bluewave

When you understand what the models strengths and weaknesses are in the long range, then you can start to make sense of what they are trying to say. So we start with what we know about the models and work from that starting point. A model strength of the ECMWF is more accurate ENSO SST forecasts once past the spring predictability barrier. The ECMWF ENSO SST forecasts with previous super events were actually pretty good from July 2023 and 2015. So chances are increasing with each model update that this will be the strongest El Niño event on record using a metric like traditional ONI anomalies and absolute SSTs. The current SSTs are already ahead of all the previous super El Niños to this point. The long range temperature forecasts for both the 2015-2016 and 2023-2024 super El Niño events were significantly too cold. The 500 mb forecasts provided some skill but the location and the magnitude of the ridges were more expansive with weaker troughs. This has been a common theme regardless of ENSO over the last decade. The areas under the ridges had temperatures which greatly exceeded forecasts. Plus there were one month intervals in the 2023-2024 and 2015-2016 super El Niño events when the Indio-Pacific warm pool was strong enough to drive the forcing outside the typical El Niño regions. This will be the first time with two super El Niño events only three years apart. It will be both a big sensible weather event around the world and a climate event. Since each super El Niño event since 1997-1998 resulted in a big jump in global temperatures to a higher baseline. June set new all-time SST records for developing El Niños in all Nino regions except 1+2. https://www.cpc.ncep.noaa.gov/data/indices/ersst5.nino.mth.91-20.ascii All-Time June SST records in bold YR MON NINO1+2 ANOM NINO3 ANOM NINO4 ANOM NINO3.4 ANOM 2026 6 25.94 2.82 28.33 1.71 30.19 1.22 29.17 1.44 2023 6 25.63 2.50 27.88 1.26 29.55 0.58 28.57 0.84 2015 6 25.32 2.19 28.07 1.45 29.88 0.92 28.90 1.18 1997 6 26.12 3.00 28.13 1.51 29.23 0.26 28.82 1.09

It’s a good thing that there were no injuries with how close a call this was.

https://newjersey.news12.com/2026/07/06/roof-collapses-at-bjs-wholesale-club-in-ocean-township/128UzlO4BAdoGypMDmXBA6 Multiple crews are responding to a roof collapse at a BJ’s Wholesale Club in Ocean Township. The Monmouth County Sheriff’s Office said first responders are on scene at the store on Route 35 in the Oakhurst section of Ocean Township. Officials are asking people to stay clear of the area so emergency crews can respond safely. The collapse happened around 11:30 a.m. Multiple mutual aid crews from surrounding towns were also called to the scene. Law enforcement officials told News 12 that there were no injuries reported. Police said all 27 staff members who were in the building at the time are accounted for and safe. All of the customers who were in BJ's at the time of the collapse are also safe, police said. According to Ocean Township Police Chief Michael Sorrentino and Monmouth County Sheriff Shaun Golden, approximately 20% of the rear of the building has collapsed. Officials believe the damage was caused by the weight of the water from the heavy rain that fell. Authorities are also urging drivers to avoid Route 35 because of severe flooding in the area. This remains a developing story.

Radar estimates near Breezy Point over 7 inches now with training and back building convection continuing.

This was our most extreme period around July 4th with record heat, damaging winds causing power outages, and torrential downpours leading flooding.

Major flooding in Monmouth County also.

I have been under training convection several times in the past when the totals went past 5.00. The most extreme version was in August 2011 when I had 10.00 to 11.00 and most of the rain fell in less than 7 hours. Back in June 1995 I picked up 5.15 in around 90 minutes.

Portions of Orange County show what can happen with training convection in situations like these. Orange County... Otisville 7.78 in 1010 AM 07/06 NYSM Montgomery 6.01 in 1005 AM 07/06 CWOP

These Euro monthly SST forecasts show how a large portion of the ENSO regions are currently on track to set new all-time actual SSTs and anomalies.

