10 Nov 2023
 | 10 Nov 2023
Status: this preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).

Development of Indian summer monsoon precipitation biases in two seasonal forecasting systems and their response to large-scale drivers

Richard J. Keane, Ankur Srivastava, and Gill M. Martin

Abstract. The Met Office Global Coupled Model (GC) and the NCEP Climate Forecast System (CFSv2) are both widely used for predicting and simulating the Indian summer monsoon (ISM), and previous studies have demonstrated similarities in the biases in both systems at a range of time scales from weather forecasting to climate simulation. In this study, ISM biases are studied in seasonal forecasting setups of the two systems, in order to provide insight into how they develop across time scales. Similarities are found in the development of the biases between the two systems, with an initial reduction in precipitation followed by a recovery associated with an increasingly cyclonic wind field to the north-east of India. However, this occurs on longer time scales in CFSv2, with a much stronger recovery followed by a second reduction associated with sea surface temperature (SST) biases, so that the bias at longer lead times is of a similar magnitude to that in GC. In GC, the precipitation bias is almost fully developed within a lead time of just eight days, suggesting that carrying out simulations with short time integrations may be sufficient for obtaining substantial insight into the biases in much longer simulations. The relationship between the precipitation and SST biases in GC seems to be more complex than in CFSv2, and is different during the early part of the monsoon season from during the later part of the monsoon season.

The relationship of the bias with large-scale drivers is also investigated, using the Boreal Summer IntraSeasonal Oscillation (BSISO) index as a measure of whether the large-scale dynamics favours increasing, active, decreasing or break monsoon conditions. Both models simulate decreasing conditions the best and increasing conditions the worst, in agreement with previous studies and extending these previous results to include CFSv2 and multiple BSISO cycles.

Richard J. Keane et al.

Status: open (until 01 Jan 2024)

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Richard J. Keane et al.

Richard J. Keane et al.


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Short summary
This work evaluates the performance of two widely used models in forecasting the Indian summer monsoon, which is one of the most challenging meteorological phenomena to simulate. The work links previous studies evaluating use of the models in weather forecasting and climate simulation, as the focus here is on seasonal forecasting, which involves intermediate time scales. As well as being important in itself, this evaluation provides insights into how errors develop in the two modelling systems.