ENSO Forecasts near the Spring Predictability Barrier and Possible Reasons for the Recently Reduced Predictability

ENSO Forecasts near the Spring Predictability Barrier and Possible Reasons for the Recently... AbstractA cross-validated statistical model has been developed to produce hindcasts for the 1980–2016 November–December–January (NDJ; assumed El Niño peak) mean Niño-3.4 sea surface temperature anomalies (SSTA). A linear combination of two parameters is sufficient to successfully predict the peak SSTA: 1) the 5°N–5°S, 130°E–180°, 5–250-m oceanic potential temperature anomalies in February and 2) the 5°N–5°S, 140°E–160°W cumulative zonal wind anomalies (ZWA), integrated from November (one year before) up to the prediction month. This model is simple but is comparable to, or even outperforms, many NOAA Climate Prediction Center’s statistical models during the boreal spring predictability barrier. In contrast to most statistical models, the predictand Niño-3.4 SSTA is not used as a predictor. The explained variance between observed and predicted NDJ Niño-3.4 SSTA at a lead time of 8 months is 57% using 5 yr for cross validation and 63% in full hindcast mode.Predictive skill is lower after 2000 when the mean climate state is more La Niña–like because of stronger equatorial easterly ZWA. Strengthened Pacific subtropical highs are observed, with weaker westerly ZWA that emerge at a later time during El Niño. The western Pacific is more recharged, with stronger upwelling over the eastern Pacific. The resulting strong zonal subsurface temperature gradient provides a high potential for Kelvin waves being triggered without strong westerly ZWA. However, the persistent easterly ZWA lead to more central Pacific–like El Niños. These are more difficult to predict because the contribution of the thermocline feedback is reduced. Overall, the authors find that the importance of the recharge state for ENSO prediction has increased after 2000, contradicting some previous studies. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Climate American Meteorological Society

ENSO Forecasts near the Spring Predictability Barrier and Possible Reasons for the Recently Reduced Predictability

Loading next page...
 
/lp/ams/enso-forecasts-near-the-spring-predictability-barrier-and-possible-tn9SKlUTCD
Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0442
D.O.I.
10.1175/JCLI-D-17-0180.1
Publisher site
See Article on Publisher Site

Abstract

AbstractA cross-validated statistical model has been developed to produce hindcasts for the 1980–2016 November–December–January (NDJ; assumed El Niño peak) mean Niño-3.4 sea surface temperature anomalies (SSTA). A linear combination of two parameters is sufficient to successfully predict the peak SSTA: 1) the 5°N–5°S, 130°E–180°, 5–250-m oceanic potential temperature anomalies in February and 2) the 5°N–5°S, 140°E–160°W cumulative zonal wind anomalies (ZWA), integrated from November (one year before) up to the prediction month. This model is simple but is comparable to, or even outperforms, many NOAA Climate Prediction Center’s statistical models during the boreal spring predictability barrier. In contrast to most statistical models, the predictand Niño-3.4 SSTA is not used as a predictor. The explained variance between observed and predicted NDJ Niño-3.4 SSTA at a lead time of 8 months is 57% using 5 yr for cross validation and 63% in full hindcast mode.Predictive skill is lower after 2000 when the mean climate state is more La Niña–like because of stronger equatorial easterly ZWA. Strengthened Pacific subtropical highs are observed, with weaker westerly ZWA that emerge at a later time during El Niño. The western Pacific is more recharged, with stronger upwelling over the eastern Pacific. The resulting strong zonal subsurface temperature gradient provides a high potential for Kelvin waves being triggered without strong westerly ZWA. However, the persistent easterly ZWA lead to more central Pacific–like El Niños. These are more difficult to predict because the contribution of the thermocline feedback is reduced. Overall, the authors find that the importance of the recharge state for ENSO prediction has increased after 2000, contradicting some previous studies.

Journal

Journal of ClimateAmerican Meteorological Society

Published: Jan 20, 2018

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off