As I have been commenting on for a while now, these expansive marine heatwaves and associated 500mb patterns can exert an influence on our weather and climate which is independent of ENSO. So at times the other marine heatwaves and associated 500mb patterns can drive the sensible weather. Then at other intervals the ENSO can have a more direct effect. Still on other occasions there is an overlapping influence. https://www.science.org/doi/10.1126/sciadv.adz4647 Marine heatwaves in the Northwestern Pacific (NWP) have become increasingly frequent and persistent, yet the mechanisms enabling their multiseasonal duration remain poorly understood. Through observational analyses and climate model experiments, we demonstrate that NWP marine heatwaves are primarily driven by a quasistationary wavenumber 5 circumglobal wave (CGW) pattern that operates independently of El Niño–Southern Oscillation. The CGW modulates surface heat fluxes during summer, triggering a self-reinforcing feedback loop where NWP warming intensifies the CGW pattern, amplifying and prolonging heatwaves across extended warm seasons. Additionally, CGW-driven summer warming in the northern North Atlantic persists into winter through oceanic thermal inertia, exciting a great-circle wave pattern that propagates back to the NWP, sustaining heatwaves through cold seasons. This interplay between atmospheric waves and trans-basin interactions enables multiyear marine heatwave events. Analysis of observational data and climate model simulations reveals a strengthening CGW influence in recent decades, indicating more frequent and prolonged NWP marine heatwaves under ongoing global warming.

You have to realize that the actual pattern isn’t always what you want it to be.

This was the warmest July 1st through 4th across the region. Several locations came close to their all-time highs. Atlantic City tied their all-time high. Time Series Summary for NEWARK LIBERTY INTL AP, NJ Warmest July 1st-4th Click column heading to sort ascending, click again to sort descending. 1 2026-07-04 89.4 0 2 2002-07-04 86.6 0 3 1966-07-04 86.0 0 4 2018-07-04 85.3 0 5 1901-07-04 84.6 0 - 1872-07-04 84.6 0 Time Series Summary for WESTCHESTER CO AP, NY Click column heading to sort ascending, click again to sort descending. 1 2026-07-04 84.5 0 2 1966-07-04 82.1 0 3 2002-07-04 81.6 0 4 2018-07-04 81.3 0 - 1964-07-04 81.3 0 5 1955-07-04 80.4 0 Time Series Summary for Poughkeepsie Area, NY (ThreadEx) Click column heading to sort ascending, click again to sort descending. 1 2026-07-04 86.1 0 2 2018-07-04 81.9 0 3 2002-07-04 81.4 0 4 1955-07-04 78.9 0 5 2013-07-04 78.1 0 Time Series Summary for Philadelphia Area, PA (ThreadEx) Click column heading to sort ascending, click again to sort descending. 1 2026-07-04 89.4 0 2 1901-07-04 89.0 0 3 1898-07-04 85.6 0 4 2018-07-04 85.3 0 5 2002-07-04 84.8 0 Time Series Summary for LAGUARDIA AIRPORT, NY Click column heading to sort ascending, click again to sort descending. 1 2026-07-04 88.6 0 2 1966-07-04 87.8 0 3 2002-07-04 86.4 0 4 2018-07-04 85.8 0 5 1955-07-04 83.9 0 Maximum 1-Day Mean Max Temperature for Poughkeepsie Area, NY (ThreadEx) Click column heading to sort ascending, click again to sort descending. Last value also occurred in one or more previous years. Period of record: 1931-01-01 to 2026-07-05 1 104.0 1933-08-01 2 103.0 2026-07-02 - 103.0 2001-08-09 - 103.0 1995-07-16 - 103.0 1966-07-03 - 103.0 1936-07-10 3 102.0 2011-07-22 - 102.0 2010-07-06 - 102.0 1991-07-20 - 102.0 1991-07-19 Maximum 1-Day Mean Max Temperature for NEWARK LIBERTY INTL AP, NJ thermometer malfunction missed the 2010 max Click column heading to sort ascending, click again to sort descending. 1 108.0 2011-07-22 2 105.0 2026-07-02 - 105.0 2001-08-09 - 105.0 1993-07-10 - 105.0 1993-07-08 - 105.0 1966-07-03 - 105.0 1953-09-02 - 105.0 1949-07-04 - 105.0 1918-08-07 3 104.0 2012-07-18 - 104.0 1995-07-15 - 104.0 1993-07-09 - 104.0 1936-07-09 Maximum 1-Day Mean Max Temperature for HARRISON, NJ Click column heading to sort ascending, click again to sort descending. 1 107.0 2011-07-22 2 106.0 2026-07-03 - 106.0 2010-07-06 3 104.0 2001-08-09 4 103.0 2026-07-04 - 103.0 2025-06-25 - 103.0 2025-06-24 - 103.0 2012-07-18 Maximum 1-Day Mean Max Temperature for LAGUARDIA AIRPORT, NY Click column heading to sort ascending, click again to sort descending. 1 107.0 1966-07-03 2 104.0 2026-07-02 - 104.0 2011-07-22 - 104.0 2001-08-09 3 103.0 2010-07-06 - 103.0 1995-07-15 - 103.0 1948-08-26 Maximum 1-Day Mean Max Temperature for Atlantic City Area, NJ (ThreadEx) Click column heading to sort ascending, click again to sort descending. 1 106.0 2026-07-04 - 106.0 1969-06-28 2 105.0 2026-07-03 - 105.0 2011-07-23 - 105.0 2011-07-22 3 104.0 1966-07-03 4 103.0 2026-07-02 - 103.0 2001-08-09

