Open AccessJournal Article
A gridded daily observation dataset over China region and comparison with the other datasets
TLDR
In this paper, a new gridded daily dataset with the resolution of 0.25°latitude by 0.75°longitude, CN05.1, is constructed for the purpose of high resolution climate model validation over China region.Abstract:
A new gridded daily dataset with the resolution of 0.25°latitude by 0.25°longitude,CN05.1,is constructed for the purpose of high resolution climate model validation over China region.The dataset is based on the interpolation from over 2400observing stations in China,includes 4variables : daily mean,minimum and maximum temperature,daily precipitation.The " anomaly approach " is applied in this interpolation.The climatology is first interpolated by thinplate smoothing splines and then a gridded daily anomaly derived from angular distance weighting method is added to climatology to obtain the final dataset.Intercomparison of the dataset with other three daily datasets,CN05for temperature,and EA05and APHRO for precipitation is conducted.The analysis period is from 1961to 2005.For multi-annual mean temperature variables,results show small differences over eastern China with dense observation stations,but larger differences(warmer) over western China with less stations between CN05.1and CN05.The temperature extremes are measured by TX3D(mean of the 3greatest maximum temperatures in a year) and TN3D(mean of the 3lowest minimum temperatures).CN05.1in general shows a warmer TX3Dover China,while a lower TN3Din the east and greater TN3Din the west are found compared to CN05.A greater value of annual mean precipitation compared to EA05and APHRO,especially to the latter,is found in CN05.1.For precipitation extreme of R3D(mean of the 3largest precipitations in a year),CN05.1presents lower value of it in western China compared to EA05.read more
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Thermal regime variations of the uppermost soil layer in the central Tibetan Plateau
TL;DR: In this paper , the authors analyzed the long-term changes in the thermal regime of the uppermost soil layer at six sites in the central Tibetan Plateau (TP), and concluded that partial correlation analysis was used to quantify the influences of factors (including surface air temperature, snow depth, rainfall, normalised difference vegetation index [NDVI], shortwave radiation, and soil moisture) on soil temperature.
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Association between the Rail Breakage Frequency in Beijing–Tianjin–Hebei High-Speed Railway and the Eurasian Atmospheric Circulation Anomaly
TL;DR: In this paper , the authors analyzed the spatiotemporal variations in the frequency of rail breakage in the high-speed railway of the Beijing-Tianjin-Hebei (BTH) region and its relationship with atmospheric circulation anomalies and surface temperature.
Journal ArticleDOI
Changes in Runoff in the Source Region of the Yellow River Basin Based on CMIP6 Data under the Goal of Carbon Neutrality
Abstract: China is committed to achieving carbon neutrality before 2060. This study projected the changes in climate and runoff in the source region of the Yellow River Basin for 2021–2060 under lower carbon emission pathways (SSP1–2.6 and SSP2–4.5) using a statistically downscaled climate dataset and the SWAT hydrological model. Results showed that the climate will become warmer and wetter from 2021–2060. In comparison with the baseline period (1995–2014), in terms of the ensemble mean, annual mean air temperature, annual precipitation, and annual runoff will increase by 1.3 °C and 1.6 °C, by 11.1% and 11.2%, and by 12.8% and 11.9% under SSP1–2.6 and SSP2–4.5 scenarios, respectively. Moreover, the seasonal pattern of runoff was projected to change. The proportion of monthly runoff to the annual total will decrease by 0.6–1.0% in summer but increase by 0.1–1.0% during the period from January to April and September to December. The multimodel ensemble mean (MEM) of extremely high monthly flow (Q10) will increase by 3.5–13.4% in the flood season (June to August) and water storage season (September to December). The MEM of extremely low monthly flow (Q90) will increase by 19.4–26.2% from February to April but decrease by 5.0–8.9% in January, May, and December. Thus, the warmer and wetter climate from 2021–2060 will likely cause flatter seasonal distribution of runoff, lower risk of water scarcity at the annual scale and of drought from February to April, but higher risk both of flood in the flood season and of drought in December, January, and May. Generally, the flatter pattern of runoff would likely alleviate water scarcity in the dry and water storage seasons to some degree, and the increase in monthly runoff in the water storage season will benefit hydroelectric power generation and agriculture and animal husbandry production. However, in some years, the increase in Q10 in the flood season will likely increase flood prevention pressure, and the decrease in Q90 in May will likely obstruct grass revival.
Journal ArticleDOI
Physical–empirical prediction model for the dominant mode of extreme high temperature events in eastern China during summer
TL;DR: Based on the mechanisms related to the dominant mode, a physical-empirical model was established that improved the prediction of extreme high temperature events in eastern China, which will help in disaster prediction and mitigation as discussed by the authors .
Journal ArticleDOI
Change in extreme precipitation events: Exposure and vulnerability in the Poyang Lake Basin, China
TL;DR: In this article , the authors analyzed the spatiotemporal characteristics of extreme precipitation events in the Poyang Lake Basin (China) using the intensity-area-duration method.
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