midatlanticweather

1.6 inches. Not bad.

This is really nice. Coming down at a good clip. Everything covered!

Watching a lot of the US for the potential of heavy snow! No bad comments!

A lot of snow not too far away!

I have mixed feelings on this. I do wish we had better models, but they are pretty dang amazing! The many variables that are challenges for storms makes the hunt and chase fun too.. the issue is, we do not bag many storms. It is the reality. BUT it is all a learning thing. The hunt, to me, is very exciting.. I love a good snow and I love watching it fall and the way it coats everything.... BUT IMMEDIATELY - I am checking models for the next system.. it is like crack! LOL!

When is the next window?

According to ChatGPT Kuchera ratios are used in meteorology to estimate snowfall amounts based on the temperature profile in the atmosphere. They provide a more accurate prediction of snow-to-liquid ratios compared to the standard 10:1 rule, which assumes 10 inches of snow for every inch of liquid water. Steps for Kuchera Ratio Calculations: Gather Atmospheric Data: Obtain vertical profiles of temperature and humidity from numerical weather models (e.g., GFS, ECMWF, NAM). This is often visualized in a Skew-T diagram. Identify Critical Layers: Look at the temperature profile throughout the atmosphere. Snowfall efficiency depends on whether temperatures are conducive to dendritic growth, typically between -12°C and -18°C. Check for layers above freezing, which could cause melting and affect snow ratios. Estimate Snow-to-Liquid Ratio: The Kuchera method calculates a dynamic snow-to-liquid ratio based on the temperature and saturation levels at various atmospheric layers. Ratios are higher (e.g., 15:1 or more) in colder, fluffier snow conditions and lower (e.g., 8:1 or less) in wetter snow. Calculate Liquid Precipitation Amount: Determine the total precipitation amount forecasted in liquid form (usually in inches). Apply Kuchera Ratios: Multiply the liquid precipitation forecast by the Kuchera snow ratio for each time or grid point to estimate total snowfall. Models often automate this step. Example: If a model predicts 1 inch of liquid equivalent precipitation: A Kuchera ratio of 12:1 gives 12 inches of snow. A ratio of 8:1 (wet snow) gives 8 inches. A ratio of 15:1 (light, fluffy snow) gives 15 inches. Kuchera ratios consider temperature dependencies, making them more reliable for variable snow conditions than static assumptions.

With this kind of setup, a correction north --- or south (more possible) could be seen! This looked pretty good! It gets all VA some love (except maybe far SE VA)!

Banter, but you reminded me of this funny bit https://www.facebook.com/share/r/14GLnrQvHC/

May need to outsource to get it fixed.

This was our big tree

Such a pretty snow

Rant:: Let's do 10:1 posts for snow maps. If you want to do Kuchera.. Fine.. I like Kuchera when we are borderline and it cuts down totals because 10:1 is unlikely, but it seems always overdone and it is annoying to keep seeing them. Do 10:1 maps and then we will let mets to do analysis on dendrites when we get close.

The cool thing with this light snow is that it covered all the dirty snow from shoveling and plowing. So pretty outside just some light snow grains and snow flaks at times here in Purcellvillle

This looks pretty healthy

We squeezed out a bit more since this morning's measure and were briefly close to 4 inches. Sleet mixes in when there is not much precipitation. 24/23

Liking the radar. More snow is coming down! Let's add some more!

Disappointing in Purcellville. About 3.3 inches thus far.. some spurts of heavier and then very light snow... been kind of depressing.

That snow hole in Central Loudoun has been sad! Friends in northern Loudoun were already reporting heavy snow! Started here about 12:18am - Not too heavy yet!

I hate the HRRR 29/9

NWS went high at about 3:30PM - I wonder if this was intentional? Seems a bit high and low in some spots!

NAM'D

Maybe people are already discussing - but the models definitely showing this trend.