All the Information!
Disclaimer: I have no formal education in meteorology. I take no responsibility for you getting skunked, pissed on, or washed off your objective. This is the Pacific Northwet, after all.
This post will cover a few basic notes about forecasting and then list many resources that I use, explaining the use of each resource.
Missed the basics? Check out Part 1: General Weather Concepts for the PNW.
TLDR: Weather forecasting is a complicated topic. A complete sense of the forecast comes from looking at many sources and understanding uncertainty and the probability of different outcomes.
Some Notes on Weather Forecasting
Weather forecasting is a complex science. I am not going to focus on how the forecasting is accomplished, since I know nothing about this. However, here a are a few notes that are helpful background information before we dive into the various resources:
Forecasting is a prediction, not a certainty. Yes, I feel like it needs to be said. Forecasts often turn out incorrect. They are just based on observations and past trends. Not everything can be predicted. That is part of the game.
Uncertainty increases with the period of the forecast. A weather forecast for the next day is usually quite reliable, but a weather forecast a week out has a great deal of uncertainty. Understanding how much uncertainty is in a forecast is an important part of making a sound decision.
A true weather forecast is not a single forecast, but an ensemble of probabilities. The simplified forecasts that most people use show a single temperature, a single emoji (sun, cloud, rain) and a single percentage of precipitation. The real story is much more complicated. Weather outcomes are a continuous probability distribution. There are many possible outcomes on a continuous spectrum, and each of them has different probabilities on a given day. Understanding the range of outcomes is very helpful versus believing a single forecast.
There are different “weather models”. A numerical weather model is a computer simulation of the atmosphere. The simulations are based on past inputs and outputs, “learning” much like people do. There are many different models: the Euro model, the GFS, the North American (NAM). In general, like all things Euro, the Euro Model is considered to be superior to the American GFS and NAM, so when we see discrepancies between the models, I generally trust the Euro.
A model itself contains many “ensemble members”. Each ensemble member uses slightly different “learning parameters” in the computer simulation. No member is necessarily more correct than the others. Sometimes different members can produce wildly different forecasts. The variation of outcomes that each member is predicting can be observed to predict the likelihood of different outcomes.
You are probably familiar with the National Weather Service and its point forecasts. I believe their forecasts rely mostly on the GFS but also take into account other models through more manual adjustments by forecasters. You can click on “Hourly Weather Forecast” near the bottom for graphs that show cloud cover, precipitation, and temperature by hour.
One thing that I appreciate about the NWS forecast is that it has manual adjustments when needed. While some of the other sources listed here, like Windy.com, are purely automated, the NWS has humans that will go in and manually adjust parameters when they feel like the models are not quite correct. This is particularly relevant during extreme weather, which the models sometimes fail to understand properly because there is a lack of precedence in the training data.
The forecast discussion accompanies my breakfast each morning. I find it very helpful to get a high level, qualitative overview of the general short term and long term weather patterns we are in. This is also a great place to start learning more weather terms and phenomenons. It is also super helpful for interpreting the forecasts and discerning uncertainty. For example, the forecast discussion might explain the nature of that pesky “20% chance showers, partly sunny” forecast: is it just a possibility of convective showers in the afternoon or are the models completely split and thus the forecast is just reverting to the mean?
Windy.com is probably the best all-around weather website (and mobile app) for hard core recreationists. You can view forecasted precipitation totals, wind patterns, and snowfall. Point forecasts include the Euro, GFS, NAM, and other models. The meteogram shows cloud levels, which can be a challenging forecast to find. If you do not already, you should have this app on your phone.
Windy is incredibly useful for seeing big picture atmospheric trends like winds, temperature, and precipitation. The point forecasts at different elevations can be interesting. Generally, I find that estimating temperature at elevation is very challenging because it is dependent on vertical mixing and there is a lack of datapoints coming from high in the Cascades, so it is hard for the models to calibrate. Additionally, the “real feel” can be much different than the actual temperature at elevation due to a variety of factors like wind, precipitation, exertion, etc.
