bluewave

Mostly climatology in that region. You can also look at all of the seasonal SST forecast models which show a rebound during the winter there. This year we don’t have as strong an Indian Ocean forcing signal as 2019 so not getting the same signal for the super strong SPV like that winter. But there are many things which can affect the SPV so there is always a bit of wait and see.

I expanded the box a bit more since the forcing is sensitive to a larger area than the one you posted. The current cooling is a result of the IOD like we saw at the same time in 2019. But once this IOD fades, the SSTs will naturally rebound like we saw by the winter of 2020. These stronger +IODs are a relatively short lived events only lasting several months.

The odd thing about this event is that the timing of El Niño global temperature spikes are usually in the late winter or spring. We never had a global temperature spike of this magnitude from the summer into the fall while an El Niño event was developing. The 15-16 peak came in late February as we would expect from the El Niño lag and usual timing of the monthly peak. Plus this event is only around +1.5C rather than the super levels in 15-16 of a record +2.6. The one theory as to timing that I heard was that Nino 1+2 got an unusually early start late last winter. And that global temperatures are very sensitive to the EPAC region.

It’s normal for the WPAC SSTs to decline a bit during El Niño periods. But this September was the warmest for an El Niño in September from the Dateline back to Asia. We can remember the record SST rebound following the 2019 fall IOD event.

Don, it will be interesting to see if the record is a result of a slight undermeasurement at the park taken too late allowing time to melt or settle. Notice the other surrounding airport sites with more frequent measurements made it to an inch on 2-27-23. Data for February 27, 2023 through February 27, 2023 Click column heading to sort ascending, click again to sort descending. State Name Station Type Total Snowfall NJ CEDAR GROVE TWP 0.4 W CoCoRaHS 2.8 NY RIDGE 1.8 SE CoCoRaHS 2.4 CT IGOR I SIKORSKY MEMORIAL AIRPORT WBAN 2.0 NY ISLIP-LI MACARTHUR AP WBAN 1.8 NJ NEWARK LIBERTY INTL AP WBAN 1.2 NY LAGUARDIA AIRPORT WBAN 1.1 NY JFK INTERNATIONAL AIRPORT WBAN 1.0 NY NY CITY CENTRAL PARK WBAN 0.9

You are talking about two different different things. Global warming is something that has been observed and seasonal forecasts involve projections about the future. You will notice in most good studies about global warming they mention that they are not sure how things will change in the future in regard to regional climate trends. Regional climate modeling is a new frontier that is still pretty young. The global climate models are a more generalized and have been doing a good job with broader global temperature trends even though this current temperature spike is outside the upper limit. It’s highly reasonable to expect when we change a climate state so rapidly there will be model differences as to the finer details. So nobody is shutting down any debates.

West Point getting close to a top 10 wettest year. Time Series Summary for WEST POINT, NY - Jan through Dec Click column heading to sort ascending, click again to sort descending. Rank Year Total Precipitation Missing Count 1 2011 80.37 0 2 1996 71.39 1 3 1983 69.49 0 4 2018 69.16 1 5 2005 67.72 1 6 2003 65.60 0 7 1952 65.01 0 8 1979 62.26 2 9 1972 59.74 0 10 1975 58.85 0 11 2010 58.04 0 12 1990 57.81 1 13 1994 56.93 0 14 2023 56.70 99

