Open AccessPrincipal components of sea surface temperatures as predictors of seasonal rainfall in rainfed wheat growing areas of P akistan
Author(s) -
van Ogtrop Floris,
Ahmad Mukhtar,
Moeller Carina
Publication year - 2014
Publication title -
meteorological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 59
eISSN - 1469-8080
pISSN - 1350-4827
DOI - 10.1002/met.1429
Subject(s) - climatology , sea surface temperature , environmental science , monsoon , el niño southern oscillation , geography , varimax rotation , mathematics , statistics , geology , cronbach's alpha , descriptive statistics
Time‐lagged relationships were explored between VARIMAX rotated principal components ( RCs ) of sea surface temperatures ( SSTs ) and rainfall periods that are important for rainfed wheat production in P akistan. Seasonal forecasts were developed using G eneralized A dditive M odels. The first 10 RCs explained 54% of the variance in the SST data. Individual RCs were strongly ( r 2 ≥ |0.5|) to moderately ( r 2 ≥ |0.3|) correlated with climatic indices of SST anomalies associated with the E l‐Niño S outhern O scillation, P acific D ecadal O scillation, I ndian O cean D ipole, and the tropical A tlantic O cean. Forecasts of monsoon ( J uly to S eptember), total growing season ( N ovember to A pril), early ( N ovember to J anuary) and late season ( F ebruary to A pril) rainfall (1961–2010) were developed for C hakwal, T alagang and I slamabad. Important, linear or non‐linear, time‐lagged relationships were found between the RCs of SSTs and rainfall. Cross‐validated forecasts were compared with real‐time forecasts to evaluate the ‘true’ forecasting ability of the models. Continuous and categorical probabilistic forecasts were tested with an array of skill scores. Skilful forecasts of pre‐season, monsoon and late‐season rainfall were produced for the drier sites C hakwal and T alagang and to a lesser extent for the wetter site I slamabad. These simple, statistical forecasts can be developed with minimal financial investment. However, consideration of the potential uses of such forecasts will require a reflective decision framework that engages stakeholders and addresses socio‐economic and agro‐ecological constraints not included here.