English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

A statistical prediction method, which is based entirely on the optimal combination of persistence, month-to- month trend of initial conditions, and climatology, is developed for the El Nino-Southern Oscillation (ENSO) phenomena. The selection of predictors is by design intended to avoid any pretense of predictive ability based on ''model physics'' and the like, but rather is to specify the optimal ''no-skill'' forecast as a baseline comparison for more sophisticated forecast methods. Multiple least squares regression using the method of leaps and bounds is employed to test a total of 14 possible predictors for the selection of the best predictors, based upon 1950- 94 developmental data. A range of zero to four predictors were chosen in developing 12 separate regression models, developed separately for each initial calendar month. The predictands to be forecast include the Southern Oscillation (pressure) index (SOI) and the Nino 112, Nino 3, Nino 4, and Nino 3.4 SST indices for the equatorial eastern and central Pacific at lead times ranging from zero seasons (0-2 months) through seven seasons (21- 23 months). Though hindcast ability is strongly seasonally dependent, substantial improvement is achieved over simple persistence wherein largest gains occur for two-seven-season (6-23 months) lead times. For example, expected maximum forecast ability for the Nino 3.4 SST region, depending on the initial date, reaches 92%, 85%, 64%, 41%, 36%, 24%, 24%, and 28% of variance for leads of zero to seven seasons. Comparable maxima of persistence only forecasts explain 92%, 77%, 50%, 17%, 6%, 14%, 21%, and 17%, respectively. More sophisticated statistical and dynamic forecasting models are encouraged to utilize this ENSO-CLIPER model in place of persistence when assessing whether they have achieved forecasting skill; to this end, real-time results for this model are made available via a Web site.

An El Niño–Southern Oscillation Climatology and Persistence (CLIPER) Forecasting Scheme