How well do the CMIP6 HighResMIP models simulate precipitation over the Tibetan Plateau?

Chen, Quanliang; Ge, Fei; Jin, Zhengrui; Lin, Zhiye

doi:10.1016/j.atmosres.2022.106393

Cited by 12 publications

(12 citation statements)

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“…The spatial correlation coefficient between RAP and GPCC was 0.77 with a root mean square error (RMSE) of 1.9 mm day −1 , while the correlation coefficient between CESM-LME and GPCC was 0.74 with an RMSE of 3.7 mm day −1 . However, both the RAP and CESM-LME exhibited some wet bias over the southern TP, which is a common error in global climate models (GCMs) (Zhu et al, 2020;Chen et al, 2022). In addition, to detect the decadal variability of precipitation, we conducted the empirical orthogonal function (EOF) analysis during the period 1901-2000 for GPCC, RAP, and CESM-LME.…”

Section: Validation Of Reconstructions and Simulationsmentioning

confidence: 99%

Decadal variability of precipitation over the Tibetan Plateau modulated by the 11-year solar cycle over the past millennium

Sun²,

Liu³

et al. 2023

Front. Earth Sci.

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Introduction: Knowledge of precipitation over the Tibetan Plateau, often referred to as the “Asian water tower”, is crucial for water resource management, infrastructure planning, and disaster mitigation. However, the decadal variability of Tibetan Plateau precipitation in response to the 11-year solar cycle remains unknown.Methods: Here, we used observational data obtained between 1901 and 2013, together with proxy-based reconstructions of the past five centuries, and discovered a notable summer wet condition over the central‒southern Tibetan Plateau, accompanied by a dry condition over the southeastern Tibetan Plateau, during peaks in the 11-year solar cycle. Using an ensemble mean of four solar-only sensitivity experiments from the Community Earth System Model Last Millennium Ensemble (CESM‒LME), we further demonstrated that the 11-year solar cycle can induce this anomalous pattern of a wet central‒southern and dry southeastern Tibetan Plateau.Results and discussion: The modeling results indicated that, under a solar maximum, a substantial surface warming occurs over the Asian continent, especially the Tibetan Plateau region; this causes an anomalous Tibetan Plateau–Indian Ocean thermal contrast, which enhances the Indian summer monsoon. The additional Tibetan Plateau heating also enhances and causes a northward shift of the South Asian High, which further intensifies the Indian summer monsoon. The enhanced Indian summer monsoon transports water vapor to the northern Indian continent, which rises upon reaching the central‒southern Tibetan Plateau, substantially increasing precipitation. Meanwhile, a negative Pacific Decadal Oscillation-like sea surface temperature pattern occurs under a solar maximum, leading to a large-scale anticyclonic anomaly over the Yangtze River basin, southeastern Tibetan Plateau, and southern Japan, substantially decreasing precipitation in these regions.

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Section: Validation Of Reconstructions and Simulationsmentioning

confidence: 99%

Decadal variability of precipitation over the Tibetan Plateau modulated by the 11-year solar cycle over the past millennium

Sun²,

Liu³

et al. 2023

Front. Earth Sci.

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“…The thermodynamic contribution is mainly related to changes in atmospheric temperature and moisture, while the dynamic contribution is caused by changes in atmospheric motion. The covariation term represents the changes in the eddy flux and is generally smaller than the other two terms over the TP (Chen et al, 2022; Gao et al, 2014; Wang et al, 2017). In the context of climate warming, the thermodynamic contribution is expected to increase due to increases in saturation specific humidity following the Clausius–Clapeyron relationship (Trenberth et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Precipitation variability related to atmospheric circulation patterns over the Tibetan Plateau

Lai,

Chen,

Chen

2023

Intl Journal of Climatology

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Precipitation is affected by intricate atmospheric dynamic and thermodynamic processes. Horizontal winds are frequently used to represent the dynamic component as winds play a critical role in transporting moisture. Previous studies on precipitation over the Tibetan Plateau (TP) focused on the influence of summer monsoons and westerlies in isolation. However, the collective seasonal dynamics and their combined effects on the precipitation distribution remain less explored. This study aims to determine the seasonal evolutions of the wind patterns and the associated regional precipitation patterns over the TP using a neural network approach and focuses on their interannual variability and long‐term trends. A self‐organizing map (SOM) was used to classify the wind patterns based on 500 hPa winds and related precipitation from the ERA5 reanalysis. The classified wind patterns show seasonal shifts between the Asian summer monsoon circulations and the westerlies along with the westerly jets migrating between the north and south of the TP from summer to winter. The locations of abundant precipitation during the winter and transition seasons are mainly associated with variations in the intensity and locations of the strong westerlies. There is a significant positive trend in the occurrences of the summer‐type wind pattern, which has likely led to a wetter TP, and an earlier‐ended winter and advanced spring wind patterns. The interannual variability of westerlies is highly related to the variability of precipitation in the western TP during its wet season (January–April). In the eastern TP, the interannual variability of the precipitation is linked to the wind patterns associated with the westerly jets to the south of the TP, while precipitation variability in the central TP is controlled by thermodynamic components. This study reveals the spatial precipitation distributions according to the different wind patterns and identifies the contributions from atmospheric components to the regional precipitation over the TP.

