Seasonal variability of Indonesian rainfall in ECHAM4 simulations and in the reanalyses : The role of ENSO

• Published in: Theoretical and applied climatology 2007, Vol.87 (1-4), p.41-59
• Main Authors: ALDRIAN, E, DÜMENIL GATES, L, WIDODO, F. H
• Format: Article
• Language: English
• Subjects: Atmospheric circulation; Atmospheric models; Atmospheric research; Climate models; Climatology. Bioclimatology. Climate change; Comparative analysis; Earth, ocean, space; El Nino; Exact sciences and technology; External geophysics; La Nina; Meteorology; Precipitation; Rain gauges; Rainfall; Seasonal variations; Simulation; Southern Oscillation; Water in the atmosphere (humidity, clouds, evaporation, precipitation); Weather forecasting
• ISSN: 0177-798X; 1434-4483
• DOI: 10.1007/s00704-006-0218-8

A study of the skill of the ECHAM version 4 atmospheric general circulation model and two reanalyses in simulating Indonesian rainfall is presented with comparisons to 30 years of rain gauge data. The reanalyses are those performed by the European Centre for Medium-Range Weather Forecasts and of the National Centers for Environmental Prediction jointly with National Center for Atmospheric Research. This study investigates the skill of the reanalyses and ECHAM4 with regard to three climate regions of Indonesia, the annual and interannual variability of rainfall and its responses to El Nino-Southern Oscillation (ENSO) events. The study is conducted at two spectral resolutions, T42 and T106. The skill of rainfall simulations in Indonesia depends on the region, month and season, and the distribution of land and sea. Higher simulation skills are confined to years with ENSO events. With the exception of the northwest region of Indonesia, the rainfall from June (Molucca) and July (south Indonesia) to November is influenced by ENSO, and is more sensitive to El Nino than La Nina events. Observations show that the Moluccan region is more sensitive to ENSO, receives a longer ENSO impact and receives the earliest ENSO impact in June, which continues through to December. It is found that the reanalyses and the climate model simulate seasonal variability better than monthly variability. The seasonal skill is highest in June/July/August, followed by September/October/November, December/January/February and March/April/May. The correlations usually break down in April (for monthly analysis) or in the boreal spring (for seasonal analysis). This period seems to act as a persistent barrier to Indonesian rainfall predictability and skill. In general, the performance of ECHAM4 is poor, but in ENSO sensitive regions and during ENSO events, it is comparable to the reanalyses. [PUBLICATION ABSTRACT]