The impact of GPS and high-resolution radiosonde nudging on the simulation of heavy precipitation during HyMeX IOP6

Abstract

Abstract. Heavy precipitation is one of the most devastating weather extremes in the western Mediterranean region. Our capacity to prevent negative impacts from such extreme events requires advancements in numerical weather prediction, data assimilation, and new observation techniques. In this paper we investigate the impact of two state-of-the-art data sets with very high resolution, Global Positioning System (GPS)-derived zenith total delays (GPS-ZTD) with a 10 min temporal resolution and radiosondes with ∼ 700 levels, on the representation of convective precipitation in nudging experiments. Specifically, we investigate whether the high temporal resolution, quality, and coverage of GPS-ZTDs can outweigh their lack of vertical information or if radiosonde profiles are more valuable despite their scarce coverage and low temporal resolution (24 to 6 h). The study focuses on the Intensive Observation Period 6 (IOP6) of the Hydrological cycle in the Mediterranean eXperiment (HyMeX; 24 September 2012). This event is selected due to its severity (100 mm/12 h), the availability of observations for nudging and validation, and the large observation impact found in preliminary sensitivity experiments. We systematically compare simulations performed with the Consortium for Small-scale Modeling (COSMO) model assimilating GPS, high- and low-vertical-resolution radiosoundings in model resolutions of 7 km, 2.8 km, and 500 m. The results show that the additional GPS and radiosonde observations cannot compensate for errors in the model dynamics and physics. In this regard the reference COSMO runs have an atmospheric moisture wet bias prior to precipitation onset but a negative bias in rainfall, indicative of deficiencies in the numerics and physics, unable to convert the moisture excess into sufficient precipitation. Nudging GPS and high-resolution soundings corrects atmospheric humidity but even further reduces total precipitation. This case study also demonstrates the potential impact of individual observations in highly unstable environments. We show that assimilating a low-resolution sounding from Nîmes (southern France) while precipitation is taking place induces a 40 % increase in precipitation during the subsequent 3 h. This precipitation increase is brought about by the moistening of the 700 hPa level (7.5 g kg−1) upstream of the main precipitating systems, reducing the entrainment of dry air above the boundary layer. The moist layer was missed by GPS observations and high-resolution soundings alike, pointing to the importance of profile information and timing. However, assimilating GPS was beneficial for simulating the temporal evolution of precipitation. Finally, regarding the scale dependency, no resolution is particularly sensitive to a specific observation type; however, the 2.8 km run has overall better scores, possibly as this is the optimally tuned operational version of COSMO. Future work will aim at a generalization of these conclusions, investigating further cases of the autumn 2012, and the Icosahedral Nonhydrostatic Model (ICON) will be investigated for this case study to assert whether its updates are able to improve the quality of the simulations.