![]() Further, the snowfall accumulation is divided by the event hours in (e) westerly and (f) easterly snowfall regimes. The total sum ( ∑) of the precipitation hours is presented in the figure legend for the 27 precipitation days. (c),(d) The event hours observed at the DFAR and OESR and the simulated precipitation hours in the NWPs. 5, the separation into wind speed regimes is done for the corrected simulated wind for MEPS, CTRL, and ICE-T. According to the correlation equation in Fig. The sum ( ∑) over the 27 days of total precipitation accumulation in each snowfall regime is presented in the figure legend in (a) and (b). Surface snowfall accumulation for DFAR observations, OESR, MEPS, CTRL, and ICE-T, separated into (a) westerly and (b) easterly snowfall regimes for 27 precipitation days during winter 2016/17. The gray dashed lines represent the line of equality where model simulations are equal to observations. The red line indicates the linear correlation between DFAR and OESR. 2019) according to the correlation equation between 10-m wind speeds observed at the DFAR and (a) MEPS, (b) CTRL, and (c) ICE-T. We reduced the known 10-m wind bias ( Frogner et al. This figure is adapted from Schirle et al. (b) Examples of large precipitating crystals observed during the westerly snowfall regime. (a) Typical snowflake habits observed during events classified in the easterly snowfall regime. (b) An example during an easterly snowfall regime with low wind speeds and light precipitation of convective nature, on 9–. The westerly snowfall regime was associated with interchanging patterns of high and low reflectivities during snowfall. (a) The time series for a westerly snowfall regime case during high wind speed on 24–. Colors indicate the 10-m wind speed categories used in this study.Įxamples of MRR reflectivity during the two typical snowfall regimes. Wind rose of the 10-m wind during snowfall events when 24-h accumulation ≥ 25 mm day −1 and 2-m temperature < 2☌ measured at HTS, during winter 2016/17. (d) Additional instruments installed during HiLaMS during winter 2016/17: Multi-Angle Snowflake Camera (MASC), Precipitation Imaging Package, and Micro Rain Radar (MRR) shown from left to right, respectively. The arrow indicates the westerly wind direction. (c) DFAR, unprotected precipitation gauges, and meteorological mast at HTS. HTS is surrounded by 500 m higher mountains to the west and more open to the southeast. ![]() ![]() From the DTM 10 terrain model of Geonorge (2018). The contours and shading present the elevation of the 2.5 km × 2.5 km grid cells. HTS is located in the mountainous region in Southern Norway. I still hate forecasting it, though.(a) Representation of the topography in MEPS and the MEPS model domain. Your mileage may vary, but accumulation amounts now have real-world usefulness. The mathematical integration of physics is better honed. The grid points and time steps are closer together. One reason we’ve gotten better is through improved computer modeling: We can now look at the atmosphere a little more finely. Measuring every hour, without giving the snow time to settle will give a higher amount than measuring every six. Snowflakes fill gaps in the snow pile as they fall. Officially it’s measured off the ground on a “snow board,” usually a large piece of plywood. When and how you measure snow affects the final total, too. The form it falls in obviously changes how much snow ends up on the ground. What starts in the clouds as snow can fall as sleet, rain, freezing rain, or even graupel (snowflakes pocked with rime ice). Most of the time the atmosphere warms as the flakes fall … but not always. ![]() So we forecast the amount of water, then how that water will act as it drops.
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