2026-2027 El Nino

[40/70 Benchmark]

It makes perfect sense to me that if the essence of El Nino is anonymously warm water modulating the Hadley Cell via enhanced convective activity, then warming up the water to the west of ENSO is going to reduce it's ability to do so because the MC is going to rob the ENSO region of some of that convection....ie it's a competing force. 

[40/70 Benchmark]

I would like to see the ONI coupled at around 1.7 or lower, and I bet we would see a better winter independent of the Modoki index.

[FPizz]

2 hours ago, GaWx said:

Chris, I’m curious. How is it possible to come up with even approximate geopotential hts for way back in 1877-8?

It is largely a huge guess and mostly filled in using a handful of data.  If it was a science paper for college using that, you'd probably fail. 

[GaWx]

13 minutes ago, FPizz said:

It is largely a huge guess and mostly filled in using a handful of data.  If it was a science paper for college using that, you'd probably fail. 

Thanks. Do you have a link to the source for the map Chris posted?

[A-L-E-K]

time 2 torch

[snowman19]

[snowman19]

This is indicative of a very well coupled (ocean-atmosphere) El Niño and Bjerknes feedback taking control:

[roardog]

55 minutes ago, snowman19 said:

This is indicative of a very well coupled (ocean-atmosphere) El Niño and Bjerknes feedback taking control:
 

Hmm. It's funny how you'll believe model output forecasting several months ahead for this but not for anything else. lol

[snowman19]

Just now, roardog said:

Hmm. It's funny how you'll believe model output forecasting several months ahead for this but not for anything else. lol

Ok Patrick Star lmfaooooo

[roardog]

The strong westerly wind burst is coming now. We'll see if snowman's triple cyclones develop and help to keep producing westerly wind bursts in the coming couple of months.

[snowman19]

@StormchaserChuck1 Here comes the -SOI….

[Stormchaserchuck1]

Well -10 isn't very strong. Those early March readings >+20 were strong. Will be interesting to see how the SOI responds to this Kelvin wave coming up. 

[roardog]

29 minutes ago, Stormchaserchuck1 said:

Well -10 isn't very strong. Those early March readings >+20 were strong. Will be interesting to see how the SOI responds to this Kelvin wave coming up. 

It looks like there’s been lower pressures around Tahiti but it seems we’re missing the high pressure around Darwin which isn’t allowing the SOI to really tank.

[GaWx]

9 hours ago, snowman19 said:

 

 In 2023, the same BoM model also had it getting to +2.4 at the same time (Sept) as per snowman’s post at the bottom of this post. Here was that 4/8/23 run:

 

 But “it” back then was ONI, which like now was then ~0.5 higher than RONI. So, it implicitly was predicting RONI only at +1.9. Thus, the current BoM prog on an apples to apples basis is progging 0.5 warmer than what it had 3 years ago.

 But also keep in mind that the ‘23 BoM turned out to be significantly too warm for the ONI. In Sept, ONI verified to be only +1.64 meaning a large bust of +0.76! RONI was only +1.15. If this BoM run were to bust as badly to the top warm side, the Sept RONI would be at +1.64.

 

 

[MJO812]

2 hours ago, snowman19 said:

@StormchaserChuck1 Here comes the -SOI….
 

Yep El Nino on the way. Strength is yet to be determined.

[GaWx]

13 hours ago, snowman19 said:

 

Being that the current OISST dailies suggest that RONI is likely ~-0.3 to -0.4, it is a very tall order to get the full April averaged RONI to rise all of the way to  +0.6, which is what this BoM run has. We’ll see what the very strong WWB/TC triplets are able to do. The rate of April warming would probably have to be well beyond record highs to get April RONI up to +0.6. The daily RONIs may have to approach +1.5 by April 30th!! I don’t see that being realistic at all.

[snowman19]

[mitchnick]

Cfs2 has really responded to its December forecast over the last week. Top link is from 18z March 30th and bottom link 18z April 6. January likewise if you scroll forward. Precip is a wowzer too both months. Temps a little AN as expected, but in January it won't matter!

https://www.tropicaltidbits.com/analysis/models/?model=cfs-mon&region=us&pkg=z500a&runtime=2026033018&fh=9

https://www.tropicaltidbits.com/analysis/models/?model=cfs-mon&region=us&pkg=z500a&runtime=2026040618&fh=8

[bluewave]

23 hours ago, GaWx said:

Chris, I’m curious. How is it possible to come up with even approximate geopotential hts for way back in 1877-8?

They have done detailed reanalysis from that era. That may be the earliest case of a a El Niño above +2.0 C that we have. Notice the record warmth that winter in the Upper Midwest.

