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Discussion papers
https://doi.org/10.5194/nhess-2019-319
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2019-319
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 19 Nov 2019

Submitted as: research article | 19 Nov 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Atmospheric Moisture Effects on Heavy Precipitation During the HyMeX IOP16 Using GPS Nudging and Dynamical Downscaling

Alberto Caldas-Alvarez1 and Samiro Khodayar1,2 Alberto Caldas-Alvarez and Samiro Khodayar
  • 1Institute of Meteorology and Climate Research (IMK-TRO), Karlsruhe Institute of Technology, Karlsruhe, P.O. Box, 76131, Germany
  • 2Mediterranean Centre for Environmental Studies (CEAM), Valencia, 46980, Spain

Abstract. Gaining insight on the interaction between atmospheric moisture and convection is determinant to improve the model representation of heavy precipitation, a weather phenomenon that every year brings casualties and important monetary losses in the western Mediterranean region. Given the large variability of atmospheric moisture, an accurate representation of its distribution is expected to reduce the errors related to the representation of moist convective processes. In this study, we assess the sensitivity of precipitating convection and underlying mechanisms during a heavy precipitation event (HyMeX intensive observation period 16) to corrections of the atmospheric moisture spatio-temporal distribution. Sensitivity experiments are carried out by nudging a homogenised data set of GPS-derived Zenith Total Delays (GPS-ZTD) with sub-hourly frequency (10 minutes) in 7 km and 2.8 km simulations with the COSMO-CLM model over the western Mediterranean region. The analysis shows that (a) large atmospheric moisture amounts (Integrated Water Vapour ~ 40 mm) precede heavy precipitation at the affected areas. This occurs 12 h before initiation over southern France and 4 h over Sardinia, north eastern Italy and Corsica (our main study area). (b) We found that the moisture is transported on the one hand, swept by a westerly large-scale front associated with an upper-level low and on the other hand evaporated from the Mediterranean Sea and north Africa. The latter moisture transport occurs in the < 1 km to 4 km layer and has been identified for this event for the first time. (c) COSMO-CLM overestimated the atmospheric humidity and precipitation amount over the study region (Corsica) and this was, to a good extent, corrected by the GPS-ZTD nudging by reducing noticeably both quantities, bringing results closer to observations. (d) The two processes that exerted the largest control on precipitation were the reduction of atmospheric instability over the island (CAPE −35 %) and the drying of the lower free troposphere bringing more dry air entrainment. Besides, the 7 km simulation showed a stronger impact for large-scale dynamical lifting at the target area, given a weakening of the represented low-pressure system and the associated wind circulation. This reduced ultimately, the intensity and number of convective updrafts represented over the island. These results highlight the large impact exerted by moisture corrections on precipitating convection and the chain of related processes leading to it across scales. Additionally. The modelling experiments demonstrated the benefit of sub-hourly GPS-ZTD nudging to improve the modelling of precipitation.

Alberto Caldas-Alvarez and Samiro Khodayar
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Alberto Caldas-Alvarez and Samiro Khodayar
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Model output to the figures in Caldas-Alvarez and Khodayar (2019) A. Caldas-Alvarez and S. Khodayar https://doi.org/10.5445/IR/1000097457

Alberto Caldas-Alvarez and Samiro Khodayar
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Short summary
Heavy precipitation costs yearly important losses and several people's lives in the Western Mediterranean. To predict better this phenomenon, we aim at understanding how the models represent the interaction between atmospheric moisture and precipitation, correcting the moisture distribution using GPS data. We found, for a case study in autumn 2012, that the improvement in the modelling of precipitation stems from relevant variations of atmospheric instability and the humidity aloft 1.5 km.
Heavy precipitation costs yearly important losses and several people's lives in the Western...
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