weatherwiz

Gotcha...I see what you're saying and I share similar thoughts. But that is the big question...is the atmosphere behaving differently? My guess is that the atmosphere may behave a bit differently. Lets say the average water temperature within the ENSO region (3.4) was 27°C. So if you get 5-consecutive trimontly periods where that average is 26.3°C that's a pretty indicative La Nina episode. These colder waters are going to have some influence on convection, etc. Let's say now the average water temperature in the ENSO region is 28°C. So 5-consecutive trimonthly periods where the average is say 27.3°C would be a defined La Nina. So in theory, we have a La Nina given the anomalies with respect to the average, but these waters are still much warmer than they used to be and I would think this is going to yield a different atmospheric response than 26°C waters. So could there be a fair assumption (which would lead to the investigation) that weak La Nina's now may actually act more like how an ENSO neutral-warm or very weak EL Nino? Rays composites regarding the tropical forcing certainly do shed some light into these ideas. Next week I'm going to plot OLR anomalies and do it with the climo breakdowns I did for temperature anomalies. While I haven't done anything with EL Nino yet I may also chart some weak EL Nino's and make a comparison as well.

That is a fantastic point. That is actually why when I did my composites I used various climo periods. If you were to look at the ONI which obviously dates back to 1950...it's comparing all those years to 1991-2020 climo...I mean is it really fair/accurate to compare an ENSO event in the 1950's or 1960's to the current climo? But my next step is to make the composites looking at tropical forcing (using OLR anomalies)...is that like what you're referring to with regarding to where the forcing is? I do agree that I think we would see stronger correlations looking at height patterns then we would with temperature anomalies. One thing to really consider too, especially regarding La Nina events is how the waters have warmed over the years. Average SST's are certainly warmer now than they were 50-60 years ago. Obviously the difference isn't substantial, but my point is is a weak La Nina now different from a weak La Nina from the 1950's or even earlier? We just classify ENSO based on temperature anomalies and longevity/consistency of these anomalies but what we consider a weak La Nina now may have been considered ENSO neutral...and with waters slightly warmer than they used to be this is certainly going to have some impact, especially with moisture content and latent heat.

Agreed...I too I think was originally using something like 1951-2010...but that too just didn't seem like enough to me, especially when doing analysis on years in the early 1900's or late 1800's. But as you know, data back then certainly has accuracy and validity questions and the majority of it I believe is all re-analysis and not actual data. One thing I've always wanted to do but I'm not good enough at math to do it (although I'm sure there are programs that can do this too but I can't program either ) but when I start getting into NAO/AO I've always wanted to create a weekly/bi-weekly version of the product instead of just a monthly value. Now I know the height anomalies are significantly greater value than the raw number but you can use the raw numbers with the creation of the height anomalies. Daily data for the NAO/AO exist and you would think it would be as easy as just adding and dividing...but that doesn't work. For example, if you were to add the daily NAO values for say January 1950 and divide by 31...the answer does not equate to what is listed for the monthly value. I've tried to read how the monthly values are derived and EOF's but lie I said...that's way beyond my math skills.

If you use this link you can customize the climo period https://psl.noaa.gov/data/atmoswrit/map/index.html Choose your source for the data set and then check subtract dataset 2 (for the dataset 2 box select the dataset) in the Enter year range if different from dataset 1 (area highlighted in blue) input your range...this will be the climate period. For variable static make sure you click on mean. This will give the anomaly. I emailed PSL well over a year ago and they gave me this link and told me these steps to make a customized climo period!

Hopefully we can get some type of crazy pattern in September otherwise this may go down as the worst severe wx season we've ever had

Agreed...there is definitely alot of subjectivity involved because there are really so many different ways you can go about things. I actually thought about doing composites from November-March as well (and that is what I had done in the past) but I wanted to focus more on the primary season and for the reason of November and March there can be a lot of transitioning going on. But I'm going to be making these same composites looking at 500 pattern, jet stream, and OLR. I have a feeling and well Ray pretty much indicated as such, you're see much stronger connections here.

Crap maybe it was a Coyote. It looked very similar to this

That's what was crossing my mind but the face structure and fur was definitely more fox like. It was a golden brown short fur coat.

Well good news is the fox seemed to be acting normal. Sniffed some grass and carried on through a narrow gap between a missing fence piece. I always thought foxes were super small and low to the ground...not this one. Maybe climate change is causing foxes to get bigger too.

