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

Aldrian, Edvin and Gates, L Dumenil and Widodo, Florentinus Heru (2006) Seasonal variability of Indonesian rainfall in ECHAM4 simulations and in the reanalyses: The role of ENSO. Theoretical and Applied Climatology, 87 (1-4). pp. 41-59.

[thumbnail of _Seasonal variability of Indonesian rainfall in ECHAM4 simulations and in the reanalyses.pdf]
Preview
Text
_Seasonal variability of Indonesian rainfall in ECHAM4 simulations and in the reanalyses.pdf

Download (990kB) | Preview

Abstract

A study of the skill of the ECHAM version 4 atmospheric general circulation model and two reanalyses in simulat ing 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 Ni~no-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 Ni~no than La Ni~na 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 simu late seasonal variability better than monthly variability. The seasonal skill is highest in June=July=August, follow ed 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.

Item Type: Article
Additional Information: DDC'23: 551.577
Uncontrolled Keywords: Atmospheric science; Rainfall; Climatology; Climate
Subjects: Atmospheric Sciences > Meteorological Data Collection, Analysis, & Weather Forecasting
Atmospheric Sciences > Meteorological Instruments & Instrument Platforms
Depositing User: Rasty -
Date Deposited: 20 Oct 2022 08:00
Last Modified: 21 Oct 2022 01:36
URI: https://karya.brin.go.id/id/eprint/12333

Actions (login required)

View Item
View Item