Correspondences
What is linked, what is not
Each arc joins two phenomena tested on this site. Green and animated: clear link (correlation significant at 5 % after correcting for autocorrelation, or a response outside chance in an event study). Grey: inconclusive test. A statistical link alone does not establish causation.
- Clear link
- Inconclusive
Hypotheses tested
28
Clear links
21
Causation demonstrated
0
Arc width from |r| of the stored result; several tests between the same phenomena are drawn as stacked arcs.
Hypothesis tested: During La Niña more rain falls over the continents (Australia, Amazonia, South-East Asia), which store it in soils, aquifers and lakes: sea level falls. During El Niño the water leaves the continents and the sea rises (Boening et al., 2012).
Pearson correlation r (lag 4 month(s))
-0.57
95% interval [-0.71; -0.33] (block bootstrap)
Aligned points
257
effective n ≈ 46 (autocorrelation)
p-value
0.00002
two-sided, Fisher z transform, effective n
r continental water – sea level
-0.57
256 months, lag 0: the two vary as mirror images
Period analysed
2002-04 → 2026-07
computed on Oct 25, 2026 · engine v1.0
Aligned series (standard deviations, after preprocessing)
Show the data as a table
Correlation by lag (month(s))
Show the data as a table
Method and sources
Monthly Niño 3.4 (NOAA PSL); total water storage averaged over land except the ice sheets (GRACE and GRACE-FO, COST-G solution of GFZ GravIS), in cm of water. Both series are deseasonalised (mean of each month removed) and linearly detrended. Lags of −6 to +12 months are paired on the calendar, since GRACE has missing months. The expected sign is negative (El Niño dries the continents): the most negative lag is kept. Effective size after Bretherton et al., 12-month block bootstrap. Mirror test: continental water against the altimetric mean sea level (University of Colorado), same preprocessing, zero lag.
Computation parameters
{
"x": "Niño 3.4 monthly (NOAA PSL)",
"y": "land water storage, GravIS COST-G, all land except Antarctica and Greenland (cm)",
"mirror": "land water storage against CU altimetric mean sea level, lag 0",
"bootstrap": {
"seed": 20261023,
"block": 12,
"draws": 1000
},
"lag_choice": "most negative r (sign expected a priori)",
"lags_months": [
-6,
12
],
"preprocessing": "monthly climatology removed, linear trend removed"
}Inputs : psl.nino34.anom.monthly (945 pts, run #42) · gravis.tws.land.monthly (259 pts, run #3712) · cu.gmsl.10day (1,203 pts, run #3693)
Reading this result
The two correlations, closed in a loop (ENSO → continental water, continental water → sea level), tell one phenomenon: a transfer of water between ocean and continents, worth a few millimetres of sea level, on top of the underlying rise (ice melt, expansion). The 2010–2011 La Niña thus lowered the sea by about 5 mm in a year. The lag of about four months reflects the time taken to fill soils and aquifers. The mean over all land mixes regions that respond in opposite directions. Correlation is not causation: common factors (seasons, cycles, trends) or coincidence can produce it. The p-values account for autocorrelation (effective n) but not for preprocessing choices; the confidence interval comes from a block bootstrap. The limits of the source data apply.
SOURCES OF THIS PAGE
- Niño 3.4 SST anomaly (NOAA PSL, ERSSTv5)
-
NOAA PSL, Niño 3.4 index: monthly SST anomaly (5°N–5°S, 170°–120°W) from ERSSTv5, climatology 1991–2020.
· source page ↗
Licence : U.S. Government work, public domain · retrieved on Oct 23, 2026 · SHA-256 879cf3cb31d7… - GravIS mass anomalies from GRACE and GRACE-FO: ice sheets and river-basin water storage (GFZ, COST-G)
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Sasgen, I., Döhne, T., Boergens, E., Horwath, M. (2026): COST-G GravIS RL02 Ice-Mass Change Products, V. 0001, GFZ Data Services, doi:10.5880/COST-G.GRAVIS_02_L3_ICE. Boergens, E., Dobslaw, H., Dill, R. (2025): COST-G GravIS RL02 Terrestrial Water Storage Anomalies, V. 0001, GFZ Data Services, doi:10.5880/COST-G.GRAVIS_02_L3_TWS. Dahle, C., et al. (2025): GravIS: mass anomaly products from satellite gravimetry, Earth Syst. Sci. Data, 17, 611–631.
· doi:10.5194/essd-17-611-2025 · source page ↗
Licence : CC BY 4.0 (GFZ Data Services); cite the data DOIs and Dahle et al. (2025) · retrieved on Oct 25, 2026 · SHA-256 59c02eaae985… - Global mean sea level by satellite altimetry (University of Colorado Sea Level Research Group)
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University of Colorado Sea Level Research Group, global mean sea level release 2026_rel2 (TOPEX/Poseidon, Jason-1/2/3, Sentinel-6MF), seasonal signals removed, glacial isostatic adjustment applied; Nerem, R. S., et al. (2010), Marine Geodesy 33, 435; Nerem, R. S., et al. (2018), PNAS 115, 2022–2025.
· doi:10.1073/pnas.1717312115 · source page ↗
Licence : Freely available for research and education; cite the CU Sea Level Research Group and Nerem et al. (2010, 2018) · retrieved on Oct 25, 2026 · SHA-256 eef45eb6580a… - Boening et al. (2012)
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Boening, C., Willis, J. K., Landerer, F. W., Nerem, R. S., & Fasullo, J. (2012). The 2011 La Niña: so strong, the oceans fell. Geophysical Research Letters, 39, L19602.
· doi:10.1029/2012GL053055
Licence : Published literature; cited - Dahle et al. (2025)
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Dahle, C., Boergens, E., Sasgen, I., Döhne, T., Reißland, S., et al. (2025). GravIS: mass anomaly products from satellite gravimetry. Earth System Science Data, 17, 611–631.
· doi:10.5194/essd-17-611-2025
Licence : Published literature; cited