NYC is on track for another 50”+ year with numerous sites around the area already over 50”. Data for January 1, 2023 through October 6, 2023 Click column heading to sort ascending, click again to sort descending. State Name Station Type Total Precipitation CT SEYMOUR 1.2 WSW CoCoRaHS 57.56 NY WEST POINT COOP 56.70 CT ANSONIA 1 NE COOP 53.38 CT PROSPECT 1.9 ENE CoCoRaHS 53.11 NY PEEKSKILL 0.4 N CoCoRaHS 52.92 NY STONY POINT 0.7 NW CoCoRaHS 52.56 CT NORWICH 2.5 NNE CoCoRaHS 52.48 NY THORNWOOD 0.7 NW CoCoRaHS 51.99 CT NORTHFORD 0.8 SW CoCoRaHS 51.99 CT EAST LYME 0.5 SW CoCoRaHS 51.82 CT WATERBURY 1.3 WNW CoCoRaHS 51.72 NY NEW HEMPSTEAD 0.6 SE CoCoRaHS 51.51 CT BROOKFIELD 3.3 SSE CoCoRaHS 50.76 CT GRISWOLD 0.9 N CoCoRaHS 50.61 NY SHRUB OAK COOP 50.59 NY BEACON 4.2 ESE CoCoRaHS 50.37 CT MIDDLEFIELD 0.6 SE CoCoRaHS 50.14 CT PROSPECT 0.5 SW CoCoRaHS 50.00 CT NAUGATUCK 1.7 NNE CoCoRaHS 49.50 NY CARMEL 4N COOP 49.46 CT MERIDEN 2.8 WSW CoCoRaHS 49.39 NY SOUTH SALEM 2.1 NW CoCoRaHS 49.26 CT BETHANY 1.3 SW CoCoRaHS 49.26 NY PORT JERVIS 2.9 ESE CoCoRaHS 49.22 NY SOUTH SALEM 0.8 N CoCoRaHS 49.10 CT COLCHESTER 0.6 ENE CoCoRaHS 48.99 CT NEWTOWN 4.6 SE CoCoRaHS 48.98 CT HIGGANUM 0.8 NE CoCoRaHS 48.68 CT DURHAM 1.2 W CoCoRaHS 48.64 CT WALLINGFORD CENTER 1.9 WNW CoCoRaHS 48.62 CT RIDGEFIELD 2.4 NNE CoCoRaHS 48.35 CT NEW CANAAN 1.9 ENE CoCoRaHS 48.17 NY BROOKLYN 3.1 NW CoCoRaHS 48.10 NY ELMSFORD 0.8 SSW CoCoRaHS 48.09 NY ARMONK 0.3 SE CoCoRaHS 48.05 CT OAKDALE 2.6 WNW CoCoRaHS 47.88 NJ RINGWOOD 3.0 SSE CoCoRaHS 47.73 CT HIGGANUM 0.7 N CoCoRaHS 47.50 NY PINE BUSH 3.4 WSW CoCoRaHS 47.34 NJ WAYNE TWP 2.3 ESE CoCoRaHS 47.31 CT SOUTHBURY 2.3 W CoCoRaHS 47.25 NY LITTLE NECK 0.3 SE CoCoRaHS 47.15 CT JEWETT CITY 3.0 ESE CoCoRaHS 47.10 CT WALLINGFORD CENTER 3.3 NNW CoCoRaHS 46.92 CT SHELTON 1.3 W CoCoRaHS 46.62 CT NORWALK 1.4 ENE CoCoRaHS 46.48 CT OLD LYME 3.4 ESE CoCoRaHS 46.42 CT BETHEL 0.5 E CoCoRaHS 46.33 CT RIDGEFIELD 3.6 N CoCoRaHS 46.13 NJ GLEN ROCK 0.7 SSE CoCoRaHS 46.12 NY LAGUARDIA AIRPORT WBAN 46.00 CT OXFORD WATERBURY WBAN 45.98 CT MONROE 0.8 W CoCoRaHS 45.98 CT NEW CANAAN 3.8 N CoCoRaHS 45.97 CT NORWALK 2.9 NNW CoCoRaHS 45.90 CT SALEM 3.6 SE CoCoRaHS 45.78 NY NY CITY CENTRAL PARK WBAN 45.73

https://iopscience.iop.org/article/10.1088/1748-9326/ac5edf/meta The Indo-Pacific warm pool (IPWP) has warmed and expanded substantially over the past decades, which has significantly affected the hydrological cycle and global climate system. It is unclear how the IPWP will change in the future under anthropogenic (ANT) forcing. Here, we quantify the human contribution to the observed IPWP warming/expansion and adjust the projected IPWP changes using an optimal fingerprinting method based on Coupled Model Intercomparison Project phase 6 (CMIP6) simulations. We find that more than 95% rapid warming and 85% expansion of the observed IPWP are detected and attributable to human influence. Furthermore, human activities affect IPWP warming through both greenhouse gases and ANT aerosols. The multiple model ensemble mean can capture the ANT warming trend and tends to underestimate the ANT warming trend. After using the observation constraint, the IPWP warming is projected to increase faster than that of the ensemble mean in the 21st Century, and the Indian Ocean warm pool is projected to expand more than previously expected. The rapid warming and expansion of IPWP over the rest of the 21st century will impact the climate system and the life of human beings.

The best October correlation that I have found since 2010 only works during La Ninas. The stronger MJO 4-6 Octobers during La Ninas had better seasonal snowfall around NYC. It’s a shorter period than we like to use for correlations but I got lucky using it during the the fall of 2020 in one of the old threads.

I wonder what it would be like to run a global system like that out to 360 hrs as an ensemble mean. I have read they want to upgrade the ECMWF EPS to 4-5 km closer to convection allowing resolution.

