Model Systematic Errors in the Annual Cycle of Monsoon: Inferences from Process-Based Diagnostics
Forecasting monsoon rainfall using dynamical climate models has met with little success, partly due to models’ inability to represent the monsoon precipitation annual cycle accurately. Here, we review and examine the nature and dynamical causes of their biases. We discuss the coupled nature of the monsoon annual cycle from observations and then present errors in multi-model-mean, climatological fields of ocean–atmosphere variables determined from CMIP5. We argue that in CMIP-era models, there is a spatial redistribution in the organization of convection, and precipitation biases are longitudinally oriented with “wet-west” and “dry-east” over the tropical Indian Ocean, with wet (dry) biases prominent over the climatological dry (wet) regions. Irrespective of resolutions and varied physical parameterizations employed in CMIP-era models, the robustness in the biases across the suite of models suggests that multiple processes and their interactions lead to these persistent errors. We review recent literature that addressed the source(s) of model errors and indicate the importance of examining both atmospheric and oceanic fast processes. After discussing the unique nature of observed convection peak during May over the western Indian Ocean, we demonstrate through idealized experiments, how errors in the representation of ocean–atmosphere feedbacks along the equatorial Indian Ocean impact monsoon precipitation errors. We apply process-based diagnostics to identify the relative role of moist and radiative processes and show how systematic errors in certain parameterizations could anchor model biases in precipitation. Despite devoted efforts by the model development teams, persistence of model errors leads us to ask: are there fundamental limits to realistically simulating the monsoon annual cycle? Can a concerted observational and modeling effort enhance models’ fidelity in simulating the monsoon? We summarize the pertinent issues on modeling, and limitations on observations to constrain model physics, and stress the need for coordinated activities across diagnostics, modeling, and observational personnel.
KeywordsSystematic errors Processes representation Fundamental limits
This research work is funded by the National Science Foundation (NSF) under grant 1460742. The author also acknowledges the financial support provided by the Indian Monsoon Mission and JAMSTEC. Jan Hafner is thanked for his assistance with diagnostics.
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