Time Series Summary for Minneapolis-St Paul Area, MN (ThreadEx) Warmest Winters with ONI  above +2.0 C bolded 
Click column heading to sort ascending, click again to sort descending.

1	2023-2024	29.9	0
2	1877-1878	29.0	0
3	1930-1931	26.9	0
4	2001-2002	26.8	0
5	2011-2012	26.3	0
6	1881-1882	26.1	0
7	1997-1998	25.9	0
8	1986-1987	25.8	0
9	2016-2017	24.3	0
10	2015-2016	24.2	0
11	1982-1983	24.0	0
12	1991-1992	23.7	0
13	1943-1944	23.5	0
14	1920-1921	23.2	0
15	1999-2000	23.1	0

https://psl.noaa.gov/data/20thC_Rean/

20th Century Reanalysis and PSL

Four-dimensional historic weather reconstructions, or reanalyses, provide a crucial instrument-based link between long paleoclimate reconstructions and climate model forecasts. But until recently, the earliest reanalyses began with the year 1948, leaving out many important 20th century climate events, such as the 1930’s Dust Bowl. 

To expand the coverage of global gridded reanalyses, the 20th Century Reanalysis Project is an effort led by NOAA's Physical Sciences Laboratory (PSL) and  CIRES at the University of Colorado, supported by the Department of Energy, to produce reanalysis datasets spanning the entire 20th century and much of the 19th century. These reanalyses assimilate only surface observations of synoptic pressure into NOAA's Global Forecast System and prescribe sea surface temperature and sea ice distribution in order to estimate e.g., temperature, pressure, winds, moisture, solar radiation and clouds, from the surface to the top of the atmosphere throughout the 19th and 20th centuries.

20CR uses an ensemble filter data assimilation method which directly estimates the most likely state of the global atmosphere for each three-hour period, and also estimates uncertainty in that analysis. The most recent version of this reanalysis, V3, provides 8-times daily estimates of global tropospheric variability across 75 km grids, spanning 1836 to 2015 (with an experimental extension from 1806 to 1835.) There are three previous versions of the reanalysis: V1, V2, and V2c.

The project has greatly benefited from international cooperation under the Atmospheric Circulation Reconstructions over the Earth (ACRE) initiative, which undertakes and facilitates the recovery of historical instrumental surface terrestrial and marine global weather observations to underpin 4D weather reconstructions spanning the last 200 to 250 years. Additional support has been provided by the Global Climate Observing System and the World Climate Research Programme.

https://journals.ametsoc.org/view/journals/clim/33/11/jcli-d-19-0650.1.xml

How Significant Was the 1877/78 El Niño?

5. Conclusions

The ERSSTv5 analysis clearly shows a strong El Niño during 1877/78. The ranking of El Niño strength will vary depending on the SST dataset, the Niño regions examined, and the climatology that is used. Here, we attempt to quantify how strong it was in the SST record using the monthly 2° × 2° ERSSTv5 (Huang et al. 2017). To compare the strength of El Niño events, the uncertainty of the Niño indices should be taken into account (Huang et al. 2016a). To date, the uncertainty has rarely been considered in comparing the strength of El Niño events. In ERSST, the SST uncertainty consists of parametric and reconstruction uncertainties (Huang et al. 2016b, 2020). For a regionally averaged SST such as Niño indices, the parametric uncertainty dominates over the reconstruction uncertainty. A 1000-member ensemble analysis of ERSSTv5 (Huang et al. 2020) is used to quantify the parametric uncertainty of Niño indices, which depends on the 2–7 selections of 28 parameters. Our initial analysis of the 1000-member ensemble shows that the ensemble averaged Niño-3 over 1877/78 is lower (1.8°C) than the value from ERSSTv5 standard run while the uncertainty is large (2.8°C). In contrast, the uncertainty range in the Niño-3 and Niño-3.4 indices during 1982/83, 1997/98, and 2015/16 is much smaller (0.1°–0.2°C).

The reasons for the small Niño-3 index value and large uncertainty among the ensemble members over 1877/78 has been investigated using factor analysis here among the 28 ERSSTv5 parameters. We find two of the 28 parameters are especially critical in representing El Niño events when observational data are sparse. In particular, the selections of 1-month high-frequency filter and 20% EOT acceptance criterion appear to reduce the Niño indices by 0.6°–0.8°C and increase the uncertainty by approximately 1.1°C. By removing these members within the 1000-member ensemble, a reassessment of the data confirms a strong El Niño during 1877/78 (with averaged Niño-3 value of 2.8°C and reduced uncertainty of 0.5°C). However, with these adjustments, the Niño indices and their uncertainty do not change much during 1982/83, 1997/98, and 2015/16, suggesting that the selections of those two parameters do not exert a large influence on the SST reconstruction across the tropical Pacific in the modern era. The reason for a more stable SST reconstruction in the modern era is due to the better observational coverage after the 1960s (80%) than during the 1870s (10%).

