Monsoons Climate Change Assessment

Wang, Bin; Biasutti, Michela; Byrne, Michael P.; Castro, Christopher L.; Chang, C. P.; Cook, Kerry H.; Fu, Rong; Grimm, Alice M.; Ha, Kyung‐Ja; Hendon, Harry H.; Kitoh, Akio; Krishnan, R.; Lee, June‐Yi; Li, Jianping; Liu, Jian; Moise, Aurel; Pascale, Salvatore; Roxy, Mathew Koll; Seth, Anji; Sui, Chung‐Hsiung; Turner, Andrew; Yang, Song; Yun, Kyung Sook; Zhang, Lixia; Zhou, Tianjun

doi:10.1175/bams-d-19-0335.1

Cited by 159 publications

(102 citation statements)

References 155 publications

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“…The WAF region climate is mainly influenced by the West African monsoon system. In a recent study (Wang et al 2020), it was found that CMIP6 models are better able to simulate global monsoon intensity and precipitation than CMIP5 models. This finding also holds for the WAF monsoon, although common biases and large intermodal spreads persist.…”

Section: West Africa (Waf)mentioning

confidence: 99%

Projected Change in Temperature and Precipitation Over Africa from CMIP6

et al. 2020

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We analyze data of 27 global climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), and examine projected changes in temperature and precipitation over the African continent during the twenty-first century. The temperature and precipitation changes are computed for two future time slices, 2030–2059 (near term) and 2070–2099 (long term), relative to the present climate (1981–2010), for the entire African continent and its eight subregions. The CMIP6 multi-model ensemble projected a continuous and significant increase in the mean annual temperature over all of Africa and its eight subregions during the twenty-first century. The mean annual temperature over Africa for the near (long)-term period is projected to increase by 1.2 °C (1.4 °C), 1.5 °C (2.3 °C), and 1.8 °C (4.4 °C) under the Shared Socioeconomic Pathways (SSPs) for weak, moderate, and strong forcing, referenced as SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. The future warming is not uniform over Africa and varies regionally. By the end of the twenty-first century, the largest rise in mean annual temperature (5.6 °C) is projected over the Sahara, while the smallest rise (3.5 °C) is over Central East Africa, under the strong forcing SSP5-8.5 scenario. The projected boreal winter and summer temperature patterns for the twenty-first century show spatial distributions similar to the annual patterns. Uncertainty associated with projected temperature over Africa and its eight subregions increases with time and reaches a maximum by the end of the twenty-first century. On the other hand, the precipitation projections over Africa during the twenty-first century show large spatial variability and seasonal dependency. The northern and southern parts of Africa show a reduction in precipitation, while the central parts of Africa show an increase, in future climates under the three reference scenarios. For the near (long)-term periods, the area-averaged precipitation over Africa is projected to increase by 6.2 (4.8)%, 6.8 (8.5)%, and 9.5 (15.2)% under SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. The median warming simulated by the CMIP6 model ensemble remains higher than the CMIP5 ensemble over most of Africa, reaching as high as 2.5 °C over some regions, while precipitation shows a mixed spatial pattern.

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Section: West Africa (Waf)mentioning

confidence: 99%

Projected Change in Temperature and Precipitation Over Africa from CMIP6

et al. 2020

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“…The cloud‐radiation process is one of the major uncertainties in current climate simulations and predictions (Boucher et al., 2013; Stephens, 2005; Webb et al., 2017). A reasonable projection for the TP and Asian monsoon climate, therefore, highly depends on an in‐depth understanding of cloud‐radiation processes and their improvement in climate models (B. Wang et al., 2020; T. Zhou et al., 2016).…”

Section: Introductionmentioning

confidence: 99%

“…Eastern China (EC) and South Asia (SA), adjacent to the TP, have significant features of the Asian monsoon climate such as remarkable seasonal variation of circulation, precipitation, and cloud fractions (Ding & Chan, 2005; Luo et al., 2009; Tao & Chen, 1987; Webster et al., 1998; Zhao et al., 2019). These three subregions are integral parts of the whole Asian monsoon region, and regional surface temperature, precipitation, and cloud‐radiation processes are very sensitive to current climate change (Ma et al., 2021; Turner & Annamalai, 2012; B. Wang et al., 2020; You et al., 2020). Understanding and predicting the Asian monsoon climate is of great scientific and societal importance owing to its huge impact on the population of a large region and sustainable socio‐economic development.…”

Section: Introductionmentioning

confidence: 99%

“…F. Li et al., 2013; Wang, Yang, & Wu, 2014). These biases contribute to current difficulties in simulation and prediction of the Asian monsoon climate to a high degree (Boo et al., 2011; Sperber et al., 2013; B. Wang et al., 2020; T. Zhou et al., 2016). In present climate models, TOA radiation budget and cloud radiative effects (CREs) are key evaluation metrics (Flato et al., 2013).…”

Section: Introductionmentioning

confidence: 99%

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Top‐of‐Atmosphere Radiation Budget and Cloud Radiative Effects Over the Tibetan Plateau and Adjacent Monsoon Regions From CMIP6 Simulations

