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In Aesop's fable, 'The Gnat and the Bull,' a tiny gnat overestimates his importance by presuming that he disturbed a large bull by landing on his horn. However, when the [...]

This paper examines the quality of seasonal probabilistic forecasts of near-global temperature and precipitation issued by the International Research Institute for Climate and Society (IRI) from late 1997 through 2008, using mainly a two-tiered multimodel dynamical prediction system. Skill levels, while modest when globally averaged, depend markedly on season and location and average higher in the tropics than extratropics. To first order, seasons and regions of useful skill correspond to known direct effects as well as remote teleconnections from anomalies of tropical sea surface temperature in the Pacific Ocean (e.g., ENSO related) and in other tropical basins. This result is consistent with previous skill assessments by IRI and others and suggests skill levels beneficial to informed clients making climate risk management decisions for specific applications. Skill levels for temperature are generally higher, and less seasonally and regionally dependent, than those for precipitation, partly because of correct forecasts of enhanced probabilities for above-normal temperatures associated with warming trends. However, underforecasting of above-normal temperatures suggests that the dynamical forecast system could be improved through inclusion of time-varying greenhouse gas concentrations. Skills of the objective multimodel probability forecasts, used as the primary basis for the final forecaster-modified issued forecasts, are comparable to those of the final forecasts, but their probabilistic reliability is somewhat weaker. Automated recalibration of the multimodel output should permit improvements to their reliability, allowing them to be issued as is. IRI is currently developing single-tier prediction components. DOI: 10.1175/2009JAMC2325.1

The International Research Institute (IRI) for Climate Prediction seasonal forecast system is based largely on the predictions of ensembles of several atmospheric general circulation models (AGCMs) forced by two versions of an SST prediction--one consisting of persisted SST anomalies from the current observations and one of evolving SST anomalies as predicted by a set of dynamical and statistical SST prediction models. Recently, an objective multimodel ensembling procedure has replaced a more laborious and subjective weighting of the predictions of the several AGCMs. Here the skills of the multimodel predictions produced retrospectively over the first 4 years of IRI forecasts are examined and compared with the skills of the more subjectively derived forecasts actually issued. The multimodel ensemble predictions are generally found to be an acceptable replacement, although the precipitation forecasts do benefit from inclusion of empirical forecast tools. Planned pattern-level model output statistics (MOS) corrections for systematic biases in the AGCM forecasts may render them more sufficient in their own right.

Extreme phases of the El Nino-Southern Oscillation (ENSO) phenomenon have been blamed for precipitation anomalies in many areas of the world. In some areas the probability of above-normal precipitation may be increased during warm or cold events, while in others below-normal precipitation may be more likely. The percentages of times that seasonal precipitation over land areas was above, near, and below normal during the eight strongest El Nino and La Nina episodes are tabulated, and the significance levels of the posterior probabilities are calculated using the hypergeometric distribution. These frequencies may provide a useful starting point for probabilistic climate forecasts during strong ENSO events. Areas with significantly high or low frequencies or above- or below-normal precipitation are highlighted, and attempts are made to estimate the proportion of land areas with significant ENSO-related precipitation signals. There is a danger of overstating the global impact of ENSO events because only about 20%-30% of land areas experience significantly increased probabilities of above- or below-normal seasonal precipitation during at least some part of the year. Since different areas are affected at different times of the year, the fraction of global land affected in any particular season is only about 15%-25%. The danger of focusing on the impact of only warm-phase events is emphasized also: the global impact of La Nina seems to be at least as widespread as that of El Nino. Furthermore, there are a number of notable asymmetries in precipitation responses to El Nino and La Nina events. For many areas it should not be assumed that the typical climate anomaly of one ENSO extreme is likely to be the opposite of the other extreme. A high frequency of above-normal precipitation during strong El Nino conditions, for example, does not guarantee a high frequency of below-normal precipitation during La Nifia events, or vice versa. On a global basis El Nino events are predominantly associated with below-normal seasonal precipitation over land, whereas La Nina events result in a wider extent of above-normal precipitation.

The International Research Institute for Climate Prediction (IRI) was formed in late 1996 with the aim of fostering the improvement, production, and use of global forecasts of seasonal to interannual climate variability for the explicit benefit of society. The development of the 1997/98 El Nino provided an ideal impetus to the IRI Experimental Forecast Division (IRI EFD) to generate seasonal climate forecasts on an operational basis. In the production of these forecasts an extensive suite of forecasting tools has been developed, and these are described in this paper. An argument is made for the need for a multimodel ensemble approach and for extensive validation of each model's ability to simulate interannual climate variability accurately. The need for global sea surface temperature forecasts is demonstrated. Forecasts of precipitation and air temperature are presented in the form of 'net assessments,' following the format adopted by the regional consensus forums. During the 1997/98 El Nino, the skill of the net assessments was greater than chance, except over Europe, and in most cases was an improvement over a forecast of persistence of the latest month's climate anomaly.