The strong 1877/78 El Niño in ERSSTv5 is consistent with independent SOI index derived from sea level pressure measurements in Darwin and Tahiti (Trenberth 1984). This El Niño event in ERSSTv5 is also consistent with the precipitation and temperature proxy data derived from tree rings and coral reefs and from the great famine record in southeastern Asia and Africa (Kiladis and Diaz 1986; Allan et al. 1991; D’Arrigo et al. 2008; Garden 2008; Hao et al. 2010; Räsänen et al. 2016; Singh et al. 2018; Lough et al. 2018). For example, Singh et al. (2018) used the Palmer drought severity index (PDSI) in Asia and demonstrated a record-breaking El Niño during 1877/78. D’Arrigo et al. (2008) used the PDSI in Australia and Lough et al. (2018) used the degree heating month index (DHMI) derived from coral reef in the tropical oceans; both showed a strong El Niño event during 1877/78.

The strong 1877/78 El Niño in ERSSTv5 is consistent with that in HadSST1 (Fig. 2c; dotted blue) (Rayner et al. 2003). The Niño-3 index is approximately 0.5°C lower in HadISST1 than in ERSSTv5 from January 1877 to February 1878, which is in the range of the uncertainty of ERSSTv5 as indicated in Fig. 5d and Table 1. The temporal correlation between ERSSTv5 and HadISST1 Niño-3 indices between January 1877 and January 1879 is high (approximately 0.94). The consistency between the 1997/98 El Niño events in ERSSTv5 and HadSST1 is very good with strong correlations (0.99) between January 1997 and January 1999 (Fig. 2f).

In conclusion, the strength (2.8°–3.5°C) and uncertainty (0.5°C) of the 1877/78 El Niño event are quantified by evaluating the selection of certain parameters in the ERSSTv5 ensemble. The strength of the 1877/78 El Niño appears approximately equal to those during 1982/83, 1997/98, and 2015/16.

[GaWx]

1 hour ago, bluewave said:

They have done detailed reanalysis from that era. That may be the earliest case of a a El Niño above +2.0 C that we have. Notice the record warmth that winter in the Upper Midwest.

Time Series Summary for Minneapolis-St Paul Area, MN (ThreadEx) Warmest Winters with ONI  above +2.0 C bolded 
Click column heading to sort ascending, click again to sort descending.

1	2023-2024	29.9	0
2	1877-1878	29.0	0
3	1930-1931	26.9	0
4	2001-2002	26.8	0
5	2011-2012	26.3	0
6	1881-1882	26.1	0
7	1997-1998	25.9	0
8	1986-1987	25.8	0
9	2016-2017	24.3	0
10	2015-2016	24.2	0
11	1982-1983	24.0	0
12	1991-1992	23.7	0
13	1943-1944	23.5	0
14	1920-1921	23.2	0
15	1999-2000	23.1	0

https://psl.noaa.gov/data/20thC_Rean/

20th Century Reanalysis and PSL

Four-dimensional historic weather reconstructions, or reanalyses, provide a crucial instrument-based link between long paleoclimate reconstructions and climate model forecasts. But until recently, the earliest reanalyses began with the year 1948, leaving out many important 20th century climate events, such as the 1930’s Dust Bowl. 

To expand the coverage of global gridded reanalyses, the 20th Century Reanalysis Project is an effort led by NOAA's Physical Sciences Laboratory (PSL) and  CIRES at the University of Colorado, supported by the Department of Energy, to produce reanalysis datasets spanning the entire 20th century and much of the 19th century. These reanalyses assimilate only surface observations of synoptic pressure into NOAA's Global Forecast System and prescribe sea surface temperature and sea ice distribution in order to estimate e.g., temperature, pressure, winds, moisture, solar radiation and clouds, from the surface to the top of the atmosphere throughout the 19th and 20th centuries.

20CR uses an ensemble filter data assimilation method which directly estimates the most likely state of the global atmosphere for each three-hour period, and also estimates uncertainty in that analysis. The most recent version of this reanalysis, V3, provides 8-times daily estimates of global tropospheric variability across 75 km grids, spanning 1836 to 2015 (with an experimental extension from 1806 to 1835.) There are three previous versions of the reanalysis: V1, V2, and V2c.

The project has greatly benefited from international cooperation under the Atmospheric Circulation Reconstructions over the Earth (ACRE) initiative, which undertakes and facilitates the recovery of historical instrumental surface terrestrial and marine global weather observations to underpin 4D weather reconstructions spanning the last 200 to 250 years. Additional support has been provided by the Global Climate Observing System and the World Climate Research Programme.

https://journals.ametsoc.org/view/journals/clim/33/11/jcli-d-19-0650.1.xml

 

How Significant Was the 1877/78 El Niño?

