Xiaona Chen

Dr. Xiaona Chen

orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 November 2015 in Scientific Reports
Verified
Journal Article
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Xiaona ChenXiaona Chen
Xiaona Chen
SLShunlin Liang
Shunlin Liang
YCYunfeng Cao
Yunfeng Cao
Tao HeTao He
Tao He
DWDongdong Wang
Dongdong Wang
Quantifying and attributing the phenological changes in snow cover are essential for meteorological, hydrological, ecological and societal implications. However, snow cover phenology changes have not been well documented. Evidence from multiple satellite and reanalysis data from 2001 to 2014 points out that the snow end date (De) advanced by 5.11 (±2.20) days in northern high latitudes (52–75°N) and was delayed by 3.28 (±2.59) days in northern mid-latitudes (32–52°N) at the 90% confidence level. Dominated by changes in De, snow duration days (Dd) was shorter in duration by 5.57 (±2.55) days in high latitudes and longer by 9.74 (±2.58) days in mid-latitudes. Changes in De during the spring season were consistent with the spatiotemporal pattern of land surface albedo change. Decreased land surface temperature combined with increased precipitation in mid-latitudes and significantly increased land surface temperature in high latitudes, impacted by recent Pacific surface cooling, Arctic amplification and strengthening westerlies, result in contrasting changes in the Northern Hemisphere snow cover phenology. Changes in the snow cover phenology led to contrasting anomalies of snow radiative forcing, which is dominated by De and accounts for 51% of the total shortwave flux anomalies at the top of the atmosphere.

15 August 2022 in Remote Sensing
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Journal Article
Open access
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XYXu Yang
Xu Yang
YYYaping Yang
Yaping Yang
Xiaona ChenXiaona Chen
Xiaona Chen
Yangxiaoyue LiuYangxiaoyue Liu
Yangxiaoyue Liu
As one of the earliest remote sensing indices, the Normalized Difference Vegetation Index (NDVI) has been employed extensively for vegetation research. However, despite an abundance of NDVI review articles, these studies are predominantly limited to either one subject area or one area, with systematic NDVI reviews being relatively rare. Bibliometrics is a useful method of analyzing scientific literature that has been widely used in many disciplines; however, it has not yet been applied to comprehensively analyze NDVI research. Therefore, we used bibliometrics and scientific mapping methods to analyze citation data retrieved from the Web of Science during 1985–2021 with NDVI as the topic. According to the analysis results, the amount of NDVI research increased exponentially during the study period, and the related research fields became increasingly varied. Moreover, a greater number of satellite and aerial remote sensing platforms resulted in more diverse NDVI data sources. In future, machine learning methods and cloud computing platforms led by Google Earth Engine will substantially improve the accuracy and production efficiency of NDVI data products for more effective global research.

1 September 2018 in Remote Sensing of Environment
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Journal Article
Closed access
Xiaona ChenXiaona Chen
Xiaona Chen
DLDi Long
Di Long
SLShunlin Liang
Shunlin Liang
LHLian He
Lian He
CZChao Zeng
Chao Zeng
YHYang Hong
Yang Hong

16 August 2017 in Scientific Reports
Verified
Journal Article
Open access
PDF file
YCYunfeng Cao
Yunfeng Cao
SLShunlin Liang
Shunlin Liang
Xiaona ChenXiaona Chen
Xiaona Chen
Tao HeTao He
Tao He
DWDongdong Wang
Dongdong Wang
XCXiao Cheng
Xiao Cheng
The speeds of both Arctic surface warming and sea-ice shrinking have accelerated over recent decades. However, the causes of this unprecedented phenomenon remain unclear and are subjects of considerable debate. In this study, we report strong observational evidence, for the first time from long-term (1984–2014) spatially complete satellite records, that increased cloudiness and atmospheric water vapor in winter and spring have caused an extraordinary downward longwave radiative flux to the ice surface, which may then amplify the Arctic wintertime ice-surface warming. In addition, we also provide observed evidence that it is quite likely the enhancement of the wintertime greenhouse effect caused by water vapor and cloudiness has advanced the time of onset of ice melting in mid-May through inhibiting sea-ice refreezing in the winter and accelerating the pre-melting process in the spring, and in turn triggered the positive sea-ice albedo feedback process and accelerated the sea ice melting in the summer.


1 February 2015 in Journal of Climate
Verified
Journal Article
Open access
YCYunfeng Cao
Yunfeng Cao
SLShunlin Liang
Shunlin Liang
Xiaona ChenXiaona Chen
Xiaona Chen
Tao HeTao He
Tao He
The decreasing surface albedo caused by continuously retreating sea ice over Arctic plays a critical role in Arctic warming amplification. However, the quantification of the change in radiative forcing at top of atmosphere (TOA) introduced by the decreasing sea ice albedo and its feedback to the climate remain uncertain. In this study, based on the satellite-retrieved long-term surface albedo product CLARA-A1 (Cloud, Albedo, and Radiation dataset, AVHRR-based, version 1) and the radiative kernel method, an estimated 0.20 ± 0.05 W m−2 sea ice radiative forcing (SIRF) has decreased in the Northern Hemisphere (NH) owing to the loss of sea ice from 1982 to 2009, yielding a sea ice albedo feedback (SIAF) of 0.25 W m−2 K−1 for the NH and 0.19 W m−2 K−1 for the entire globe. These results are lower than the estimate from another method directly using the Clouds and the Earth’s Radiant Energy System (CERES) broadband planetary albedo. Further data analysis indicates that kernel method is likely to underestimate the change in all-sky SIRF because all-sky radiative kernels mask too much of the effect of sea ice albedo on the variation of cloudy albedo. By applying an adjustment with CERES-based estimate, the change in all-sky SIRF over the NH was corrected to 0.33 ± 0.09 W m−2, corresponding to a SIAF of 0.43 W m−2 K−1 for NH and 0.31 W m−2 K−1 for the entire globe. It is also determined that relative to satellite surface albedo product, two popular reanalysis products, ERA-Interim and MERRA, severely underestimate the changes in NH SIRF in melt season (May–August) from 1982 to 2009 and the sea ice albedo feedback to warming climate.