Then maybe you can help me understand what you mean by the term surrogate since it’s not typically a word that is used when trying to understand the weather and climate.

I usually don’t post seasonal forecast maps for details like temperatures. Looking more at where the seasonal models have some actual skill like the ENSO plumes past the spring predictability barrier. The temperature maps posted were to show that the models haven’t had much skill in that area. Just remember than none of the seasonal models over the last decade have successfully forecast any the record warmth which has been so frequent at times most winter seasons since the 2015-2016 super El Niño. I don’t understand what you mean by surrogates since that implies a situation or process where you can exert some influence on the outcome. Now if I could affect the weather in some way, it would be to restore our colder climate of days past since I didn’t like how much warmer our climate has become.

In a broad sense you can consider these seasonal models guidance, but the guidance is more of a correlation at times than an actual forecast. I showed in earlier posts how the 2023-2024 seasonal forecasts matched the correlations for Nino 3.4 and not the subset of super events over +2.0. About the only thing that the seasonal models have skill at in July are the Nino forecast plumes now that we are past the spring predictability barrier.

You have to remember that biases with these models are often situational on where the strongest ridges set up. The locations of the strongest ridges will vary based on La Niña, El Niño and the intensity of the event. This past winter none of the models forecast the record warmth out West where the ridge got stuck in place. The magnitude of the models missing the cold in the east was significantly smaller than the warmth in the west. About the only time in the last few years that the seasonal models were significantly too warm across the entire CONUS was back in January 2025. It was close to the 30th coldest January for the CONUS which was the coldest single month of the 2020s so far. But that miss was eclipsed by December 2024 being the 4th warmest on record.

Yeah, people have to remember that models can give us signals but the exact amounts and locations are going to vary. Especially when they are modeling convection where mesoscale boundaries and processes are at play. It’s better to think in ranges of possibilities so if you live in a flood prone area you can at least prepare. I can remember growing up when the models wouldn’t even give us any signal at times and some of the events came as a complete surprise.

