Mapping snow avalanches hazard in poorly monitored areas. The case of Rigopiano avalanche, Apennines of Italy

Hazard mapping is carried out in Italy according to the AINEVA guidelines, which require (i) data driven avalanche dynamic modelling to assess end mark and pressure, and (ii) assessment of maximum yearly three-day snow depth increase h72 for 30 to 300 years return period. When no historical avalanche data are present, model tuning and data based assessment of avalanche return periods are hardly feasible. Also when (very) short series of h72 are available, station based quantile estimation for such high return periods is very uncertain, and regionally based approaches can be used. We apply an index value approach for the case study avalanche of Rigopiano, where a 105 m3 snow mass hit the Rigopiano Hotel killing 29 persons on January 18th 2017. This area is poorly monitored avalanche wise, and displays short series (max 14 years) of snow depth measurements, no historical avalanche maps are available on the avalanche track, and no hazard maps have been developed hitherto. First, we tune the recently developed Poly-Aval dynamic avalanche model (1D/q2D) against the 18th January event data (release zone, release depth, end mark) from different sources. We then use snow data from 7 snow stations in Abruzzo (75 equivalent years of data) to tune a regionally valid distribution of h72. We then calculate the 30-years, 100-years, and 300-years runout zone and flow pressures, including confidence limits. We demonstrate that (i) properly tuned 1D/quasi2D models can be used for avalanche modeling even within poorly monitored area as here, and (ii) the use of regional analysis allows hazard mapping for large return periods, reducing greatly the uncertainty against canonical, single site analysis. Our approach is usable in poorly monitored regions like Abruzzo here, and we suggest that (i) avalanche hazard mapping needs to be pursued with regional approaches for h72, and (ii) confidence limits need to be provided for the proposed zoning.

NOGAPS-ALPHA model simulations of stratospheric ozone during the SOLVE2 campaign

This paper presents three-dimensional prognostic O3 simulations with parameterized gas-phase photochemistry from the new NOGAPS-ALPHA middle atmosphere forecast model. We compare 5-day NOGAPS-ALPHA hindcasts of stratospheric O3 with satellite and DC-8 aircraft measurements for two cases during the SOLVE II campaign: (1) the cold, isolated vortex during 11-16 January 2003; and (2) the rapidly developing stratospheric warming of 17-22 January 2003. In the first case we test three different photochemistry parameterizations. NOGAPS-ALPHA O3 simulations using the NRL-CHEM2D parameterization give the best agreement with SAGE III and POAM III profile measurements. 5-day NOGAPS-ALPHA hindcasts of polar O3 initialized with the NASA GEOS4 analyses produce better agreement with observations than do the operational ECMWF O3 forecasts of case 1. For case 2, both NOGAPS-ALPHA and ECMWF 114-h forecasts of the split vortex structure in lower stratospheric O3 on 21 January 2003 show comparable skill. Updated ECMWF O3 forecasts of this event at hour 42 display marked improvement from the 114-h forecast; corresponding updated 42-hour NOGAPS-ALPHA prognostic O3 fields initialized with the GEOS4 analyses do not improve significantly. When NOGAPS-ALPHA prognostic O3 is initialized with the higher resolution ECMWF O3 analyses, the NOGAPS-ALPHA 42-hour lower stratospheric O3 fields closely match the operational 42-hour ECMWF O3 forecast of the 21 January event. We find that stratospheric O3 forecasts at high latitudes in winter can depend on both model initial conditions and the treatment of photochemistry over periods of 1-5 days. Overall, these results show that the new O3 initialization, photochemistry parameterization, and spectral transport in the NOGAPS-ALPHA NWP model can provide reliable short-range stratospheric O3 forecasts during Arctic winter.