Dog weighs somewhere around 50...in the 50's. The fox was pretty tall...must of been a full grown adult. I thought those suckers transited at night

Do foxes go after dogs? Was on a call and all of a sudden I see a big fox just walking through the yard. Not sure I ever seen a fox that big. Thank God the dog wasn't in the room...he probably would have went wild. Usually outside playing too around that time. The Fox would have had a 2 for 1 meal

Thank you! This is why I am really trying to evolve this to incorporate so much more. As Ray stated, ENSO is a critical piece of the puzzle, but it alone is not the overall or biggest driver. There are many other factors which need to be taken into account and consideration and perhaps the greatest challenge of all is gauging and figuring out what is driving the pattern...and more times than not it's not just one "piece" it's a combination of "pieces" and figuring out how all those pieces or interacting and driving is the greatest challenge of all.

I figured this would be right up your ally and I am looking forward to some great back-and-forth discussion from you and anyone else. To your first post, I am thrilled you made such a post. I don't want to come across and I don't want to make it seem like I am de-valuing ENSO at all. As you stated, ENSO is an extremely important piece of the puzzle. But you make a great point regarding the sample-sizes...perhaps it would be best to combine central-based and basin-wide. You're totally right, it is extremely difficult to sometimes decipher between the two. Per my breakdown I differentiated central-based from basin-wide from whether the core anomalies where between 120-170 or whether the core anomalies extended into 120-170...ultimately, those fringe ENSO regions are relatively small in comparison. This is a great idea! I'm also glad you brought up the MEI as the MEI and SOI are also important to take into account when assessing ENSO. Of course there is also the TNI (trans-nino index). I've read papers on the TNI but I am still not sure how to grasp, use, and interpret this index. Really great opening posts here! As this is a subject I am trying to do much more studying and analysis on this will be an ever expanding work. This will be expanded to look at teleconnection patterns, stratosphere, etc. I am so glad I was provided with that second link I provided where you can create anomalies based on a climo period of your choosing. I think this can yield more accurate results. IMO, comparing temperature anomalies from 1908-1909 to a climo period of 1991-2020 I think will slightly skew the integrity of the 1908-1909. Now I'm sure the differences are not that much.

(EDITED 09/14/2022) Weak Basin Wide La Nina Winter Temperature Anomalies: Moderate Basin-Wide La Nina Winter Temperature Anomalies (Includes Ensemble ONI and ONI Defined Events): Strong and Super-Strong Basin-Wide La Nina Winter Temperature Anomalies (Includes Ensemble ONI and ONI Defined Events):

(EDITED 09/14/2022) Weak East-Based La Nina Winter Temperature Anomalies (Includes Ensemble ONI and ONI Defined Events): Moderate East-Based La Nina Winter Temperature Anomalies (Includes Ensemble ONI and ONI Defined Events): Strong and Super-Strong East-Based La Nina Winter Temperature Anomalies (Includes Ensemble ONI and ONI Defined Events):

(EDITED 09/14/2022) Weak West-Based La Nina Winter Temperature Anomalies (Includes Ensemble ONI and ONI Defined Events): Moderate West-Based La Nina Winter Temperature Anomalies (Includes Ensemble ONI and ONI Defined Events): Strong and Super-Strong West-Based La Nina Winter Temperature Anomalies:

(EDITED 09/14/2022) West-Based La Nina Winter Temperature Anomalies: East-Based La Nina Winter Temperature Anomalies: Basin-Wide La Nina Winter Temperature Anomalies:

(EDITED 09/14/2022) Weak La Nina Winter Temperature Anomalies: Moderate La Nina Winter Temperature Anomalies: Strong/Super-Strong La Nina Winter Temperature Anomalies:

