About the Authors:
Gunnar Noer has a MSc from the University of Oslo in 1997. He has been working as a senior forecaster at the Norwegian Meteorological Institute (MET Norway), in the forecasting department in Tromsø, since 1998. Since 2010, he has held the position as a developer for polar meteorology at MET Norway’s Development Center for Weather Forecasting. Gunnar is specializing in polar lows and the forecasting of convective winter weather and extreme weather events.
Rafael Grote is a researcher and former forecaster at MET Norway’s Development Center for Weather Forecasting. He received his Ph.D. in 2013 from the University of Oslo in collaboration with the Norwegian Polar Institute, working with the transport of reactive nitrogen into the Arctic. Thereafter, he has worked as a forecaster for MET Norway at the forecasting department for northern Norway. Since 2017, he is working as a researcher for MET Norway, specializing in ensemble prediction for the Arctic domain.
Long Spells of Snow and an Increase in Casualty Rate
Snow avalanches have always been a part of winter life in the mountainous parts of Norway. At the beginning of the year 2000, the average number of casualties was three to four every winter. In the years 2008, 2010, 2011 and 2013, there were some March months with an unusually high number of polar lows and long spells of heavy snowfall in northern Norway, and the number of accidents increased, counting between 7 and 13 casualties.
The Move to Consequence-Based Forecasting
Recently, the Norwegian Meteorological Institute (MET Norway) has moved to consequence-based forecasting. The scale of avalanche risk has been adjusted to the international classification. That means that on a normal winter day with dry weather and stable snow conditions, the warning is yellow or moderate while during ongoing heavy snowfall it is typically set at red or high.
Being aware of the high risk, skiers and others generally make the decision to stay away from areas with red snow avalanche warnings. Deciding which areas to avoid is – for several reasons – more challenging when the weather is sunny and dry, and the hazard levels are yellow. Then the mountain sides are soon crowded with eager skiers. At this level, natural or unprovoked avalanches are rare, but triggered avalanches can occur. Trigger mechanisms can be related to skiers or snowmobiles moving in the area. Hence, the hazard level at which most avalanche accidents occur is actually yellow.
Reliable weather forecasts for all weather conditions are therefore crucial in order to protect life and property. The core of the Norwegian snow avalanche service at varsom.no (see fact box) is therefore a team of four experts covering both weather and snow conditions, with input from the nationwide network of observers in the field. An important part of the work is also to raise general awareness about avalanches. This has been largely successful among local residents.
In northern Norway, the main part of the total snowfall is associated with spells of cold air outbreaks from the Arctic. As cold air crosses the Norwegian Seas, it picks up large amounts of heat and moisture and becomes highly convective. The associated wintry showers are not evenly distributed but have a tendency to cluster along lines of up to several hundred kilometers length, so called squall lines. In severe cases, the squall lines transform into polar lows with heavy snow fall and strong surface winds. Forecasting these mesoscale events is crucial in order to determine the location and intensity of the snowfall.
Forecasting Snow Showers
Numerical weather prediction models generally show lower forecast capability at high latitudes compared to other regions. Forecasting high-impact weather events in the Arctic has proven to be especially challenging. This is particularly true when it comes to polar lows and squall lines, which form along cold fronts and have enhanced convection.
The sources of uncertainty are due to gaps in the observation network, errors in the observations themselves, as well as uncertainties in the parameterisations of small-scale processes in the model, including challenges unique to the Arctic. These errors, even if originally small, may amplify with time to the point where they have a distinct effect on forecast accuracy.
The current operational numerical weather prediction model at MET Norway is the HARMONIE-AROME model, which has a horizontal grid spacing of 2.5 km. An ensemble prediction system (EPS) based on this model has been developed to include estimations of forecast uncertainties. The EPS is run with ten ensemble members on a domain covering mainland Scandinavia and the coastal waters.
Severe winter weather in northern Scandinavia typically comes from the north, and a fine-scale model is necessary to capture the conditions well. Therefore, MET Norway also runs a dedicated configuration of HARMONIE-AROME for Arctic conditions. The configuration AROME Arctic covers the geographical area from northern Scandinavia to north of Svalbard, closely covering WMO METAREA XIX. AROME Arctic is currently our main tool to forecast polar lows and other meteorological phenomena that cause convective snowfall in northern Norway.
Advancing the Use of Probabilistic Forecasting
AROME Arctic is currently run four times per day but not in an ensemble setup, and therefore gives limited indication of the uncertainty of the forecast. However, as part of the Alertness research project, researchers are now developing an ensemble setup similar to the model run over the Scandinavian mainland domain, but adapted to Arctic conditions and challenges.
A part of this work is to implement perturbation methods for sea-surface temperature and sea-ice concentrations. The improvement of those particular aspects in the ensemble generation is vital, since especially the sea-surface temperature is one of the determining factors for the formation of snow showers in northern Norway. Indeed, one of the most prominent research issues for short-range predictability in polar areas is to understand complete forecast misses of polar lows; i.e. cases in which a polar low was not predicted or cases where a polar low was predicted but did not develop.
Communicating Uncertainties to the Public
In the Arctic, the societal value of fundamental weather research – like in Alertness – is strongly conditioned upon the ability to provide forecasts and warnings that user groups can incorporate in their decision-making processes. Conveying uncertainty and correct estimates of severe snowfall to the general public is not easy, as it involves concepts like probabilities and impact levels which may not be fully understood by the layman. This requires substantial skill from the forecaster, both as a communicator and as an interpreter of the physical processes involved.
Routinely, weather warnings and snow avalanche forecasts are issued on the Yr web page as well as on varsom.no. In addition, MET Norway reaches out to the public through local media and social media channels, especially the Twitter account @Meteorologene. Norwegians are generally quite well informed on the subject of the weather, and it is an enjoyable challenge for the forecaster to convey rather advanced weather information. The dedicated avalanche meteorologists enjoy an even greater freedom to do good descriptive forecasts with more specific focus on mountainous and local weather for the discerning public of mountaineers in Norway.
About the Alertness Project
Alertness (Advanced models and weather prediction in the Arctic) is a 4-year research project about Arctic weather prediction financed by the Norwegian Research Council and led by the Norwegian Meteorological Institute (MET Norway).
The ambition and primary objective of the Alertness research project is to develop world leading capacity for the delivery of reliable and accurate Arctic weather forecasts and warnings. These will benefit maritime operations, business and society.
Alertness is a cooperation between MET Norway, University of Bergen (UiB), Uni Research (UNI), University of Tromsø (UiT), The Royal Netherlands Meteorological Institute (KNMI), Nansen Environmental and Remote Sensing Center (NERSC), and The University Centre in Svalbard (UNIS).