Scholarlink

<p>The Indian Summer Monsoon Rainfall (ISMR) and its extremes exhibit substantial complexity due to the region’s intricate land–ocean distribution and diverse topography, and remain crucial for the livelihoods of billions across the Indian subcontinent. This study examines the influence of increased horizontal resolution on persistent dry biases over India and associated physical mechanisms, using the High-Resolution Model Intercomparison Project (HighResMIP) data under the PRIMAVERA framework. The analysis demonstrates that higher-resolution models show marked improvements in reproducing the mean ISMR and its extremes, with rainfall distributions more consistent with observations. Enhanced resolution also contributes to a more realistic simulation of intraseasonal variability, particularly the active and break phases of the monsoon. However, considerable inter-model spread remains even at finer resolutions, highlighting the ongoing role of model physics and parameterization schemes in determining simulation fidelity. These findings underscore the added value of increased horizontal resolution in reducing systematic biases and enhancing the representation of monsoon variability, while emphasizing the need for continued improvements in the physical representation of key processes within climate models.</p> Graphical Abstract <p>This figure summarizes the study, which investigates the role of enhanced horizontal resolution in simulating Indian Summer Monsoon (ISM) extremes and intraseasonal variability. Rainfall data from the India Meteorological Department (IMD) and 850&#xa0;hPa wind data from ERA5 are used to evaluate the performance of models participating in HighResMIP, listed in the blue box. The study conducts extreme rainfall analyses using both observed and model datasets, and Kernel Density Estimation (KDE) is applied to examine rainfall distribution. The results confirm that finer-resolution models reproduce the observed distribution more accurately and capture extreme rainfall events over the Indian landmass. Spatial bias maps are analyzed to understand regional variability, revealing that coarser models exhibit notable dry biases over northern India, which are reduced in most high-resolution models, except for NorESM2-MM, where biases remain pronounced. Performance gains are assessed not only for mean rainfall but also for extremes, and the ETCCDI indices demonstrate that finer-resolution models are more skillful in representing extreme rainfall events. The study further examines intraseasonal variability, including active and break spells during July–August over the core monsoon zone, and evaluates the models’ ability to depict the low-level jet (LLJ) at 850&#xa0;hPa, a key feature of ISM circulation. The results highlight that high-resolution models consistently outperform their coarser counterparts, capturing mean rainfall, extremes, intraseasonal variability, and seasonal wind patterns more realistically. Overall, the findings demonstrate that high-resolution models offer substantial improvements for monsoon simulation, providing better representation of mean and extreme rainfall as well as LLJ dynamics. However, model physics and parameterization schemes continue to play a critical role in modulating model performance, indicating that resolution alone is not sufficient for achieving optimal skill.</p> <p></p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Reliability of HighResMIP CMIP6 Models for Indian Summer Monsoon Extremes and Intraseasonal Variability: Insights from Enhanced Horizontal Resolution

  • 期刊论文

  • 发表日期：

    2026年1月8日

查看全文
  • Amita Kumari,
  • Alok Kumar Mishra,
  • Amit Kumar

摘要

The Indian Summer Monsoon Rainfall (ISMR) and its extremes exhibit substantial complexity due to the region’s intricate land–ocean distribution and diverse topography, and remain crucial for the livelihoods of billions across the Indian subcontinent. This study examines the influence of increased horizontal resolution on persistent dry biases over India and associated physical mechanisms, using the High-Resolution Model Intercomparison Project (HighResMIP) data under the PRIMAVERA framework. The analysis demonstrates that higher-resolution models show marked improvements in reproducing the mean ISMR and its extremes, with rainfall distributions more consistent with observations. Enhanced resolution also contributes to a more realistic simulation of intraseasonal variability, particularly the active and break phases of the monsoon. However, considerable inter-model spread remains even at finer resolutions, highlighting the ongoing role of model physics and parameterization schemes in determining simulation fidelity. These findings underscore the added value of increased horizontal resolution in reducing systematic biases and enhancing the representation of monsoon variability, while emphasizing the need for continued improvements in the physical representation of key processes within climate models.

Graphical Abstract

This figure summarizes the study, which investigates the role of enhanced horizontal resolution in simulating Indian Summer Monsoon (ISM) extremes and intraseasonal variability. Rainfall data from the India Meteorological Department (IMD) and 850 hPa wind data from ERA5 are used to evaluate the performance of models participating in HighResMIP, listed in the blue box. The study conducts extreme rainfall analyses using both observed and model datasets, and Kernel Density Estimation (KDE) is applied to examine rainfall distribution. The results confirm that finer-resolution models reproduce the observed distribution more accurately and capture extreme rainfall events over the Indian landmass. Spatial bias maps are analyzed to understand regional variability, revealing that coarser models exhibit notable dry biases over northern India, which are reduced in most high-resolution models, except for NorESM2-MM, where biases remain pronounced. Performance gains are assessed not only for mean rainfall but also for extremes, and the ETCCDI indices demonstrate that finer-resolution models are more skillful in representing extreme rainfall events. The study further examines intraseasonal variability, including active and break spells during July–August over the core monsoon zone, and evaluates the models’ ability to depict the low-level jet (LLJ) at 850 hPa, a key feature of ISM circulation. The results highlight that high-resolution models consistently outperform their coarser counterparts, capturing mean rainfall, extremes, intraseasonal variability, and seasonal wind patterns more realistically. Overall, the findings demonstrate that high-resolution models offer substantial improvements for monsoon simulation, providing better representation of mean and extreme rainfall as well as LLJ dynamics. However, model physics and parameterization schemes continue to play a critical role in modulating model performance, indicating that resolution alone is not sufficient for achieving optimal skill.