 

5. Conclusions

The ERSSTv5 analysis clearly shows a strong El Niño during 1877/78. The ranking of El Niño strength will vary depending on the SST dataset, the Niño regions examined, and the climatology that is used. Here, we attempt to quantify how strong it was in the SST record using the monthly 2° × 2° ERSSTv5 (Huang et al. 2017). To compare the strength of El Niño events, the uncertainty of the Niño indices should be taken into account (Huang et al. 2016a). To date, the uncertainty has rarely been considered in comparing the strength of El Niño events. In ERSST, the SST uncertainty consists of parametric and reconstruction uncertainties (Huang et al. 2016b, 2020). For a regionally averaged SST such as Niño indices, the parametric uncertainty dominates over the reconstruction uncertainty. A 1000-member ensemble analysis of ERSSTv5 (Huang et al. 2020) is used to quantify the parametric uncertainty of Niño indices, which depends on the 2–7 selections of 28 parameters. Our initial analysis of the 1000-member ensemble shows that the ensemble averaged Niño-3 over 1877/78 is lower (1.8°C) than the value from ERSSTv5 standard run while the uncertainty is large (2.8°C). In contrast, the uncertainty range in the Niño-3 and Niño-3.4 indices during 1982/83, 1997/98, and 2015/16 is much smaller (0.1°–0.2°C).

The reasons for the small Niño-3 index value and large uncertainty among the ensemble members over 1877/78 has been investigated using factor analysis here among the 28 ERSSTv5 parameters. We find two of the 28 parameters are especially critical in representing El Niño events when observational data are sparse. In particular, the selections of 1-month high-frequency filter and 20% EOT acceptance criterion appear to reduce the Niño indices by 0.6°–0.8°C and increase the uncertainty by approximately 1.1°C. By removing these members within the 1000-member ensemble, a reassessment of the data confirms a strong El Niño during 1877/78 (with averaged Niño-3 value of 2.8°C and reduced uncertainty of 0.5°C). However, with these adjustments, the Niño indices and their uncertainty do not change much during 1982/83, 1997/98, and 2015/16, suggesting that the selections of those two parameters do not exert a large influence on the SST reconstruction across the tropical Pacific in the modern era. The reason for a more stable SST reconstruction in the modern era is due to the better observational coverage after the 1960s (80%) than during the 1870s (10%).

The strong 1877/78 El Niño in ERSSTv5 is consistent with independent SOI index derived from sea level pressure measurements in Darwin and Tahiti (Trenberth 1984). This El Niño event in ERSSTv5 is also consistent with the precipitation and temperature proxy data derived from tree rings and coral reefs and from the great famine record in southeastern Asia and Africa (Kiladis and Diaz 1986; Allan et al. 1991; D’Arrigo et al. 2008; Garden 2008; Hao et al. 2010; Räsänen et al. 2016; Singh et al. 2018; Lough et al. 2018). For example, Singh et al. (2018) used the Palmer drought severity index (PDSI) in Asia and demonstrated a record-breaking El Niño during 1877/78. D’Arrigo et al. (2008) used the PDSI in Australia and Lough et al. (2018) used the degree heating month index (DHMI) derived from coral reef in the tropical oceans; both showed a strong El Niño event during 1877/78.

The strong 1877/78 El Niño in ERSSTv5 is consistent with that in HadSST1 (Fig. 2c; dotted blue) (Rayner et al. 2003). The Niño-3 index is approximately 0.5°C lower in HadISST1 than in ERSSTv5 from January 1877 to February 1878, which is in the range of the uncertainty of ERSSTv5 as indicated in Fig. 5d and Table 1. The temporal correlation between ERSSTv5 and HadISST1 Niño-3 indices between January 1877 and January 1879 is high (approximately 0.94). The consistency between the 1997/98 El Niño events in ERSSTv5 and HadSST1 is very good with strong correlations (0.99) between January 1997 and January 1999 (Fig. 2f).

In conclusion, the strength (2.8°–3.5°C) and uncertainty (0.5°C) of the 1877/78 El Niño event are quantified by evaluating the selection of certain parameters in the ERSSTv5 ensemble. The strength of the 1877/78 El Niño appears approximately equal to those during 1982/83, 1997/98, and 2015/16.

 I fully get that 1877-8 is as strong as any El Niño on record based on Nino 3.4 as Eric Webb’s and other tables show. But it’s the H5 maps that were shocking to see since I had never seen any H5 maps before the late 1940s. Now after reading what you posted above, I realize this 1877-8 H5 is no more than the equivalent of a wild educated guess as all it is based on is surface data as that’s all the only data they have.