Teleconnections between Ethiopian summer rainfall and sea surface temperature: part II. Seasonal forecasting

A seasonal forecasting system that is capable of skilfully predicting rainfall totals on a regional scale would be of great value to Ethiopia. Here, we describe how a statistical model can exploit the teleconnections described in part 1 of this pair of papers to develop such a system. We show that, in most cases, the predictors selected objectively by the statistical model can be interpreted in the light of physical teleconnections with Ethiopian rainfall, and discuss why, in some cases, unexpected regions are chosen as predictors. We show that the forecast has skill in all parts of Ethiopia, and argue that this method could provide the basis of an operational seasonal forecasting system for Ethiopia.

Toward an integrated seasonal forecasting system for South America

This study proposes an objective integrated seasonal forecasting system for producing well-calibrated probabilistic rainfall forecasts for South America. The proposed system has two components: ( i) an empirical model that uses Pacific and Atlantic sea surface temperature anomalies as predictors for rainfall and ( ii) a multimodel system composed of three European coupled ocean - atmosphere models. Three-month lead austral summer rainfall predictions produced by the components of the system are integrated ( i. e., combined and calibrated) using a Bayesian forecast assimilation procedure. The skill of empirical, coupled multimodel, and integrated forecasts obtained with forecast assimilation is assessed and compared. The simple coupled multimodel ensemble has a comparable level of skill to that obtained using a simplified empirical approach. As for most regions of the globe, seasonal forecast skill for South America is low. However, when empirical and coupled multimodel predictions are combined and calibrated using forecast assimilation, more skillful integrated forecasts are obtained than with either empirical or coupled multimodel predictions alone. Both the reliability and resolution of the forecasts have been improved by forecast assimilation in several regions of South America. The Tropics and the area of southern Brazil, Uruguay, Paraguay, and northern Argentina have been found to be the two most predictable regions of South America during the austral summer. Skillful rainfall forecasts are generally only possible during El Nino or La Nina years rather than in neutral years.

Predictability and skill of boreal winter forecasts made with the ECMWF Seasonal Forecasting System II

The performance of boreal winter forecasts made with the European Centre for Medium-Range Weather Forecasts (ECMWF) System 11 Seasonal Forecasting System is investigated through analyses of ensemble hindcasts for the period 1987-2001. The predictability, or signal-to-noise ratio, associated with the forecasts, and the forecast skill are examined. On average, forecasts of 500 hPa geopotential height (GPH) have skill in most of the Tropics and in a few regions of the extratropics. There is broad, but not perfect, agreement between regions of high predictability and regions of high skill. However, model errors are also identified, in particular regions where the forecast ensemble spread appears too small. For individual winters the information provided by t-values, a simple measure of the forecast signal-to-noise ratio, is investigated. For 2 m surface air temperature (T2m), highest t-values are found in the Tropics but there is considerable interannual variability, and in the tropical Atlantic and Indian basins this variability is not directly tied to the El Nino Southern Oscillation. For GPH there is also large interannual variability in t-values, but these variations cannot easily be predicted from the strength of the tropical sea-surface-temperature anomalies. It is argued that the t-values for 500 hPa GPH can give valuable insight into the oceanic forcing of the atmosphere that generates predictable signals in the model. Consequently, t-values may be a useful tool for understanding, at a mechanistic level, forecast successes and failures. Lastly, the extent to which t-values are useful as a predictor of forecast skill is investigated. For T2m, t-values provide a useful predictor of forecast skill in both the Tropics and extratropics. Except in the equatorial east Pacific, most of the information in t-values is associated with interannual variability of the ensemble-mean forecast rather than interannual variability of the ensemble spread. For GPH, however, t-values provide a useful predictor of forecast skill only in the tropical Pacific region.

The role of the Madden-Julian Oscillation in the El Nino and Indian drought of 2002

In 2002 India experienced a severe drought, one among the five worst droughts since records began in 1871, notable for its countrywide influence. The drought was primarily due to an unprecedented break in the monsoon during July, which persisted for almost the whole month and affected most of the sub-continent. The failure of the monsoon in 2002 was not predicted and India was not prepared for the devastating impacts on, for example, agriculture. This paper documents the evolution of the 2002 Indian summer monsoon and considers the possible factors that contributed to the drought and the failure of the forecasts. The development of the 2002/2003 El Nino and the unusually high levels of Madden-Julian Oscillation (MJO) activity during the monsoon season are identified as the central players. The 2002/2003 El Nino was characterised by very high sea-surface temperatures (SSTs) in the central Pacific that developed rapidly during the monsoon season. It is suggested that the unusual character of the developing El Nino was associated with the MJO and was a consequence of the eastward extension of the West Pacific Warm Pool, brought about primarily by a series of westerly wind events (WWEs) as part of the eastward movement of the active phase of the MJO. During the boreal summer, the MJO is usually characterised by northward movement, but in 2002 the northward component of the MJO was weak and the MJO was dominated by a strong eastward component, probably driven by the abnormally high SSTs in the central Pacific. It is suggested that a positive feedback existed between the developing El Nino and the eastward component of the MJO, which weakened the active phases of the monsoon. In particular, the unprecedented monsoon break in July could be associated with the juxtaposition of strong MJO activity with a developing El Nino, both of which interfered constructively with each other to produce major perturbations to the distribution of tropical heating. Subsequently, the main impact of the developing El Nino was a modulation of the Walker circulation that led to the overall suppression of the Indian monsoon during thess latter part of the season. It is argued that the unique combination of a rapidly developing El Nino and strong MJO activity, which was timed within the seasonal cycle to have maximum impact on the Indian summer monsoon, meant that prediction of the prolonged break in July and the seasonally deficient rainfall was a challenge for both the empirical and dynamical forecasting systems. Copyright (C) 2006 Royal Meteorological Society.