The purpose of this thread is not directed towards the discussion of current ENSO state or ENSO forecasting as there is a thread for that in the main form, but the purpose of this thread is to elicit discussion about ENSO and how ENSO may influence, shape, or drive global (or hemispheric) weather patterns. As we know, when it comes to long-range weather forecasting, the state of ENSO is a widely and very popular used index. However, is ENSO all that it is played out to be? It is this question here which drives the creation of this thread. The most popular metric for measuring ENSO state is the Oceanic-Nino Index (ONI). The CPC defines a La Nina event as 5-consecutive trimonthly periods in which SSTA's within region 3.4 are at least -0.5°C or colder. An EL Nino event is defined as 5-consecutive trimonthly periods in which SSTA's within region 3.4 are at least +0.5C or greater. If neither of these conditions are met, the ENSO state is said to be neutral. While the ONI is the most commonly metric used and perhaps the most universally accepted metric, the ONI is not the only metric available to measure ENSO state. In fact, there are at least 50-different definitions available to define ENSO state. A meteorologist by the name of Eric Webb has done some phenomenal work and research regarding ENSO. His work can be found on the following link https://www.webberweather.com/ensemble-oceanic-nino-index.html Eric Webb has created the Ensemble Oceanic Nino Index. Eric Webb's Ensemble ONI dates back to 1950 (compared to the ONI which dates back to 1950). Eric Webb defines an ENSO event of at least 50% of ENSO definitions met surrounding a particular month, irrespective of the events duration and/or potential discontinuities with adjacent months. (For more on ENSO definitions he explains in detail on his page linked above). In order to get started with my contribution to this thread and discussion I have done some work just focusing on La Nina Winters. My hope is to continue such work for EL Nino events as well and even focus outside the winter months. Given I have a love and fascination with long-range weather forecasting, my personal goal is to just develop and enhance those skills, or at the very least, just understand what influences global weather patterns and how those patterns correlate to local weather even better. This initial post is set to look for similarities in ENSO events with a correlation on winter (DJF) temperature anomalies across the northern hemisphere. In addition to just classifying an ENSO event, the strength of that particular event is very important as the strength can have a significant impact on the large-scale global pattern (especially in stronger events). The following guidelines (which are the most widely accepted for strength breakdown) were used: Weak Event: SSTAs +/- 0.5°C to +/- 0.9°C Moderate Event: SSTAs +/- 1.0°C to +/- 1.4°C Strong Event: SSTAs >/< +/- 1.5°C Super-strong: </> +/- 2.0°C As we all know, every ENSO event is shaped differently (each event has its own "flavor". While the state of ENSO alone is an important consideration the structure if just as, if not, perhaps more important then ENSO state alone. By structure of the ENSO event we're referring to where the core of highest anomalies are present. This can help identify whether a particular event is a west-based event, east-based event, central-based event, or basin-wide. This was something I had always seemingly struggle to do and that's how to classify this breakdown. Upon reading Ray's winter outlook last season, I was heavily influenced by what he had done. I was trying to make such a classification much harder than need be. From Ray's influence this was used as a metric to distinguish between the different structures: Before getting a bit more in-depth into some initial work I want to provide some definitions to yield some context. 1. An event was classified if ANY winter month within the trimonthly data involved a defined La Nina 2. The strength was based on the peak SSTA during the event 3. Additional notes were added to highlight borderline events - in terms of the event itself, strength, and structure (but this is not incorporated within anything posted here). Below is a list of defined La Nina Winters using Eric Webb's Ensemble ONI and the CPC's ONI along with the strength breakdown Below is a structure breakdown of La Nina Winters using Eric Webb's Ensemble ONI and the CPCs ONI along with a grouping of ENSO phase/structure/ In parenthesis indicates if it is Ensemble ONI defined, CPC defined, or both: Temperature Anomalies The first part of this project was solely focusing on temperature anomalies vs. ENSO state. So this is a breakdown of comparing temperature anomalies for the winter as a whole (DJF) based off of ENSO state (as defined by both Ensemble ONI and CPC ONI), and where core SSTA's were located within the ENSO region. This will be expanded to also analyze outgoing longwave radiation anomalies (to pinpoint where convection/subsidence is present), zonal wind anomalies (focus on trade winds and upper-level jet), sea-level pressure anomalies, and more. When it came to assessing temperature anomalies, I wanted to do something different. Due to the state of a warming climate (whether this be human-induced/influence, cyclical, or a combination of both goes beyond the realm of this scope) I didn't feel like we could compare say weak La Nina winter temperature anomalies from the early 1900's to a climatological period of 1981-2010 or the latest, 1990-2020. Using the following website https://psl.noaa.gov/data/atmoswrit/map/index.html I was able to create different climatological periods and choose which period the temperature anomalies were being compared too. I used 20th Century Reanalysis V3 (For Years 1904 to 1981) and NCEP/NCAR R1 (for years 1982 to Present) as my datasets. While Eric Webb's Ensemble ONI data goes back to 1850, the dataset for the variables (temperature) went back to like the 1880's or something. What I did was used the following climatological periods. In parenthesis would be the years used against that climatological period's mean (Note: I also did this in the construction of SSTAs which I can perhaps post in a subsequent post): In order to save space I will post a GIF of the following (Note: I will focus on just the Ensemble ONI Index here since it's a larger dataset). For now I will only post the All La Nina Winters (DJF) Temperature Anomalies and then post these additional GIFs over the coming days. I also used a consistent legend (-7°F to +7°F with an interval of 10°F). 1. All La Nina Winters (DJF) Temperature Anomalies 2. Weak La Nina Winter Temperature Anomalies 3. Moderate La Nina Winter Temperature Anomalies 4. Strong/Super-Strong La Nina Winter Temperature Anomalies 5. West-Based La Nina Winter Temperature Anomalies 6. East-Based La Nina Winter Temperature Anomalies 7. Basin-Wide La Nina Winter Temperature Anomalies 8. Weak West-Based La Nina Winter Temperature Anomalies 9. Moderate West-Based La Nina Winter Temperature Anomalies 10. Strong/Super-Strong West-Based La Nina Winter Temperature Anomalies 11. Weak East-Based La Nina Winter Temperature Anomalies 12. Moderate East-Based La Nina Winter Temperature Anomalies 13. Strong/Super-Strong East-Based La Nina Winter Temperature Anomalies 14. Weak Basin-Wide La Nina Winter Temperature Anomalies 18. Moderate Basin-Wide La Nina Winter Temperature Anomalies 19. Strong/Super-Strong Basin-Wide La Nina Winter Temperature Anomalies I'm going to bold this part here as this is likely well-beyond a TLDR post but the point of this is too illustrate a few things: Outside of perhaps moderate west-based La Nina's, weak central-based La Nina's, and Strong/Super-Strong Central-Based La Nina's there actually doesn't appear to be a very strong signal correlating La Nina episodes to temperature anomalies across the Northern Hemisphere. Another point here is when you get into breaking down into finite details the sample-sizes become way too small. So I guess my point is that I have a hypothesis that ENSO (maybe just La Nina) does not have the weight or merit that we once thought it did. All La Nina Winters (DJF) Temperature Anomalies. Through the GIF you can see the variations in temperature anomalies which exist. Over the days I'll post the additional GIFs as well. I am hoping this may elicit some awesome discussion/research. You'll notice within the loop that climatological periods change as well as the dataset of computation:

