Forecasting Winter Weather Events: How Time Impacts Winter Storm Forecasts
Updated: Oct 18
As we head into mid-October, many of us are starting to think about winter weather and forecasting. While some are looking forward to seeing the first snowflakes, others are dreading the impacts from the winter precipitation. Regardless, we all have an interest in winter weather predictions. From the time we first hear the word “snow” in the forecast, until the temperatures once again warm in the Spring, we will all be watching for any winter weather precipitation in the forecast.
While we have all seen the promises of winter weather events weeks ahead, we have also experienced how incorrect those forecasts can be! Today we are going to look at how accurate weather (in particular winter weather) forecasts are, and when more confidence can be put into the forecast, and how those change over time.
OVER TWO WEEKS
We have all seen the long-range forecasts that promise heavy snow in 3 weeks online, but often we see those forecasts bust. At 2+ weeks out, predicting the timing, amounts, and exact areas that will see winter weather is all but impossible.
However, meteorologists can see how the weather pattern is evolving during this time. Meteorologists use teleconnections, the MJO, and long-range models like the ECMWF weeklies, GEFS extended, and CFS data to get a better understanding of how the pattern will continue to evolve with time. These things can be used to draw up a general picture of the environment/pattern in the weeks to come, and meteorologists use pattern recognition to determine where the greatest likelihood (usually regionally) of where more impactful weather could occur.
While verification of certain specifics at this time is extremely low, confidence in the general weather pattern can be relatively high depending on the pattern. However, the more active the weather pattern is, the more complicated and likely low confidence the long-range outlook will tend to be.
In the day 10–14-day range, global models such as the GFS, ECMWF, and CMC operational give us their first glimpse into the medium to long range. The ensemble guidance from these three models is also a very important tool for meteorologists at this range.
Ensemble Members Show Various Outcomes for 500mb Heights
Meteorologists in this time frame may talk more about the pattern looking for conducive for a winter weather event or winter storm. However, model data is usually very low performing during this time and greatly limits confidence in more precise details. Forecast data is less than 50% accurate at this forecast range.
The 1 week to 10-day period is still a time of lower confidence. The ECMWF, GFS, CMC and their ensemble data still play an important role in the forecast.
During this period, data is still not reliable enough to start placing numbers on amounts, talking about precise locations, or even impacts with any confidence. Often, the main area of interest is still off the West Coast and has not been sampled. This lack of data can have major impacts to the forecast model output for the forecast period we desire to view. Overall, confidence is still low at this time in many aspects and generally forecast accuracy is still around 50%.
Decline of Model Forecast Scores with Respect to Time
The global weather models and their ensembles are still an important part of the forecast during this time. However, we do start to see the UKMET data available at hour 144/Day 6. This can add extra confidence or skepticism to the forecast. Teleconnections can also play a role here, as changes to the PNA, AO, and NAO can help signal the potential track of the system.
During this time, meteorologists are starting to gain more confidence in the forecast, mainly regarding the fact a more impactful storm looms. Meteorologists will talk about “monitoring” or “tracking” a potential winter storm system. However, in most instances, details are still fuzzy and there are still many questions to be answered. Forecast accuracy is still around the 50-60% mark at 5-7 days out.
The 3–5 day period can be significant when forecasting winter storms. Forecast accuracy (on average) starts to rise closer to the 80% mark by 3–4-day period. NAM 12km data also becomes available at hour 84 lending more data for forecasting. The system may also be onshore in the day 3 period which gives additional confidence to the meteorologist. At this point model data can ingest actual, observed conditions from the system allowing for models to be more accurate.
Confidence generally increases more significantly for meteorologists during this time, and is especially true if forecast guidance is consistent with the storm’s details. Outlining areas of impact, snowfall amounts, and general timing should start to be ironed out by the end of this forecast period.
However, there are times when data is not in agreement and confidence is lower. This could mean a longer waiting period for storm details as data resolves more of the smaller scale details. It is also worth mentioning that models can start to make major adjustments during this range in one direction or another. We saw this occur both in the Winter of 21-22 and 22-23 as longer-range predictions suggested impactful snowstorms, but as we got a few days out, forecast snow amounts dropped dramatically in just a couple of model runs. This is because the storm had moved onshore and actual weather observations from the incoming system were ingested into the forecast models. These observations can be different from how models were visualizing the system, making for significant alterations to the forecast.
Forecast Snowfall Amounts Shift with Time as the Storm System Comes Onshore
The day 2-3 period for winter weather forecasting is crunch time as high-resolution data such as the NAM 3km, HRRR, & RAP become available. Generally, forecast data will start to come into more agreement with the track and amounts during this time, lending greater confidence to meteorologists.
It’s during this time that greater details will emerge on timing, precipitation type, locations, and amounts. Details regarding impacts from not only precipitation, but also winds and temperatures are starting to be conveyed heavily along with potential impacts to roads, power lines, etc. The National Weather Service will start to issue Winter Storm Watches, Warnings, and Winter Weather Advisories during this period.
LESS THAN 24 HOURS
The 18-24 hours leading up to the winter weather event will provide the most data, as both the HRRR and RAP data update each hour. More importantly, conditions upstream (where the storm is coming from) can be watched for any ongoing changes. These changes can be monitored via live surface observations, radar, satellite, and other instrumentation that serve meteorologists in real-time. These real-time observations become very important in the last few hours leading up to the arrival of the precipitation.
While the last 6-12 hours can, and often do, lead to more fine-tuning of the details of the event, it is worth mentioning that high-resolution hourly data will tend to flip-flop during this time. It is important not to put all your eggs in one basket with these models as they update each hour and forecasts change. Personally, I like to see a combination of consistent forecast data output from high-res data in the hours leading up to the storm and the real-time conditions/ observations to back data up before altering any forecasts.
Overall, there are many factors that meteorologists look for when forecasting more impactful weather events that can lend or take away confidence in the forecast. It could be trends, pattern volatility, model performance, or just gut instinct. This is why having meteorologists you can trust and rely on when it comes to preparing for impactful weather is important- whether it’s snow, ice, flooding, or severe thunderstorms- and we hope that you will turn to us at TDS Weather when you are looking for the latest information all season long!
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