El Nino Suppresses Aantarctic Warming

Here we present new isotope records derived from snow samples from the McMurdo Dry Valleys, Antarctica and re-analysis data of the European Centre for Medium-Range Weather Forecasts (ERA-40) to explain the connection between the warming of the Pacific sector of the Southern Ocean [Jacka and Budd, 1998; Jacobs et al., 2002] and the current cooling of the terrestrial Ross Sea region [Doran et al., 2002a]. Our analysis confirms previous findings that the warming is linked to the El Nino Southern Oscillation (ENSO) [Kwok and Comiso, 2002a, 2002b; Carleton, 2003; Ribera and Mann, 2003; Turner, 2004], and provides new evidence that the terrestrial cooling is caused by a simultaneous ENSO driven change in atmospheric circulation, sourced in the Amundsen Sea and West Antarctica.

La vita di Nino Bixio.

Mode of access: Internet.

Alternativas para el cuidado de nino s del Departamento De Servicios para Nino s y Familias.

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El nino perdido : juguete comico en un acto y en verso /

Mode of access: Internet.

Three putative types of El Nino revealed by spatial variability in impact on Australian wheat yield

The El Nino-Southern Oscillation (ENSO) phenomenon significantly impacts rainfall and ensuing crop yields in many parts of the world. In Australia, El Nino events are often associated with severe drought conditions. However, El Nino events differ spatially and temporally in their manifestations and impacts, reducing the relevance of ENSO-based seasonal forecasts. In this analysis, three putative types of El Nino are identified among the 24 occurrences since the beginning of the twentieth century. The three types are based on coherent spatial patterns (footprints) found in the El Nino impact on Australian wheat yield. This bioindicator reveals aligned spatial patterns in rainfall anomalies, indicating linkage to atmospheric drivers. Analysis of the associated ocean-atmosphere dynamics identifies three types of El Nino differing in the timing of onset and location of major ocean temperature and atmospheric pressure anomalies. Potential causal mechanisms associated with these differences in anomaly patterns need to be investigated further using the increasing capabilities of general circulation models. Any improved predictability would be extremely valuable in forecasting effects of individual El Nino events on agricultural systems.