Showing papers by "Rob Allan published in 2000"

ENSO and climatic signals across the Indian Ocean Basin in the global context: part I, interannual composite patterns

Abstract: This study focuses on the interplay between mean sea level pressure (MSLP), sea surface temperature (SST), and wind and cloudiness anomalies over the Indian Ocean in seasonal composite sequences prior to, during, and after strong, near-global El Nino and La Nina episodes. It then examines MSLP and SST anomalies in the 2–2.5-year quasi-biennial (QB) and 2.5–7-year low-frequency (LF) bands that carry the bulk of the raw ENSO signal. Finally, these fields were examined in conjunction with patterns of correlations between rainfall and joint spatiotemporal empirical orthogonal function (EOF) time series band pass filtered in the QB and LF bands. The seasonal composites indicate that the El Nino-1 (La Nina-1) pattern tends to display a more robust and coherent (weaker and less organized) structure during the evolution towards the mature stage of the event. The reverse tends to be apparent in the cessation period after the peak phase of an event, when El Nino events tend to collapse quite quickly. Climatic variables over the Indian Ocean Basin linked to El Nino and La Nina events show responses varying from simultaneous, to about one season's lag. In general, SSTs tend to evolve in response to changes in cloud cover and wind strength over both the north and south Indian Ocean. There are also strong indications that the ascending (descending) branch of the Walker circulation is found over the African continent (central Indian Ocean) during La Nina phases, and that the opposite configuration occurs in El Nino events. These alternations are linked to distinct warm–cool (cool–warm) patterns in the north–south SST dipole over the western Indian Ocean region during the El Nino (La Nina) events. An examination of MSLP and SST anomaly patterns in the QB and LF bands shows that signals are more consistent during El Nino-1 and El Nino sequences than they are during La Nina-1 and La Nina sequences. The QB band has a tendency to display the opposite anomaly patterns to that seen on the LF band during the early stages of event onset, and later stage of event cessation, during both El Nino–Southern Oscillation (ENSO) phases. El Nino events tend to be reinforced by signals on both bands up to their mature phase, but are then seen to erode rapidly, as a result of the presence of distinct La Nina anomalies on the QB band after their peak phase. During La Nina events, the opposite is observed during their cessation phase. Both QB and LF bands often display SST dipole anomalies that are not clearly evident in the raw composites alone. An eastern Indian Ocean SST dipole shows a tendency to occur during the onset phase of particular El Nino or La Nina episodes, especially during the austral autumn–winter (boreal spring–summer) and, when linked to tropical-temperate cloud bands, can influence Australian rainfall patterns. Analyses of seasonal correlations between rainfall and joint MSLP and SST EOF time series on QB and LF bands and their dynamical relationship with MSLP and SST anomalies during El Nino and La Nina events, show that the interplay between atmospheric circulation and SST anomalies dictates the observed rainfall response. Instances where either, or both, QB and LF bands are the prime influence on observed rainfall regimes are evident. This ability to discriminate the finer structure of physical relationships, correlations and patterns provides a deeper insight into Indian Ocean responses to ENSO phases. Copyright © 2000 Royal Meteorological Society

The Potential for Improved Statistical Seasonal Climate Forecasts

Abstract: From its beginning, statistical climate prediction has been hampered by poor observational data coverage, both spatially and temporally; incomplete theoretical understanding of the climate system; availability of only basic statistical techniques and limited computational capabilities. Progress in recent years, and the potential for further improvement in the future is the result of improvements in all these areas. Obviously these topics are all connected, and improvement in one area leads to, or requires, improvement in the others. This paper examines these issues as a basis to discuss potential to improve statistical seasonal climate forecasts.