December 2024 - Best look to an early December pattern in many a year!

[DavisStraight]

22 hours ago, klw said:

I made the mistake of stopping in the Stowe Market in the mid-afternoon for a couple of things.  Wow, just wow.  Just so many clueless, self involved folks.  When the aisle in front of the register is 3 feet wide, maybe find another spot for your conversation.

It's not just Stowe, I've been to the grocery store when it's slow and they'll be two women with their carriages blocking a 6 foot aisle, oblivious to any other shoppers in the store.

[ORH_wxman]

15 hours ago, ORH_wxman said:

ORH is still running too high anyways. Been that way since 2020. Crazy that it’s almost 5 years worth of data now. 
 

I meant to put together a spreadsheet but haven’t done it yet…but now that we have all the months through the end of 2024, I may line up all the monthly anomalies for first order SNE sites and then graph them. That would be the ultimate tell. 

Graph of monthly departures since January 2021 for the 4 major first order BOX climo sites

Legend:

Blue = BOS

Orange = ORH

Purple = BDL

Yellow = PVD

 

Frankly, the last 2-3 years has been particularly embarrassing....absolute clown show from ORH and BDL slipped off the reservation too. PVD (we noted this a while ago too) started going cold as well in the other direction. You can see they fixed BOS sometime in late 2021...we had known they were too warm prior to that.

 

All of these are going into the official database too to produce more normals once we get to 2030.

 

@dendrite@CoastalWx

 

 

[CoastalWx]

3 hours ago, ORH_wxman said:

Graph of monthly departures since January 2021 for the 4 major first order BOX climo sites

Legend:

Blue = BOS

Orange = ORH

Purple = BDL

Yellow = PVD

 

Frankly, the last 2-3 years has been particularly embarrassing....absolute clown show from ORH and BDL slipped off the reservation too. PVD (we noted this a while ago too) started going cold as well in the other direction. You can see they fixed BOS sometime in late 2021...we had known they were too warm prior to that.

 

All of these are going into the official database too to produce more normals once we get to 2030.

 

@dendrite@CoastalWx

 

 

Wow that's embarrassing. Look at the separation at ORH and BDL lol. And yeah PVD is cold for whatever reason.

[ORH_wxman]

3 minutes ago, CoastalWx said:

Wow that's embarrassing. Look at the separation at ORH and BDL lol. And yeah PVD is cold for whatever reason.

Solid 1-2F of separation. That’s so bad. 
 

The reason the graph is such a tell is that if differences in departures were due to random variance in weather conditions, you’d expect different stations to be warmer/colder outliers each time. But this is a consistent pattern which tells us the instrumentation is not correct.

 

[H2Otown_WX]

1 minute ago, ORH_wxman said:

Solid 1-2F of separation. That’s so bad. 
 

The reason the graph is such a tell is that if differences in departures were due to random variance in weather conditions, you’d expect different stations to be warmer/colder outliers each time. But this is a consistent pattern which tells us the instrumentation is not correct.

 

I've noted the temperature sensor runs too warm but apparently the techs don't care lol

[ORH_wxman]

4 minutes ago, H2Otown_WX said:

I've noted the temperature sensor runs too warm but apparently the techs don't care lol

Someone with an NWS tech background posted in here before and said if the ASOS thermometers are within 2F of calibration, it “passes”. 
 

I remember being astounded that it wasn’t an order of magnitude less than that. 

[CoastalWx]

17 minutes ago, ORH_wxman said:

Someone with an NWS tech background posted in here before and said if the ASOS thermometers are within 2F of calibration, it “passes”. 
 

I remember being astounded that it wasn’t an order of magnitude less than that. 

That seems risky if there is a ZR issue. That happened at KBOS. They had 34F and ZR falling. Call me crazy, but the aviation industry might care about that lol.

 

I actually had to let my former team know about that when forecasting. Hey no big deal, it's 34 and snow. Yeah, not really lol.

[SJonesWX]

1 hour ago, ORH_wxman said:

Someone with an NWS tech background posted in here before and said if the ASOS thermometers are within 2F of calibration, it “passes”. 
 

I remember being astounded that it wasn’t an order of magnitude less than that. 

you would think that NWS (or some scientist somewhere) would want accurate data to be able to accurately track the rate of CC. i understand that one ASOS is not the issue, but if we are not getting good data across the board, how can it be trusted? NOTE that this is not an argument for or against CC.

[ORH_wxman]

33 minutes ago, SJonesWX said:

you would think that NWS (or some scientist somewhere) would want accurate data to be able to accurately track the rate of CC. i understand that one ASOS is not the issue, but if we are not getting good data across the board, how can it be trusted? NOTE that this is not an argument for or against CC.