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“…Recently, several studies (Ajibola et al 2020;Bador et al 2020;Strandberg et al 2021;Liang-Liang et al 2022;Chen et al 2022;Scoccimarro et al 2022;Liang et al 2023;Jin et al 2023;) have been dedicated to assessing the importance of enhancing spatial resolution in simulating precipitation characteristics using CMIP6 HighResMIP models. Several of these studies concluded that increasing the spatial resolution of GCMs within the CMIP6 HighResMIP experiment improved the model performance in simulating precipitation characteristics.…”

mentioning

confidence: 99%

“…However, contrasting findings exist, with other studies indicating that an increase in spatial resolution results in deterioration in model performance. For instance, Chen et al (2022) and Jin et al (2023) reported that an increase in spatial resolution reduces biases in simulating precipitation extremes over the Tibetan Plateau and southwest China, respectively. In contrast, Bador et al (2023) reported that global climate models (GCMs) with enhanced spatial resolution under the CMIP6 HighResMIP project often exhibit lower skill than their low-resolution counterparts in simulating global land extreme precipitation.…”

mentioning

confidence: 99%

“…In summary, the increase in horizontal resolution in CMIP6 HighResMIP exacerbated the wet bias for both R95p and R99p across the basins compared to their LR counterparts (Fig.10).Bador et al (2023) reported that within the framework of CMIP6 HighResMIP, global land precipitation extremes are more intense in high-resolution (HR) models than in their LR counterparts. The intensification of the wet bias in HR models compared to that in their LR counterparts can be attributed to the differences in simulating atmospheric circulation(Chen et al 2022). Another plausible mechanism is the enhancement of convective process linked to highly resolved topography.…”

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confidence: 99%

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Exploring the Influence of Improved Horizontal Resolution on Extreme Precipitation in Southern Africa Major River Basins: Insights from CMIP6 HighResMIP Simulations

Samuel,

Tsidu,

Dosio

et al. 2024

Preprint

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This study examines the impact of enhanced horizontal resolution on simulating mean and precipitation extremes in the major river basins of southern Africa. Seven global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP) within the Coupled Model Intercomparison Project Phase 6 (CMIP6) are employed. The models are available at both high-resolution (HR) and low-resolution (LR) resolutions. Three datasets are used to assess the models for the period 1983-2014 during December-January-February. The distributions of daily precipitation from the HR models are nearly identical to those of their LR counterparts. However, the bias of intense daily precipitation is not uniform across the three observations. Most HR and LR models reasonably simulate mean precipitation, maximum consecutive dry days (CDD), and the number of rainy days (RR1), albeit with some biases. Improvements due to enhanced horizontal resolution are realised for mean precipitation, CDD, and RR1 as noted from high spatial correlation coefficients (SCCs), low root mean square errors, and biases. The CMIP6 HighResMIP models tend to overestimate very and extreme wet days (R95p and R99p), maximum one-day precipitation (Rx1day), and simple daily intensity (SDII) with a pronounced wet bias in HR models for R95p and R99p. Most HR models outperform their LR counterparts in simulating R95p, R99p, and SDII. Our results indicate that enhanced horizontal resolution under CMIP6 HighResMIP results in either improvements (e.g., increased SCC) or deterioration (e.g., decreased SCC), depending on precipitation extremes, river basin, and model. The findings of this study are important for both climate scientists and policymakers.

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How well do the CMIP6 HighResMIP models simulate precipitation over the Tibetan Plateau?

Cited by 12 publications

References 50 publications

Decadal variability of precipitation over the Tibetan Plateau modulated by the 11-year solar cycle over the past millennium

Decadal variability of precipitation over the Tibetan Plateau modulated by the 11-year solar cycle over the past millennium

Precipitation variability related to atmospheric circulation patterns over the Tibetan Plateau

Exploring the Influence of Improved Horizontal Resolution on Extreme Precipitation in Southern Africa Major River Basins: Insights from CMIP6 HighResMIP Simulations

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