Evaluation and Projection of Near-Surface Wind Speed over China Based on CMIP6 Models

Deng, Hao; Hua, Wei; Fan, Guangzhou

doi:10.3390/atmos12081062

Cited by 19 publications

(7 citation statements)

References 23 publications

(38 reference statements)

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“…In contrast, the SSP245, and especially the “green path” of SSP126, project an SWS decline until ∼2070 followed by an interruption of the slowdown until the end of the century. These results are in agreement with previous studies over the Northern Hemisphere regions 16,46 . To summarize, the higher the greenhouse gas emission scenarios, the higher the projected stilling for the 21st century.…”

Section: Discussionsupporting

confidence: 93%

“…These results are in agreement with previous studies over the Northern Hemisphere regions. 16,46 To summarize, the higher the greenhouse gas emission scenarios, the higher the projected stilling for the 21st century. In contrast, positive SWS trends are predicted for mid-(2036-2061) and end-(2071-2100) of the century for the WRF-CESM2 under SSP585, the highest external forcing scenario.…”

Section: Discrepancies Between the Gcms And Rcms And Observationsmentioning

confidence: 99%

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Uncertainty in surface wind speed projections over the Iberian Peninsula: CMIP6 GCMs versus a WRF‐RCM

Andres‐Martin,

Azorin‐Molina,

Shen

et al. 2023

Annals of the New York Academy of Sciences

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This study assessed the projected near‐surface wind speed (SWS) changes and variability over the Iberian Peninsula for the 21st century. Here, we compared Coupled Model Intercomparison Project Phase 6 global climate models (GCMs) with a higher spatial resolution regional climate model (RCM; ∼20 km), known as WRF‐CESM2, which was created by a dynamic downscaling of the Community Earth System Model version 2 (CESM2) using the Weather Research and Forecasting (WRF) model. Our analysis found that the GCMs tended to overestimate observed SWS for 1985–2014, while the higher spatial resolution of the WRF‐CESM2 did not improve the accuracy and underestimated the SWS magnitude. GCMs project a decline of SWS under high shared socioeconomic pathways (SSPs) greenhouse concentrations, such as SSP370 and SSP585, while an interdecadal oscillation appears in SSP126 and SSP245 for the end of the century. The WRF‐CESM2 under SSP585 predicts the opposite increasing SWS. Our results suggest that 21st‐century projections of SWS are uncertain even for regionalized products and should be taken with caution.

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Section: Discussionsupporting

confidence: 93%

Section: Discrepancies Between the Gcms And Rcms And Observationsmentioning

confidence: 99%

Uncertainty in surface wind speed projections over the Iberian Peninsula: CMIP6 GCMs versus a WRF‐RCM

Andres‐Martin,

Azorin‐Molina,

Shen

et al. 2023

Annals of the New York Academy of Sciences

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“…The interannual variability skill (IVS) score was used to evaluate the interannual variability in the simulations relative to the observations [60,61]. The formula was as follows:…”

Section: Methodology 231 Model Evaluation Metricsmentioning

confidence: 99%

Projected Changes in Precipitation Based on the CMIP6 Optimal Multi-Model Ensemble in the Pearl River Basin, China