CC monitoring on a global or even national scale won't be affected by a few bad data points....there's so many of them that it amounts to a rounding error. But it will certainly affect the local climo records. When you have a 5 year period that is consistently calibrated 1-2F too warm, that would definitely be a problem. It will also affect model verification stats and could be an increasing problem for models that learn from observed data. If the models are accurate for their temps, but they "think" they are running 1-2F too cold versus reality when they actually aren't, that would be an issue too.

[SJonesWX]

11 minutes ago, ORH_wxman said:

CC monitoring on a global or even national scale won't be affected by a few bad data points....there's so many of them that it amounts to a rounding error. But it will certainly affect the local climo records. When you have a 5 year period that is consistently calibrated 1-2F too warm, that would definitely be a problem. It will also affect model verification stats and could be an increasing problem for models that learn from observed data. If the models are accurate for their temps, but they "think" they are running 1-2F too cold versus reality when they actually aren't, that would be an issue too.

agreed-I guess my point regarding "a few" bad data points, is that if us weenies (and of course you Mets) notice that temp discrepancies, and they are not addressed for a long time, it's a problem like you said. 

I'll not beat a dead horse on this. I just think that unless the data being used is confirmed to be accurate (regular instrument calibration, etc), it shouldn't be used to used to support the CC debate (on either side) or for climate records. for all we know, a certain percentage of the data is skewed too low, which would mean that CC is way worse than we think.

[Layman]

18 hours ago, SJonesWX said:

agreed-I guess my point regarding "a few" bad data points, is that if us weenies (and of course you Mets) notice that temp discrepancies, and they are not addressed for a long time, it's a problem like you said. 

I'll not beat a dead horse on this. I just think that unless the data being used is confirmed to be accurate (regular instrument calibration, etc), it shouldn't be used to used to support the CC debate (on either side) or for climate records. for all we know, a certain percentage of the data is skewed too low, which would mean that CC is way worse than we think.

This is critical for science to be meaningful and useful.  It should be the utmost priority in any realm to ensure the input data is accurate.  Tip was referring to multiple studies just yesterday citing how they were "science'd" (I believe that was the term he used) and peer reviewed/confirmed.  If your input data is inaccurate, your peer-reviewed output data is also inaccurate.  I'm not sure what data specifically was being used there and can't say one way or the other if that data was accurate but the point is much bigger than the accuracy of a handful of studies.  The principles of science must be adhered to so it can be relied upon in all realms it's deployed.  Whether it's improperly calculated instruments, human error, lax testing/recording, biased influencing, or any other inaccurate input it degrades the usefulness of the output.  Perhaps, and realistically considering, science has always been this way and the innate level of ignorance borne from that has instilled too much confidence.  With so much data at our fingertips now it's easy for a pro or average Joe to spot inconsistencies/inaccuracies and it certainly muddies the water of reliable consensus.  

[ORH_wxman]

1 hour ago, Layman said:

This is critical for science to be meaningful and useful.  It should be the utmost priority in any realm to ensure the input data is accurate.  Tip was referring to multiple studies just yesterday citing how they were "science'd" (I believe that was the term he used) and peer reviewed/confirmed.  If your input data is inaccurate, your peer-reviewed output data is also inaccurate.  I'm not sure what data specifically was being used there and can't say one way or the other if that data was accurate but the point is much bigger than the accuracy of a handful of studies.  The principles of science must be adhered to so it can be relied upon in all realms it's deployed.  Whether it's improperly calculated instruments, human error, lax testing/recording, biased influencing, or any other inaccurate input it degrades the usefulness of the output.  Perhaps, and realistically considering, science has always been this way and the innate level of ignorance borne from that has instilled too much confidence.  With so much data at our fingertips now it's easy for a pro or average Joe to spot inconsistencies/inaccuracies and it certainly muddies the water of reliable consensus.  

Attribution studies outside of empirical temperature/dewpoint increases are easily the weakest link of the climate science. Most of them are low confidence and there’s a relatively high rate of rebuttal papers that come out on those attribution studies. If you take time to read some of them, it becomes clear but the problem is a lot of them get curated in media with big headlines and nobody bothers to look deeper because they assume the headline is not only accurate, but the confidence is high…when often that is not the case at all. 
 

The waters get muddied too because if you push back on a specific attribution study or highlight the low confidence aspect of it, you’ll get accused of being a “science denier” which in my opinion, is probably the most anti-science thing you can say. Science is about asking questions and being skeptical of high-impact claims. Saying “ok, let’s see some more robust data on this before confidently making headline claims” is not being anti-science. It’s being pro-science. 
 

I have fairly high confidence in most of the datasets being used in climate science. There’s obviously some problems on smaller scales (such as the ASOS temp discussion here) but the larger scale impacts of those should be fairly minimal. The biggest weakness is not the datasets themselves, but the statistical application of that data and some of the climate models being used to analyze that data. You see some p-hacking to squeeze stuff inside the 2-sigma confidence intervals and on top of that, you’ll frequently get “scenarios” in the climate models and only the tail-end scenario makes the headline when it’s somewhere between excessively unlikely and completely unrealistic.