Just remember that with our last super El Niño which was much weaker than this one, the seasonal forecasts including the ECWMF were significantly too cool for what verified from the long range forecasts. Forecast from August 2023 Verification

The location of the heaviest potential with HFEF max around the region usually shifts from run to run. But the signal is there mesoscale banding producing localized 5”+ amounts. Sometimes the mean chart is closer the actual amounts and other times the max does better. We never really know for sure. So it’s good to post the mean and max together to show the range of possibilities. The WPC and NWS use that as one of the models for their QPF forecasts. We can see a few spots so far are over 3”. But the nature of convection usually means that the models can’t really pinpoint the exact locations. The latest runs have shifted east a bit which is par for the course with convective rainfall forecasts. Excessive Rainfall Discussion NWS Weather Prediction Center College Park MD 423 AM EDT Mon Jul 6 2026 Day 1 Valid 12Z Mon Jul 06 2026 - 12Z Tue Jul 07 2026 ...THERE IS A MODERATE RISK OF EXCESSIVE RAINFALL ACROSS PORTIONS OF COASTAL NEW JERSEY TO SOUTHEAST Massachusetts... ...Mid-Atlantic and Northeast... Waves of low pressure ripple along a latitudinally wavering stationary front causing multiple rounds of training thunderstorms. During this period the front will likely be sprawled from central Ohio to central New Jersey. Two distinct shortwaves moving along this front will help track dual waves of low pressure eastward, each of which will locally enhance ascent (one across western Pennsylvania, the second from New Jersey into southern New England). Broad areas of ascent, instability with PW values exceeding 2" will be aligned near this front to yield a significant risk for heavy rainfall capable of producing flash flooding. The latest guidance mainly focuses the heaviest QPF over southern New England and portions of northern/coastal New jersey. Although the placement widely varies among the hires guidance there continues to be consensus for areal averages of 3 to 6 inches with local maximums of 8+ as reflected by the REFS and HREF PMM. The neighborhood probabilities reach above 40% for coastal New England and Long Island for 3"/24 hr and 15% for 5"/24 hr. Rainfall rates at times reaching 2-3"/hr combined with aligned mean wind/Corfidi vectors which are parallel to the boundary will drive training/backbuilding to support these heavy rainfall amounts. A Moderate Risk cover far northeast New Jersey, Southeast New York and Long Island, southern Connecticut, southern Rhode Island and portions of southeast Massachusetts.

The Euro update from a few minutes ago now has the strongest traditional ONI on record near +3.8 to +3.9. June set new all-time SST records for developing El Niños in all Nino regions except 1+2. https://www.cpc.ncep.noaa.gov/data/indices/ersst5.nino.mth.91-20.ascii All-Time June SST records in bold YR MON NINO1+2 ANOM NINO3 ANOM NINO4 ANOM NINO3.4 ANOM 2026 6 25.94 2.82 28.33 1.71 30.19 1.22 29.17 1.44 2023 6 25.63 2.50 27.88 1.26 29.55 0.58 28.57 0.84 2015 6 25.32 2.19 28.07 1.45 29.88 0.92 28.90 1.18 1997 6 26.12 3.00 28.13 1.51 29.23 0.26 28.82 1.09

The Euro ensemble spread narrowed at a little higher mean on the new July run to what looks like an around +3.8 to +3.9 on traditional ONI ensemble mean peak. July run June run

This is just like the old times when we get a deluge following record heat. The current heavy rain flash flood potential looks like it could be the most significant event here since the last ones in August 2024 and July 2023. Widespread 2-4” and localized pockets over 5”+ where the best training set up. This is also the most juiced that we have seen the SPC HREF since then. This will be the first chance NYC and some other spots see a wetter than average month since way back in May 2025. The heat over the next 10 days will shift to the West with the potential for over a 600 dm ridge. In the past when we have had 103°+ major heatwaves and heavy rains, the maximum temperatures remained the highest of the summer. So hopefully this will turn out to be the highest temperatures which reached 105°-106°of the entire summer. While this doesn’t rule out more 95° to around 100° heat, the patterns in the past haven’t been able to follow up with as much heat in the following extreme heat to very wet.

Things worked out really well here. They set off all the fireworks just before the heavy thunderstorms arrived. Picked up my heaviest downpour of the summer so far with 0.56 in a short time and wind gusts to 45mph. A great show plus some much needed rainfall.