2023
DOI: 10.3390/ijerph20064961
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Future Projection of Extreme Precipitation Indices over the Qilian Mountains under Global Warming

Abstract: The Qilian Mountains are a climate-sensitive area in northwest China, and extreme precipitation events have an important impact on its ecological environment. Therefore, considering the global warming scenario, it is highly important to project the extreme precipitation indices over the Qilian Mountains in the future. This study is based on three CMIP6 models (CESM2, EC-Earth3, and KACE-1-0-G). A bias correction algorithm (QDM) was used to correct the precipitation outputs of the models. The eight extreme prec… Show more

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Cited by 4 publications
(5 citation statements)
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“…Another possible factor for the wet bias was the sparse distribution of stations in the QMs. Most of these stations are located in the valleys of the QMs, and there are elevation errors between them and the grid points of the model, which may lead to an underestimation of precipitation [50]. Especially in the western region, precipitation decreases gradually with increasing altitude, and the whole layer of atmospheric water vapor is mainly concentrated below 5000 m.…”
Section: Cmip6 Model Performancementioning
confidence: 99%
See 4 more Smart Citations
“…Another possible factor for the wet bias was the sparse distribution of stations in the QMs. Most of these stations are located in the valleys of the QMs, and there are elevation errors between them and the grid points of the model, which may lead to an underestimation of precipitation [50]. Especially in the western region, precipitation decreases gradually with increasing altitude, and the whole layer of atmospheric water vapor is mainly concentrated below 5000 m.…”
Section: Cmip6 Model Performancementioning
confidence: 99%
“…Another possible factor for the wet bias was the sparse distribution of stations in the QMs. Most of these stations are located in the valleys of the QMs, and there are elevation errors between them and the grid points of the model, which may lead to an underestimation of precipitation [50]. Especially in the western region, precipitation decreases gradually with increasing altitude, and the whole layer of atmospheric water vapor is mainly concentrated below 5000 m. From the data we have analyzed, we found that (Figure 4) MME simulated the spatial distribution characteristics of decreasing precipitation from the southeast to northwest QM, which is in agreement with Qiang Fang's research [51].…”
Section: Cmip6 Model Performancementioning
confidence: 99%
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