SpotWX does not offer anything that Windy doesn’t really: temperature, wind, and precipitation graphs for the GFS, NAM, but not the Euro. The precipitation accumulation graphs and temperature graphs are nice to look at and easy to discern information from.
The Rainier Recreational Forecast is a nice tool for climbing on Rainier specifically and also getting an understanding how temperature might vary with elevation.
I only mention MountainForecast as a resource NOT TO USE. It is really terrible, in so many ways. It greatly overestimates snowfall on any high peak, thinks that freezing level does not change during the day versus nighttime, and generally is overly optimistic about sunshine here. It is really, really bad. If you need a ray of light with a dark forecast, maybe it can provide the optimism you need.
This page shows cloud, temperature, precipitation, and wind forecasts for the European ensemble members over a 10 day window. This is perhaps the most useful tool for gauging uncertainty in the forecast. The box and whiskers plot informs you how much uncertainty a forecast contains. Not a single bar showing precipitation over the weekend? You’re pretty much guaranteed to be dry. A large spread in forecasts? Be cautious, because there is disagreement amongst the members. Uncertainty affects my trip plan in many ways. This is why reading the forecast goes far beyond reading the simple forecast, with one icon and one number.
This resource is the most useful tool for spotting “weather windows” 5-10 days out. When looking at a point forecast, you might see three straight days of nice weather a week out, but it is difficult to know the confidence in that forecast. If you look at the ensemble members and see the 90th percentile in precipitation showing no precipitation and no cloud cover, then things are actually really looking good. As always, these models can change, but it gives you a better idea of how things are setting up.
Note: This source (and other less user friendly options) use UTC time, which means the time displayed is 7 hours ahead of our Pacific timezone, when daylight savings time is active. Off daylight savings time, we are 8 hours behind.
Plumes show the predicted accumulation of rain or snow over time according to different model members. This is a great source for gauging precipitation uncertainty and precipitation timing. I personally find the University of Utah site to be more user friendly. It has a list of ski areas to choose from on the left hand menu.
The UW Department of Atmospheric Science is supposedly world class and they put out some handy products free for the public. These precipitation and snow maps show accumulations by 3 hour periods up to 72 hours. Note that the “24 hour snowfall model”, in the 72nd hour, for example, means the snowfall accumulation in the previous 24 hours leading up to 72 hours from now, so the period 2-3 days from now. For even longer term forecasts, they have extended forecasts. Note this data is GFS.
Snow Conditions / Avalanche
The Northwest Avalanche Center is an incredible resource. We get daily avalanche forecasts from all zones, telemetry, and community observations. Here is a breakdown of the useful aspects:
- Avalanche forecasts: Daily forecasts help us understand the avalanche problems and make a plan for a day in the backcountry.
- Telemetry: NWAC has nice graphs and tables with weather data from all the ski areas and a few other passes. This gives us a window into what is happening in the mountains with winds, precipitation, and temperature.
- Recent observations: Members of the community submit observations with snow conditions and avalanche observations. Read these to get an idea of details beyond the general avalanche forecast.
Consider donating to NWAC! We are fortunate to have such a well funded, operated avalanche center.
Snotel Sites are a reliable source of snow depth and snow water equivalent for a variety of locations. You can compare the stats against a typical year, which is useful for longer term planning and timing. Snotel data is particularly useful for timing the melt out of spring trips in more remote regions. You can even induce the isothermal transition of the snowpack (when the entire depth of the snowpack reaches 32 degrees and changes state) by watching the snow depth decrease but snow water equivalent stay the same.
This map shows the projected snow depth. It obviously is just a projection, extrapolated from Snotel data and other data, because there are not measurement devices everywhere. Snotel sites are more reliable, but might not have data where you want, so this can be helpful. Note that this map is California centric and is rather annoying to move up to Washington, so this unofficial snow depth map might be easier to use.