He,

Chen,

Sun

et al. 2023

Remote Sensing

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Precipitation fluctuations in the Pearl River Basin (PRB) have a significant impact on river runoff, causing huge economic losses and casualties. However, future precipitation variations in the PRB remain unclear. Therefore, we explored the projected changes in precipitation in the PRB based on the coupled model intercomparison project phase 6 (CMIP6) model via three shared socio-economic pathways scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). In our study, the optimal ensemble of global climate models in the PRB was identified using the comprehensive rating index (CRI), which is based on climatology, spatial variation, and interannual variability, and it was used to analyze potential precipitation changes in the basin in the period 2025–2100. The results showed that the CMIP6 models underestimated precipitation in the PRB; the consistency between the observations and the multi-model ensemble mean of the four best models was higher than those of any other ensembles, and the CRI value was highest (0.92). The annual precipitation in the PRB shows a significant increasing trend under three scenarios from 2025 to 2100 (p < 0.01), with the highest rate of precipitation increase being seen under the high-emission scenario. By the end of the 21st century, the regional mean precipitation in the PRB will increase by 13%, 9.4%, and 20.1% under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios, respectively. Spatially, the entire basin is projected to become wetter, except for a slight decrease of less than 6% in the central part of the basin and the Pearl River Delta in the near term in the 21st century, and the highest increases are projected to occur in the Xijiang River basin.

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“…Surface wind speed is an important indicator of wind energy resources (Feng et al, 2019) and has a significant effect on the hydrological cycle and wind‐related natural disasters, for example, dust and sand storms, tornadoes and typhoons (Deng et al, 2021; Wang et al, 2009; Xu et al, 2020). Studies of surface wind speeds can be used for energy conservation, emission reductions, understanding climate change and reduction of property losses due to natural disasters.…”

Section: Introductionmentioning

confidence: 99%

Regime shift of the leading mode of winter surface wind speed in northwest China in 2003/04 and its possible link with Barents–Kara sea ice

Wang,

Zhou,

Liu

et al. 2024

Intl Journal of Climatology

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Using the ERA‐5 reanalysis datasets, NCEP/NCAR sea ice concentration (SIC) and observed winter surface wind speed (WSWS) in northwest China during 1979–2020, this study examined the regime shift of the leading mode of observed WSWS in northwest China and investigated its possible link with the winter Barents–Kara Sea (BKS) SIC. The leading mode of observed WSWS in northwest China showed negative anomalies in southern and northeastern Xinjiang, Gansu, western and northern Shaanxi Provinces, and positive anomalies in northwestern and middle Xinjiang, Qinghai and Ningxia Provinces. The signs of WSWS in the leading mode is generally opposite to their trends during 1979–2020. Leading principal component (PC1) of observed WSWS in northwest China underwent an obvious decreasing regime shift in 2003/04, as well as the winter BKS SIC. There are significant correlations between PC1 and BKS SIC on both interdecadal and interannual timescales. Decadal decrease of BKS SIC is accompanied with a positive phase of Scandinavia pattern (SP) with positive anomalies of 500‐hPa geopotential height over subtropical North Atlantic, Arctic‐Ural region and southern Asia, and negative anomalies over northern North Atlantic‐West Europe and Siberia regions. BKS SIC and SP significantly influenced the Northern China Wind Index (NCWI) at 200 hPa on interdecadal timescale, which was related to the PC1 on both interdecadal and interannual timescales after removing the signal of Arctic Oscillation. Meridional configuration of Siberian cyclonic anomaly and southern Asian anticyclonic anomaly associated with the winter BKS SIC could enhance the intensity of NCWI, which favoured the increase of observed WSWS in northwest China and thereby may contribute to the regime shift in 2003/04 of the leading mode. However, there were still some stations showing decreasing regime shift, which mainly located at the region of steeping terrain. These decreasing changes of WSWS may be related to circumfluence effect of terrain, urbanization and local microclimate, and these reasons still need further detailed study.

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Evaluation and Projection of Near-Surface Wind Speed over China Based on CMIP6 Models

Cited by 19 publications

References 23 publications

Uncertainty in surface wind speed projections over the Iberian Peninsula: CMIP6 GCMs versus a WRF‐RCM

Uncertainty in surface wind speed projections over the Iberian Peninsula: CMIP6 GCMs versus a WRF‐RCM

Projected Changes in Precipitation Based on the CMIP6 Optimal Multi-Model Ensemble in the Pearl River Basin, China

Regime shift of the leading mode of winter surface wind speed in northwest China in 2003/04 and its possible link with Barents–Kara sea ice

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