Intraseasonal and seasonal predictability of monsoon of high-resolution models in project Athena

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Thursday, 27 January 2011: 4:30 PM
Intraseasonal and seasonal predictability of monsoon of high-resolution models in project Athena
609 (Washington State Convention Center)
Emilia Kyung Jin, COLA, Calverton, MD

The Project Athena collaboration brought together an international team of over 30 people from six institutions on three continents, including climate and weather scientists and modelers, and experts in high‐end computing (HEC), to demonstrate the feasibility of using dedicated HEC resources to rapidly accelerate progress in addressing one of the most critical problems facing the global community, namely, global climate change. The scientific basis for undertaking this project was established in the World Modeling Summit, held in May 2008 in Reading, UK, where there was a call for a revolution in seamless weather and climate modeling. Using dedicated high-end computing support which is the entire 18,048‐core Athena Cray XT‐4 supercomputer, the numerical experiments were conducted with two state‐of‐the‐art global atmospheric models run at the highest possible resolutions. The Non‐hydrostatic ICosahedral Atmospheric Model (NICAM) global cloud-system resolving atmospheric model was run at 7‐km grid resolution to simulate the boreal summer climate during 2001-2009. Experimental 10‐km (T2047), 16‐km (T1279) and operational 40-km (T511), 128-km (T159) versions of the ECMWF Integrated Forecast System (IFS), a global atmospheric general circulation model, which is used daily to produce 10‐day weather forecasts, were run on multi-year timescales. The boreal summer cases of T2047 IFS during 2001-2009 and the 13-month hindcast experiments of lower resolutions during 1960-2008 has conducted along with 50-year AMIP simulations. Based on these experiments, the impact of resolution and cloud resolving on the intraseasonal and seasonal predictability of Asian–Australian monsoon has been analyzed. The NICAM outperforms IFS to simulate Indian monsoon rainfall. The increase of horizontal resolution generally improves the forecast skill of Indian monsoon rainfall. The ENSO-monsoon relationship shows moderate improvement in higher resolution. The spatial and temporal characteristics of subseasonal variability of monsoon rainfall shows more realistic representation in higher resolution.