SentinelHub provides free 10m resolution satellite imagery every few days. This is a great tool to visually see snow coverage over the mountains. You cannot tell snow depth, but you can see if that road still has snow in the spring or if a lake is still frozen. You can even spot larches turning gold if you get lucky.
When we get a cold snap, I often wonder, “for how many days does it need to be below freezing for X to come in?” You might find that old trip report of ice at Vantage, but not know how conditions then compared to now. This is where historical weather comes in. You can look at daily temperature for cities going back many years and compare that to the current trend in temperatures. As you should know with ice, there are no guarantees, but this can help you evaluate if it is even worth checking. For more details about finding ice, see my other blog post.
The NWAC observation graphs and tables are the go-to source for real time weather conditions in the mountains during the winter. I watch these graphs obsessively, watching what wind, temperature, and precipitation did at the ski areas. This helps me predict the snow conditions I will find on different aspects and at different elevations. This is probably the most useful single tool with tour planning the night before, or even morning of.
Some key things I look for:
- What is the vertical temperature gradient in the atmosphere? During a storm, if the upper elevation station is trending warmer while the lower station is staying the same, that usually indicates heavy snow coming down. A larger gradient will often bring surprisingly low density snow down to the surface.
- What is the snow water density? You can look at the accumulated snow and precipitation and easily calculate the snow density. 1.5 inches of water but only 10 inches of snow? That’s 15% snow water density, and I would stay away from that!
- What are the winds doing? Winds can mess up powder just like warm temperatures or sun can. Choosing sheltered aspects is often the key.
The satellite view (GeoColor 2400×2400 for daytime) is nice when checking general extend of cloud cover or smoke.
Check radar for current rainfall. It is not as trustworthy over higher terrain, but can be useful if you are trying to nail a weather window for a dry training run in the city during a predominantly wet period.
It is generally a good idea to check road and pass conditions before heading out, and WSDOT has you covered.
Finally, ski areas usually issue a snow report. There is not usually much here than you cannot deduce from NWAC observation graphs, but sometimes their qualitative assessment is useful, although usually the omnipresent “packed powder” tells us nothing useful.
The HRRR Smoke Model is a relatively recent advance and a very useful one. Smoke forecasting is challenging, but is improving rapidly. This tool allows you to look at smoke projections up to 48 hours out. At the top, select an hour that is a multiple of 6 to see the full 48 hour forecast. I usually select “near surface smoke” although if you are interested in smoke aloft, you could select a different one.
This map shows AQI values at various locations.
Yet another source that can give you the AQI in your location or at other locations.
Whether you agree with his political views or not, Cliff Mass is a regional expert on weather and has contributed much to our weather community. Reading his blog is a great way to learn about weather topics and stay up to date on major weather events and local trends. He also has published a book “The Weather of the Pacific Northwest” that covers the basics of our weather, but in more detail than I did.
Caltopo is the greatest mapping software around but also has a fair bit of weather features. You can view avalanche data, snotel sites, fire info, and recent satellite imagery, although some of these features are for the paid subscription only. The sun exposure layer can be helpful to determining corn-o-clock.
This is a more user friendly version of the caltopo feature that does sun shading. Includes sunrise and sunset times and a nice slider for adjusting the time.
There are, of course, more weather resources, but hopefully this list can get you started!
4 thoughts on “Weather in the Cascades Part 2: Weather Forecasting and Resources”
I lol’d when I read what you said about mountain forecast bc I thought I was slick and advanced using it. Happy to be wrong and learn these better resources for very important factors, thanks Kyle!
I’ve just found Mountain Forecast to be wildly wrong in most cases, but maybe it is correct occasionally! Glad you enjoyed it!
All of my friends give me a hard time for always telling them Mountain Forecast is garbage. This was made all the more comical by one of those friends sending me this series of posts when I’m heated discussion about why I think considering Mountain Forecast is like purposely adding bad data to a data set 🙂
Mountain Forecast gives us hope, only to be crushed in a tangle of wet alder.