As long as we keep building high anomalies well into western and central Canada we're unlikely to see much in the way of cooldowns or anything significant with exception being northern New England. Unless we see some pretty significant changes during the second half of September we are looking at yet another very warm month with respect to climo.

Great point...you don't hear much about the lack of tropical activity or tornado activity...and the lack of tornado activity pretty much the past decade has been quite noticeable. We are setting records for like lowest tornado counts, longest stretches without EF5's, etc. Was just talking about this with Vortmax95 via email. When you look at how low of a lull we are in tornado numbers that is super impressive given the technological advances we have and how so many brief spinups are being picked up by chasers or anyone really. Same goes with cold...remember a few years back there was that pretty remarkable I think late spring cold stretch into the southern Plains...wasn't much talk about that.

This certainly is a major factor and something that exuberates these sort of events. At the end of the day we're probably our own worst enemy by building and establishing livelihoods in these high disaster prone areas. I mean look at how many people keep rebuilding along the Gulf Coast. I mean how many times do you need to see your house wiped away to realize that's probably not a good spot? I'm glad insurance companies are finally catching on.

Yeah...I'm with you. As much as I am an advocator of climate change and fully believe it's occurring and impacting climate regimes, it's also important to understand not every single weather event isn't the direct response of climate change. They are certainly prone to these type of magnitude events given where their located and influences by such phenomena as MJO activity.

It's beyond scary. It's like something out of a Sci-Fi movie. A third of the country is underwater...I don't even know how to comprehend that. But yeah...these type of 1:750-1,000 year events are becoming more and more common. And regardless of the reasonings as to why they're happening or whether they've "occurred before" means nothing...that truth of the matter is countless lives are being disrupted and destroyed.

OT but what the flooding in Pakistan is unreal....gut wrenching really. Saw some videos last night on Twitter. Those poor people.