Interesting…thanks for posting. https://gsl.noaa.gov/focus-areas/unified_forecast_system/rrfs Within the NOAA model unification effort, the RRFS represents the evolution of the NAM, RAP, HRRR, and HREF systems to a new unified deterministic and ensemble storm-scale system. This new system is targeted for initial operational implementation in late 2024 as a planned replacement for the NAMnest, HRRR, HiResWindows, and HREF. While the standalone regional (SAR) FV3 model is being developed for convection-allowing forecasting of a limited area (CONUS), other possible components of the RRFS are being tested now in the experimental, WRF-based High-Resolution Rapid Refresh Ensemble (HRRRE). Experimental runs of the HRRRE at GSL are focused particularly on: Improving 0-12 h high-resolution forecasts through ensemble-based, multi-scale data assimilation Producing spread in 0-36 h ensemble forecasts through initial-condition perturbations, boundary-condition perturbations, and stochastic physics.

It’s a bit of an October reversal like we see with the MJO 4-6 being colder in October than the winter.

The big MEI mismatch continues with AS only coming in at +0.6. Doesn’t match any of the other AS cases with Nino 3.4 in the borderline moderate to strong range. https://psl.noaa.gov/enso/mei/

The real test will come during the winter since a stronger Aleutian low in October is more Niña-like than Nino-like. It’s one of those interesting monthly correlation shifts that we see from time to time. It’s one of the few times of the year when a La Niña or -PDO produce a trough near the Southeast.

We probably have to take the warmer trend more seriously than we usually do with these seasonal forecasts since it matches the winter pattern of warmer East and colder West since the super El Niño in 15-16.

The weaker Aleutian low has become a common theme with the persistent La Niña background state following the WPAC warm pool expansion. https://www.eurekalert.org/news-releases/1002264 Wang and co-authors examined 20 La Niña events from 1920-2022 to investigate the fundamental reasons behind the historic change of the multiyear La Niña. Some long-lasting La Niñas occurred after a super El Niño, which the researchers expected due to the massive discharge of heat from the upper-ocean following an El Niño. However, three recent multiyear La Niña episodes (2007–08, 2010–11, and 2020–22) did not follow this pattern. They discovered these events are fueled by warming in the western Pacific Ocean and steep gradients in sea surface temperature from the western to central Pacific. “Warming in the western Pacific triggers the rapid onset and persistence of these events,” said Wang. “Additionally, our study revealed that multiyear La Niña are distinguished from single-year La Niña by a conspicuous onset rate, which foretells its accumulative intensity and climate impacts.” Results from complex computer simulations of climate support the observed link between multiyear La Niña events and western Pacific warming. The new findings shed light on the factors conducive to escalating extreme La Niña in a future warming world. More multiyear La Niña events will exacerbate adverse impacts on communities around the globe, if the western Pacific continues to warm relative to the central Pacific. “Our perception moves beyond the current notion that links extreme El Niño and La Niña to the eastern Pacific warming and attributes the increasing extreme El Niño and La Niña to different sources,” Wang added. “The knowledge gained from our study offers emergent constraints to reduce the uncertainties in projecting future changes of extreme La Niña, which may help us better prepare for what lies ahead.”

The new DJF 500 mb pattern is a blend of El Niño and -PDO composites with the trough pulled further west from the earlier forecasts. So a colder West and warmer East trend from earlier runs. New run blended El Niño -PDO 500 mb composite Old run was more of an El Niño dominant composite

This month will be a good test of the El Niño vs -PDO influence. The key region in October is the EPO. The PNA becomes more correlated in the winter. El Niño Octobers typically have a -EPO pattern. -PDO in October is +EPO. So we can already see the back and forth between -EPO and +EPO in the model forecasts for the month.

Euro seasonal update is trending colder in the West and warmer East as it has a more well defined -PDO pattern for the winter. The main feature of the -PDO is the warm pool and ridge south of the Aleutians. While the Euro doesn’t have great seasonal skill, sometimes it’s trends from run to run provide some skill. New run Old run

We’ll see if the SPC HREF picks up on it once we are within range.

Too much SE flow today here so the most impressive records going north.

Almost Looks like a PRE or inverted trough associated with Phillipe as he interacts with the trough. We’ll probably have to wait until this gets within the range of the CAMS to see if this feature is real.

Record heat today on Long Island. We haven’t had an October record low on Long Island since 2003. Good early signal for the record cold that followed in January 2004. Reynolds Channel between Long Beach and Island Park was nearly frozen all the way across near the bridge.

Another outstanding job by this model with the September average extent finishing at 4.37 million sq km. This is nearly identical to the forecast of 4.46 million sq km issued back in June based on May melt pond data.