Fidelity of CMIP5 multi-model mean in assessing Indian monsoon simulations

Abstract

Considering the wide use of the multi-model mean (MMM) on the seasonal time scale, this work examines its fidelity in simulating some important characteristics of the Indian summer monsoon using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations. It is noted that the MMM captures the observed spatial pattern and annual cycle of surface air temperature to a great extent, but there are large biases in magnitude, particularly over north India. For precipitation, only the broad-scale features are captured and extreme large biases, of magnitude equal or higher than the seasonal mean precipitation, exist in the MMM. The simulation of trends in seasonal mean temperatures and precipitation is even less satisfactory than the climatological means. Several precipitation features, for example, low-to-moderate intensity precipitation events, orography-related rain bands, extreme events, are noted to improve with increasing resolution of the models, whereas, no such improvement is noted for temperatures. It is also noted that the improvement in CMIP5 MMM is marginal if compared with the best performing model from the group of models considered for analysis. There are several models that show similar skill as MMM, and therefore could be alternatively used for future projections. Moreover, using such individual models for Indian monsoon projections will also help us to understand the underlying mechanisms and processes by conducting targeted numerical experiments, which would otherwise be highly limited by approaches like MMM. Therefore, targeted efforts to improve some of these better models are required to gain more confidence in future projections of Indian monsoon.

Near‐Future Anthropogenic Aerosol Emission Scenarios and Their Direct Radiative Effects on the Present‐Day Characteristics of the Indian Summer Monsoon

“…Among the main biases is an underestimation of precipitation by 2 to 6 mm/day over some central regions of India (Figure c). This problem is however common to many global and regional models over the Indian subcontinent, and in fact, our model performance is in line with most previous studies (Mishra et al, ; Singh et al, ; Sperber et al, ). This dry bias may be associated with reduced soil moisture availability simulated by CLM4.5 (Maharana et al, ).…”

Future exacerbation of hot and dry summer monsoon extremes in India

“…According to CESM-LENS, in spite of seemingly stable SPEI projections due to moderate increases in future monsoon rainfall, the long-lived rise in surface-air temperatures will conspire with El Niño to yield extreme seasonal heat and dryness. Since our analysis is based on the single model (CESM-LENS), additional analyses with other global climate models that show reasonable skill in capturing the ENSO-monsoon relationship 41,42 can provide additional insights into the increasing contribution of El-Nino events in driving the rising concurrence of hot and dry extremes over India under the warming climate. Nonetheless, the increased severity of hot and dry monsoon extremes is likely to pose a substantial challenge to the future food security of the Indian subcontinent.…”

On the Projected Decline in Droughts Over South Asia in CMIP6 Multimodel Ensemble

“…Previous studies (Ashfaq et al, 2017;Jain et al, 2019;Mishra, Sahany, et al, 2018;Sabeerali et al, 2015;Saha et al, 2014) based on the CMIP5-GCMs reported that the majority of GCMs fail to capture the summer monsoon variability over South Asia. Consistent with the CMIP5-GCMs, we find that the majority of the CMIP6-GCMs are not able to capture the South Asian summer monsoon variability (Table S3 and Figures 3 and S4).…”