Indian summer monsoon variability forecasts in the North American multimodel ensemble

Area of Science:

• Climate Science
• Atmospheric Science
• Oceanography

Background:

• The Indian summer monsoon rainfall (ISMR) is crucial for South Asia's climate and economy.
• Accurate representation of ISMR in climate models is vital for predicting regional climate variability.
• The North American Multimodal Ensemble (NMME) provides a platform for evaluating global coupled models.

Purpose of the Study:

• To evaluate the performance of NMME phase 1 and phase 2 global coupled models in simulating ISMR.
• To assess the models' ability to capture seasonal mean and interannual variability of ISMR.
• To investigate the representation of sea surface temperature (SST) and its teleconnections with ISMR.

Main Methods:

• Analysis of seasonal mean and interannual variability of ISMR from NMME:1 and NMME:2 (1982-2009).
• Evaluation over the Indo-Pacific domain using May initial conditions.
• Assessment of model-simulated SST and its relationship with rainfall, comparing with observations.

Main Results:

• The multi-model ensemble (MME) shows modest skill and systematic biases in representing ISMR.
• No significant improvement in ISMR forecast skill or variability was found in NMME:2 compared to NMME:1.
• Models skillfully predict seasonal mean SST and some teleconnections, but SST-rainfall links are overestimated, and extremes are poorly captured.

Conclusions:

• Current NMME global coupled models exhibit limitations in accurately simulating ISMR and its variability.
• The models struggle to capture observed SST-rainfall teleconnections and extreme rainfall events.
• Further improvements are needed in model physics and parameterizations to enhance ISMR representation.