Sun

Liu

et al. 2021

JGR Atmospheres

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This study investigates the top‐of‐atmosphere (TOA) radiation budget (RT) and cloud radiative effects (CREs) over the Tibetan Plateau (TP) and adjacent Asian monsoon regions including Eastern China (EC) and South Asia (SA) using the Coupled Model Intercomparison Project 6 (CMIP6) simulations. Considerable simulation biases occur but specific causes differ in these regions. Most models underestimate the intensity of annual mean RT and cloud radiative cooling effect over the TP, and the RT during the cold‐warm transition period is hard to capture. The biases in surface temperature and cloud fractions substantially contribute to cloud‐radiation biases over the western and eastern TP, respectively. Over EC, the intensity of RT and cloud radiative cooling effect is seriously underestimated especially in the springtime when the model spread is large, and their biases are closely related to less low‐middle cloud fractions and weaker ascending motion. Over SA, simulation biases mainly arise from longwave radiative components associated with less high cloud fraction and weaker convection, with the large model spread in the summertime. The annual cycles of RT and CREs over EC and SA can be well reproduced by most models, while the summertime peak of the net CRE over the TP occurs later than the observation. The RT and its simulation bias strongly depend on the cloud radiative cooling effect over EC and SA. Our results demonstrate that contemporary climate models still have obvious difficulties in representing various complex cloud‐radiation processes in Asian monsoon regions.

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“…Several studies suggest that the CMIP5 multi-model ensemble mean captures well observed spatial patterns and interannual variability of GM's rainfall, though most individual models underestimate its extent and intensity (Flato et al, 2013;Wang et al, 2017). CMIP6 models simulate better global monsoon intensity and precipitation over CMIP5 models, but common biases and large intermodal spreads persist (Wang et al, 2020). Moreover, projected CMIP6 monsoon precipitation indicates that an important uncertainty arises from circulation changes, which can be partly explained by model-dependent response to uniform sea surface temperature warming (Chen et al, 2020).…”

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confidence: 99%

The monsoon hydroclimates in HadGEM3 model configurations GA3.0 and GA4.0: Impact of remote versus local circulations errors and horizontal resolution

Moufouma-Okia

Vondou

Jones

2020

Preprint

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Abstract. State-of-the-science general circulation models (GCMs) are the primary tools for making policy-relevant climate calculations. Yet, these models face challenges in monsoon regions where live more than 70 % of the world's population, due to the complex interplay of local and remote influences on a spectrum of space and time scales. This work examines the fidelity to reproduce regional and global monsoons climatological features using the Met Office Unified Model (MetUM) third and fourth generations Global Atmosphere (GA3.0) and (GA4.0), two configurations of the HadGEM3 system developed for seamless use across climate and weather time scales. Results are compared both against multiple observational gridded datasets and outputs from 20 atmospheric-only GCMs simulations from the CMIP5 campaign. Furthermore, we investigate the influence of remote versus local atmospheric circulation errors by constraining realistically HadGEM3 circulations over a prescribed monsoon domain and examining the consequences outside and inside this domain using the grid-point nudging method. The GA3.0 largely captures global monsoon features, including the monsoon precipitation patterns and extent of regional monsoon domains, when integrated using a low (~ 135-km in mid-latitudes), medium (~ 60 km in mid-latitudes) and high (~ 25 km in mid-latitudes) horizontal resolutions. GA4.0 and GA3.0 results display a close similarity, and compares reasonably well against the best available CMIP5 models. The common failure of HadGEM3 configurations is the simulated weak magnitude and extent of the Asian Summer Monsoon (ASM) precipitation pattern, and associated low-level Somali jet. This situation is also apparent within HadGEM2-A, ACCESS1-0, and CSIRO-Mk3-6-0 – three GCMs sharing dynamical and physical components. HadGEM3 performance improves significantly over ASM with atmospheric circulations constrained realistically over the tropics, West African and Asian Summer monsoon domains. Conversely, constraining atmospheric circulations over other remote monsoon domains show little influence on the ASM precipitation. We argue that GA4.0 and GA3.0 poor simulations over the ASM domain are attributable, partly to local atmospheric circulations errors and excessive precipitation over the southwest equatorial Indian Ocean, rather than to remote tropical atmospheric responses of varying forcing fields, such as SST over the Arabian Sea, aerosols, and growing greenhouse gas emissions. The improved understanding of GCM performance in monsoon regions is an important step for credible projections of global monsoon changes.

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Monsoons Climate Change Assessment

Abstract: Capsule Summary This paper reviews the current knowledge on detection, attribution and projection of global and regional monsoons (South Asian, East Asian, Australian, South American, North American, and African) under climate change.

Cited by 159 publications

References 155 publications

Projected Change in Temperature and Precipitation Over Africa from CMIP6

Projected Change in Temperature and Precipitation Over Africa from CMIP6

Top‐of‐Atmosphere Radiation Budget and Cloud Radiative Effects Over the Tibetan Plateau and Adjacent Monsoon Regions From CMIP6 Simulations

The monsoon hydroclimates in HadGEM3 model configurations GA3.0 and GA4.0: Impact of remote versus local circulations errors and horizontal resolution

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