Trend and Abrupt Regime Shift of Temperature Extreme in Northeast China, 1957–2015

Mwagona, Patteson Chula; Yao, Yunlong; Shan, Yuanqi; Hou, Yu; Zhang, Yiwen

doi:10.1155/2018/2315372

Cited by 11 publications

(8 citation statements)

References 41 publications

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“…On the whole, the wetland loss rate would be 0.9 and 7.4% under RCP 2.6 for the 2050s and 2070s and would be 6.3 and 23.8% under RCP 8.5 for the 2050s and 2070s, respectively. Recent studies have shown that the Xing'anling Mountains have been stalled in a climate warming stage from 1957 to 2015, the annual average temperature in this period was approximately −3.22°C (Mwagona, Yao, Shan, Yu, & Zhang, 2018; Zhao et al, 2016). More seriously, this climate warming trend in the Xing'anling Mountains is predicted to continue and even accelerate during the 21st century (Hjort et al, 2018; Sun, Miao, & Duan, 2015).…”

Section: Discussionmentioning

confidence: 99%

Simulating potential impacts of climate changes on distribution pattern and carbon storage function of high‐latitude wetland plant communities in the Xing'anling Mountains, China

et al. 2021

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Though one of the most vulnerable terrestrial ecosystems, wetlands provide multiple ecosystem services, most notably storing carbon. It is now widely recognized that climate change could have a large impact on high-latitude wetlands. A key question is how climate change will affect the distribution pattern of wetland plant communities, and to what extent the transitions among different wetland plant communities respond to regional warming? To answer this question, we estimated the total SOC storage with 139 soil profiles in the Xing'anling Mountains and performed ensemble species distribution modelling for 11 dominant wetland plant communities by using numerous vegetation plots. Results show that 4.5-23.8% of the high-latitude wetlands in the study area would be lost following widespread thawing of permafrost under different climate warming scenarios by the end of this century. The total wetland SOC in the Xing'anling Mountains is estimated to be 1.58 Pg, about 25.5-29.3% of the total of China's wetlands, however, predicted wetland loss could put 5.4-20.5% (0.08-0.32 Pg C) of the total SOC storage at risk of instability. Our results also predicted a significant northward migration of southern Deyeuxia angustifolia communities driven by future climate changes. This wetland succession could profoundly reduce future carbon sequestration capacity of wetlands in the study area. The findings presented here are helpful for both current reserve management and future conservation planning of wetlands in the study area.

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Section: Discussionmentioning

confidence: 99%

Simulating potential impacts of climate changes on distribution pattern and carbon storage function of high‐latitude wetland plant communities in the Xing'anling Mountains, China

et al. 2021

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“…Donat et al, 2013). Mwagona et al (2018) observed changes in cold/warm night frequency at 116 stations in northeastern China. They report a decrease in cold night frequency during winter and spring, while warm night frequency increased primarily in summer.…”

Section: Frequencymentioning

confidence: 99%

“…Matthews et al, 2016b) in a given period. The number of events can be estimated using tracking algorithms, ranging from simple algorithms based on the mean sea level pressure values for cyclone activity (Murray and Simmonds, 1991;Donat et al, 2011) and the exceedance over the 98th percentile wind speeds for wind storms (Leckebusch et al, 2008) to the more complex tracking of sting jets (Hart et al, 2017). The frequency of extreme winds may be quantified from reanalysis data, noting that the trend magnitude and sign can be sensitive to the reanalysis product (Befort et al, 2016;Wohland et al, 2019;Torralba et al, 2017).…”

Section: Frequencymentioning

confidence: 99%

Nonstationary weather and water extremes: a review of methods for their detection, attribution, and management

Slater

Anderson

Buechel

et al. 2021

Hydrol. Earth Syst. Sci.

155

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Abstract. Hydroclimatic extremes such as intense rainfall, floods, droughts, heatwaves, and wind or storms have devastating effects each year. One of the key challenges for society is understanding how these extremes are evolving and likely to unfold beyond their historical distributions under the influence of multiple drivers such as changes in climate, land cover, and other human factors. Methods for analysing hydroclimatic extremes have advanced considerably in recent decades. Here we provide a review of the drivers, metrics, and methods for the detection, attribution, management, and projection of nonstationary hydroclimatic extremes. We discuss issues and uncertainty associated with these approaches (e.g. arising from insufficient record length, spurious nonstationarities, or incomplete representation of nonstationary sources in modelling frameworks), examine empirical and simulation-based frameworks for analysis of nonstationary extremes, and identify gaps for future research.

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“…Many scholars have studied the variation of temperature in northeast China. Mwagona et al [21] found that T min increased at a faster rate than T max , leading to the decrease of DTR in northeast China. Shen et al [22] obtained similar results using data from meteorological stations.…”

Section: Introductionmentioning

confidence: 99%

Elevation-Dependent Trend in Diurnal Temperature Range in the Northeast China during 1961–2015

2021

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The diurnal temperature range (DTR) is considered a signature of observed climate change, which is defined as the difference between the maximum (Tmax) and minimum temperatures (Tmin). It is well known that the warming rate of mean temperature is larger at high elevations than at low elevations in northeast China. However, it is still uncertain whether DTR trend is greater at high elevations. This study examined the spatiotemporal variation in DTR and its relationship with elevation in northeast China based on data from 68 meteorological stations from 1961 to 2015. The results show that there was a significant declining trend (0.252 °C/decade) in DTR from 1961 to 2015 due to the fact that Tmin increased at a faster rate than Tmax. Seasonally, DTR in northeast China showed a decreasing trend with the largest decrease rate in spring (−0.3167 °C/decade) and the smallest decrease rate in summer (−0.1725 °C/decade). The results of correlation analysis show that there was a significant positive correlation between the annual DTR trend and elevation in northeast China. This is due to the fact that increasing elevation has a significant warming effect on Tmax. Seasonally, there were significant positive correlations between the DTR trend and elevation in all seasons. The elevation gradient of DTR trend was the greatest in winter (0.392 °C/decade/km) and the lowest in autumn (0.209 °C/decade/km). In spring, summer, and autumn, increasing elevation has a significant warming effect on Tmax, leading to a significant increase of the DTR trend with increasing elevation. However, in winter, increasing elevation has a significant cooling effect on Tmin, resulting in a significant increase of the DTR trend with increasing elevation.

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Trend and Abrupt Regime Shift of Temperature Extreme in Northeast China, 1957–2015

Cited by 11 publications

References 41 publications

Simulating potential impacts of climate changes on distribution pattern and carbon storage function of high‐latitude wetland plant communities in the Xing'anling Mountains, China

Simulating potential impacts of climate changes on distribution pattern and carbon storage function of high‐latitude wetland plant communities in the Xing'anling Mountains, China

Nonstationary weather and water extremes: a review of methods for their detection, attribution, and management

Elevation-Dependent Trend in Diurnal Temperature Range in the Northeast China during 1961–2015

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