assimilation of GPS zenith delay on Mediterranean heavy rainfall forecasting, Ann. Geophys., 27, 2739–2753, https://doi.org/10.5194/angeo-27-2739-2009, 2009. a
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Short summary
The assimilation impact of four observation data sets on forecasts is studied in a mesoscale weather model. The ground-based Global Navigation Satellite System (GNSS) zenithal total delay data set with information on humidity has the largest impact on analyses and forecasts, representing an evenly spread and frequent data set for each analysis time over the model domain. Moreover, the reprocessing of these data also improves the forecast quality, but this impact is not statistically significant.
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