On the climate model simulation of Indian monsoon low pressure systems and the effect of remote disturbances and systematic biases
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Monsoon low pressure systems (LPS) are synoptic-scale systems forming over the Indian monsoon trough region, contributing substantially to seasonal mean summer monsoon rainfall there. Many current global climate models (GCMs), including the Met Office Unified Model (MetUM), show deficient rainfall in this region, much of which has previously been attributed to remote systematic biases such as excessive equatorial Indian Ocean (EIO) convection, while also substantially under-representing LPS and associated rainfall as they travel westwards across India. Here the sources and sensitivities of LPS to local, remote and short-timescale forcing are examined, in order to understand the poor representation in GCMs. An LPS tracking method is presented using TRACK feature tracking software for comparison between re-analysis data-sets, MetUM GCM and regional climate model (RCM) simulations. RCM simulations, at similar horizontal resolution to the GCM and forced with re-analysis data at the lateral boundaries, are carried out with different domains to examine the effects of remote biases. The results suggest that remote biases contribute significantly to the poor simulation of LPS in the GCM. As these remote systematic biases are common amongst many current GCMs, it is likely that GCMs are intrinsically capable of representing LPS, even at relatively low resolution. The main problem areas are time-mean excessive EIO convection and poor representation of precursor disturbances transmitted from the Western Pacific. The important contribution of the latter is established using RCM simulations forced by climatological 6-hourly lateral boundary conditions, which also highlight the role of LPS in moving rainfall from steep orography towards Central India.
KeywordsIndian monsoon Low pressure systems Systematic bias Global climate model Regional climate model
The authors were supported by the Joint UK BEIS/Defra Met Office Hadley Centre Climate Programme (GA01101). The authors acknowledge the use of the Indian Meteorological Department (IMD) eAtlas products developed by Cyclone warning Research Centre (Regional Meteorological Centre, Chennai, India), and the use of the TRACK feature tracking software developed by Kevin Hodges of Reading University. Thanks go to Chang Wang, Erica Neininger and Simon Tucker for technical help with the MetUM. Thanks also goes to William R. Boos of Yale University for useful discussions on monsoon LPS. The authors also thank three anonymous reviewers, whose comments have helped improve the manuscript.
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