Really, really lovely cumulonimbus action tonight! I just happened to have my drone in the car and got some solid shots of DT Seattle/Lake Washington/Mercer Island/Bellevue looking north from Skyway. Alas, the focal length of the lens doesn't do the vertical height justice and my WB was off rendering it into semi-gross HDR territory, but still... fun looking weather! It was quite windy- I was flying right at 390 ft and the drone was giving me all sorts of warnings about sustained winds/gusts.
A most incredible snow storm. At times the snowfall rates have been as heavy or slightly heavier than January 2017. Temp 27.5, Dewpoint: 27.1 with gusty east wind and very heavy snow continuing. I'm at 11 1/2" now! UNBELIEVABLE!!!! This pic does no justice at all.
NBM is quite an interesting product! Their weighting algorithm is moderately complex and dynamic, though does has some drawbacks as we saw yesterday. For those who don't know, NBM is an attempt by NOAA to create a super probabilistic forecast model that ingests output from all the models above and outputs forecast guidance for local offices that help them to gauge the relative odds of particular weather outcomes. The 'special sauce' is the post-processing, normalization and weighting that they d
They are useful for communicating warming to the public. The 2 meter temp in urbanized areas is what the majority of people experience. Obviously scientists have to be careful to make the distinction of local vs. global climate change and sometimes they are not as careful as they should be. My personal weather station tracks closely with Sea-Tac airport so I think it is fine enough as a representative site for Seattle.
What bothers me more is that like all surface obs these ASOS stations are prone to sensor drift and bias but they don’t seem to have good QC measures in place to catch that early and it’s often the general public alerting the NWS to an issue.
The fact these urbanizing UHI stations are relied on so heavily in surface climate datasets is a joke.
It’s obvious sfc datasets are corrupted because the vast majority of “observed” warming has occurred at night, even in areas where cloud cover has declined. Also, satellites are in near perfect alignment w/ sfc datasets over the oceans, but on land sfc datasets are warming up to 2X faster than satellite data in some areas.
Yes, GHG-induced warming will also skew slightly higher at night (for a multitude of reasons that require lots of jargon to explain), however it’s a minuscule difference when you actually calculate it, even if you are extra generous w/ how you construct the “fractal” of diurnal/nocturnal fluxes.
FWIW, one of the leading Apr-Jun EOFs during p8-1-2 transitions in waning niños is troughing at the coasts and a ridge in the middle of the country. There are other possible outcomes (subseasonal responses are always state dependent), but I could definitely see that pattern verifying.
Recommended Posts
Posted by The Ms. Anthrop,
insta pin. glorious cloud pics!
Recommended by Meatyorologist
19 reactions
Go to this post
Posted by Gradient Keeper,
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
Recommended by Meatyorologist
50 reactions
Go to this post
Posted by ajreich,
16 reactions
Go to this post
Posted by BLI snowman,
18 reactions
Go to this post
Join the conversation
You can post now and register later. If you have an account, sign in now to post with your account.