Evaluating vector winds in the Asian-Australian monsoon region simulated by 37 CMIP5 models

Huang, Fanyang; Xu, Zhongfeng; Guo, Weidong

doi:10.1007/s00382-018-4599-z

Cited by 25 publications

(20 citation statements)

References 45 publications

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“…Agreement of other simulated components of the global monsoon domain with observations is generally strong, and CESM is among the best coupled climate models in reproducing the monsoons (e.g. Huang et al, , Figure ). In this work, various components of the global monsoon are examined including the entirety of the region in Figure , the global monsoon (GM), and its NH (NHM) and SH (SHM) subdomains.…”

Section: Cesm Simulation Of the Global Monsoonmentioning

confidence: 98%

The Influence of Volcanic Aerosol Meridional Structure on Monsoon Responses over the Last Millennium

Fasullo

Otto‐Bliesner

Stevenson

2019

Geophysical Research Letters

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Monsoon responses to eruptions over the last millennium (LM) are examined in an ensemble of climate simulations as a function of eruption hemisphere. A composite analysis reveals a particularly strong sensitivity of monsoon rainfall in the year following Northern Hemisphere (NH) extratropical eruptions. Additional analysis focusing on the 18th century eruption of Mt. Laki and idealized simulations representing an analogue Southern Hemisphere eruption (SH‐Laki) reveal monsoon responses that are approximately symmetric across hemispheres, despite exhibiting asymmetries in other aspects of the climate response. We conclude that 1) latitudinally mirrored eruptions result in approximately symmetric monsoon responses, 2) disproportionate weakening (strengthening) of NH (SH) monsoons by NH eruptions over the LM resulted in part from their relatively high latitudes, and 3) uncertainty in eruption latitude fundamentally limits our ability to accurately simulate associated monsoon and tropical precipitation responses in nature.

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Section: Cesm Simulation Of the Global Monsoonmentioning

confidence: 98%

The Influence of Volcanic Aerosol Meridional Structure on Monsoon Responses over the Last Millennium

Fasullo

Otto‐Bliesner

Stevenson

2019

Geophysical Research Letters

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“…These information are very important for us to understand the model biases. The Taylor diagram can also be generalized as a vector field evaluation (VFE) diagram, which can quantitatively evaluate model performance in simulating vector fields, for example, vector winds (Xu et al, 2016;Huang et al, 2019). A single index or model skill score is certainly necessary to measure model performance but it loses the detail information on model performance.…”

Section: Discussionmentioning

confidence: 99%

Short communication comments on ‘DISO: A rethink of Taylor diagram’

Han

2019

Intl Journal of Climatology

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In a recent article, Hu et al. (2019) argued that the commonly used Taylor diagram in climate model evaluation only considered centred statistics, while the absolute error (AE) was not considered. Therefore, they proposed a new index, termed Distance between Indices of Simulation and Observation (DISO), that takes AE, correlation coefficient, and uncentred RMSE into account to comprehensively measure climate model performance. Note that the widely used uncentred RMSE is a function of the AE and correlation coefficient. Therefore, it is not necessary to combine AE and correlation coefficient with the uncentred RMSE again to define DISO. In addition, model performance does not improve monotonically with the decrease in the DISO index, which is also a flaw of the index. Indeed, the Taylor diagram was constructed based on the cosine law between three‐centred statistics that cannot measure the mean error of the climate model. However, this limitation can be mitigated by showing the mean error or percent bias on the diagram or constructing the Taylor diagram with uncentred statistics. The uncentred statistics still satisfy the cosine law and can also be illustrated in the Taylor diagram. In our viewpoint, there is nothing wrong with the Taylor diagram. On the contrary, the Taylor diagram can effectively visualize multiple statistics and compare the performance of different climate models.

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“…In order to assess the overall simulation capability for TC environmental fields, suggested that high-resolution models generally perform better in simulating the wind vector field in the Asian-Australian monsoon region (Huang et al, 2019). Of course, the above relationship is not always valid.…”

Section: Evaluation Of the Performance Of Cmip6 Models In Five Ocean Regionsmentioning

confidence: 99%

Assessing the performance of 33 CMIP6 models in simulating the large-scale environmental fields of tropical cyclones

Han

Zhang

et al. 2021

Preprint

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General circulation model (GCM) biases are one of the important sources of biases and uncertainty in dynamic downscaling–based simulations. The ability of regional climate models to simulate tropical cyclones (TCs) is strongly affected by the ability of GCMs to simulate the large-scale environmental field. Thus, in this work, we employ a recently developed multivariable integrated evaluation method to assess the performance of 33 CMIP6 (phase 6 of the Coupled Model Intercomparison Project) models in simulating multiple fields. The CMIP6 models are quantitatively evaluated against two reanalysis datasets over five ocean areas. The results show that most of the CMIP6 models overestimate the mid-level humidity in almost all tropical oceans. The multi-model ensemble mean overestimates the vertical shear of the horizontal winds in the Northeast Pacific and North Atlantic. An increase in model horizontal resolution appears to be helpful in improving the model simulations. For example, there are 6–8 models with higher resolution among the top 10 models in terms of overall model performance in simulating the climatology and interannual variability of multiple variables. Similarly, there are 7–8 models with lower resolution among the bottom 10 patterns. The model skill varies depending on the region and variable being evaluated. Although no model performs best in all regions and for all variables, some models do show relatively good capability in simulating the large-scale environmental field of TCs. For example, the MPI-ESM1-2-LR, MPI-ESM1-2-HR, and FIO-ESM-2-0 models show relatively good skill in simulating the climatology and interannual variability of the large-scale environmental field in the Northern and Southern Hemispheres.

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Evaluating vector winds in the Asian-Australian monsoon region simulated by 37 CMIP5 models

Cited by 25 publications

References 45 publications

The Influence of Volcanic Aerosol Meridional Structure on Monsoon Responses over the Last Millennium

The Influence of Volcanic Aerosol Meridional Structure on Monsoon Responses over the Last Millennium

Short communication comments on ‘DISO: A rethink of Taylor diagram’

Assessing the performance of 33 CMIP6 models in simulating the large-scale environmental fields of tropical cyclones

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