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El Niño-Southern Oscillation (ENSO) events are associated with particular seasonal weather anomalies in many regions around the planet. When the statistical links are sufficiently strong, ENSO state information can provide useful seasonal forecasts with varying lead times. However, using conventional sea surface temperature or sea level pressure indices to characterize ENSO state leads to many instances of limited forecast skill (e.g., years identified as El Niño or La Niña with weather anomalies unlike the average), even in regions where there is considerable ENSO-associated anomaly, on average. Using outgoing longwave radiation (OLR) conditions to characterize ENSO state identifies a subset of the conventional ENSO years, called OLR El Niño and OLR La Niña years herein. Treating the OLR-identified subset of years differently can both usefully strengthen the level of statistical significance in the average (composite) and also greatly reduce the year-to-year deviations in the composite precipitation anomalies. On average, over most of the planet, the non-OLR El Niño and non-OLR La Niña years have much more limited statistical utility for precipitation. The OLR El Niño and OLR La Niña indices typically identify years in time to be of use to boreal wintertime and later seasonal forecasting efforts, meaning that paying attention to tropical Pacific OLR conditions may offer more than just a diagnostic tool. Understanding better how large-scale environmental conditions during ENSO events determine OLR behavior (and deep atmospheric convection) will lead to improved seasonal precipitation forecasts for many areas. [ABSTRACT FROM AUTHOR]

El Niño-Southern Oscillation (ENSO) events are associated with particular seasonal weather anomalies in many regions around the planet. When the statistical links are sufficiently strong, ENSO state information can provide useful seasonal forecasts with varying lead times. However, using conventional sea surface temperature or sea level pressure indices to characterize ENSO state leads to many instances of limited forecast skill (e.g., years identified as El Niño or La Niña with weather anomalies unlike the average), even in regions where there is considerable ENSO-associated anomaly, on average. Using outgoing longwave radiation (OLR) conditions to characterize ENSO state identifies a subset of the conventional ENSO years, called OLR El Niño and OLR La Niña years herein. Treating the OLR-identified subset of years differently can both usefully strengthen the level of statistical significance in the average (composite) and also greatly reduce the year-to-year deviations in the composite precipitation anomalies. On average, over most of the planet, the non-OLR El Niño and non-OLR La Niña years have much more limited statistical utility for precipitation. The OLR El Niño and OLR La Niña indices typically identify years in time to be of use to boreal wintertime and later seasonal forecasting efforts, meaning that paying attention to tropical Pacific OLR conditions may offer more than just a diagnostic tool. Understanding better how large-scale environmental conditions during ENSO events determine OLR behavior (and deep atmospheric convection) will lead to improved seasonal precipitation forecasts for many areas. [ABSTRACT FROM AUTHOR]

It is shown that space–time smoothed outgoing longwave radiation (OLR) indices of equatorial Pacific seasonal variability can give an interestingly different perspective on El Niño than is obtained from sea surface temperature (SST) indices or the Southern Oscillation index (SOI). In particular, the index defined by averaging over an eastern-central region exhibits strong event like character—more so than in any other El Niño–Southern Oscillation (ENSO) warm-phase index known to the authors. Although the historical record for OLR is much shorter than for SST or SOI, OLR offers a direct connection to anomalous atmospheric heating. It is suggested that the years identified as events by this OLR index deserve particular recognition; and it is noteworthy that they all meet the criteria for “El Niño” years. Other years, whose warm-ENSO status differs depending upon the index favored, are not particularly distinctive from an OLR perspective, and a case could be made that either the other years do not deserve special classification or that they should be identified as different from the OLR-distinguished El Niño years. [ABSTRACT FROM AUTHOR]

It is shown that space–time smoothed outgoing longwave radiation (OLR) indices of equatorial Pacific seasonal variability can give an interestingly different perspective on El Niño than is obtained from sea surface temperature (SST) indices or the Southern Oscillation index (SOI). In particular, the index defined by averaging over an eastern-central region exhibits strong event like character—more so than in any other El Niño–Southern Oscillation (ENSO) warm-phase index known to the authors. Although the historical record for OLR is much shorter than for SST or SOI, OLR offers a direct connection to anomalous atmospheric heating. It is suggested that the years identified as events by this OLR index deserve particular recognition; and it is noteworthy that they all meet the criteria for “El Niño” years. Other years, whose warm-ENSO status differs depending upon the index favored, are not particularly distinctive from an OLR perspective, and a case could be made that either the other years do not deserve special classification or that they should be identified as different from the OLR-distinguished El Niño years. [ABSTRACT FROM AUTHOR]

The investigation of the consequences of trying to blend tropical Pacific observations from the Tropical Atmosphere-Ocean (TAO) array into the dynamical framework of an intermediate coupled ocean-tmosphere model is continued. In a previous study it was found that the model dynamics, the prior estimates of uncertainty in the observations, and the estimates of the errors in the dynamical equations of the model could not be reconciled with data from the 1994-95 period. The error estimates and the data forced the rejection of the model physics as being unacceptably in error. In this work, data from two periods (1995-96 and 1997-98) were used when the tropical Pacific was in states very different from the previous study. The consequences of increasing the prior error estimates were explored in an effort to find out if it is possible at least to use the intermediate model physics to assist in mapping the observations into fields in a statistically consistent way. It was found that such a result is possible for the new data periods, with larger prior error assumptions. However, examination of the behavior of the mapped fields indicates that they have no dynamical utility. The model dynamical residuals, that is, the size of the quantity that is left after evaluating all of the terms in each intermediate model equation, dominate the terms themselves. Evidently the intermediate model is not able to add insight into the processes that caused the tropical Pacific to behave as it was observed to, during these time intervals. The inverse techniques described here together with the relatively dense TAO dataset have made it possible for the unambiguous rejection of the nonlinear intermediate model dynamical system. This is the first time that data have been able to provide such a clear-cut appraisal of simplified dynamics. [ABSTRACT FROM AUTHOR]