Improving Medium‐Range Forecasts of Rain‐on‐Snow Events in Prealpine Areas

Abstract

Rain‐on‐snow (RoS) events have caused severe floods in mountainous catchments in the recent past. Challenges in forecasting such events are uncertainties in meteorological input variables, the accurate estimation of snow cover and deficits in process understanding during runoff formation. Here, we evaluate the potential of the European Centre for Medium‐Range Weather Forecasts Integrated Forecasting System (ECMWF IFS) to forecast RoS disposition (i.e., minimum rainfall amounts, initial snow cover, and meltwater contribution) several days ahead. We thereby evaluate forecasts of rain and snowfall with disdrometer observations and show that ensemble‐based forecasts have larger potential than the high‐resolution forecast of ECMWF IFS. Then, we use ECMWF IFS weather forecasts as input to a conceptual hydrological model, which is calibrated using estimates of snow‐covered area (SCA), snow water equivalent (SWE), and discharge observations. We show that the forecast skill of this model chain is reasonably high with respect to SCA and SWE, even several days ahead. However, a number of RoS events are missed in the forecast, mainly due to an underestimation of rainfall amounts. These misses can be reduced by lowering the rainfall amount threshold for the forecast as compared to the analysis, being accompanied by only a moderate increase in false alarm rates. In contrast, the forecast of RoS disposition is found to be less sensitive to thresholds of initial snow cover and meltwater contribution. We conclude that valuable disposition warnings for RoS events can be issued several days ahead, and we illustrate this idea with a case study.

The Role of Snowmelt Temporal Pattern in Flood Estimation for a Small Snow‐Dominated Basin in the Sierra Nevada

“…Accurate simulation of ROS flooding is challenging due to various factors such as rain intensity and amount, prevailing freezing level, and spatial distribution of snow cover. Either of these uncertainties could contribute to bias in predicting the peak flow during ROS events (Fehlmann et al., 2019). Although SNOTEL simulation indicated a good match in SWE simulation in 1997, one SNOTEL site may not represent all mountain ranges, and the SNOTEL network is biased toward specific types of terrain and vegetation (Mote et al., 2016).…”

The Role of Snowmelt Temporal Pattern in Flood Estimation for A Small Snow-Dominated Basin in the Sierra Nevada

“…Last, we Except for one year (1997) when the observed streamflow peak was significantly greater than the simulated value at the USGS gauge 10296000, other periods had a very good agreement between the simulations and observations. In the calibration period, statistical comparisons of measured events (Fehlmann et al, 2019). Although SNOTEL simulation indicated a good match in 𝑆𝑆𝑆𝑆𝑆𝑆 simulation in 1997, one SNOTEL site may not represent all mountain ranges, and the SNOTEL network is biased towards specific types of terrain and vegetation (Mote et al, 2016).…”

Daily ensemble river discharge reforecasts and real-time forecasts from the operational Global Flood Awareness System

“…Prediction of convective rainfall, dominant in the tropics, remains a challenge in the current generation of NWP, including the ECMWF IFS that GloFAS are based on (Haiden et al, 2019). Additionally, hydrological prediction in regions with more challenging hydroclimate conditions, particularly snowy catchments, where simplified snow accumulation and melt processes as well as rain-on-snow events are known to be highly sensitive to error (Fehlmann et al, 2019). (1-(a), 3-(b), 5-(c), and 10-days (d)) with respect to GloFAS-ERA5 river discharge reanalysis at 5997 diagnostic river points.…”