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by Borderies, M., Caumont, O., Delanoë, J., Ducrocq, V. and Fourrié, N.
Abstract:
The article reports on the impact of the assimilation of wind vertical profile data in a kilometre-scale NWP system on predicting heavy precipitation events in the north-western Mediterranean area. The data collected in diverse conditions by the airborne W-band radar RASTA (Radar Airborne System Tool for Atmosphere) during a 45-day period are assimilated in the 3-h 3DVar assimilation system of AROME. The impact of the length of the assimilation window is investigated. The data assimilation experiments are performed for a heavy rainfall event, which occurred over south-eastern France on 26 September 2012 (IOP7a), and over a 45-day cycled period. During IOP7a, results indicate that the quality of the rainfall accumulation forecasts increases with the length of the assimilation window. By contrast, on the 45-day period, the best scores against rain gauges measurements are reached with a 1hour assimilation window, which recommends to use observations with a small period centred on the assimilation time. The positive impact of the assimilation of RASTA wind data is particularly evidenced for the IOP7a case since results indicate an improvement in the predicted wind at short term ranges (2hours and 3hours) and in the 12-hour precipitation forecasts. However, on the 45-day cycled period, the comparison against other assimilated observations shows an overall neutral impact. Results are still encouraging since a slight positive improvement in the 6-, 9- and 12-hour precipitation forecasts of heavier rainfall was demonstrated.
Reference:
Borderies, M., Caumont, O., Delanoë, J., Ducrocq, V. and Fourrié, N., 2018: Assimilation of wind data from airborne Doppler cloud-profiling radar in a kilometre-scale NWP systemNatural Hazards and Earth System Sciences Discussions, 1-25.
Bibtex Entry:
@Article{Borderies_2018,
  author        = {Borderies, M. and Caumont, O. and Delanoë, J. and Ducrocq, V. and Fourrié, N.},
  title         = {Assimilation of wind data from airborne Doppler cloud-profiling radar in a kilometre-scale {NWP} system},
  journal       = {Natural Hazards and Earth System Sciences Discussions},
  year          = {2018},
  pages         = {1-25},
  month         = {sep},
  abstract      = {The article reports on the impact of the assimilation of wind vertical profile data in a kilometre-scale NWP system on predicting heavy precipitation events in the north-western Mediterranean area. The data collected in diverse conditions by the airborne W-band radar RASTA (Radar Airborne System Tool for Atmosphere) during a 45-day period are assimilated in the 3-h 3DVar assimilation system of AROME. The impact of the length of the assimilation window is investigated. The data assimilation experiments are performed for a heavy rainfall event, which occurred over south-eastern France on 26 September 2012 (IOP7a), and over a 45-day cycled period. During IOP7a, results indicate that the quality of the rainfall accumulation forecasts increases with the length of the assimilation window. By contrast, on the 45-day period, the best scores against rain gauges measurements are reached with a 1hour assimilation window, which recommends to use observations with a small period centred on the assimilation time. The positive impact of the assimilation of RASTA wind data is particularly evidenced for the IOP7a case since results indicate an improvement in the predicted wind at short term ranges (2hours and 3hours) and in the 12-hour precipitation forecasts. However, on the 45-day cycled period, the comparison against other assimilated observations shows an overall neutral impact. Results are still encouraging since a slight positive improvement in the 6-, 9- and 12-hour precipitation forecasts of heavier rainfall was demonstrated.},
  copublication = {5: 5 Fr},
  doi           = {10.5194/nhess-2018-246},
  owner         = {hymexw},
  publisher     = {Copernicus {GmbH}},
  timestamp     = {2019-01-25},
  url           = {https://www.nat-hazards-earth-syst-sci-discuss.net/nhess-2018-246/},
}