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The past and future of global river ice 期刊论文
NATURE, 2020, 577 (7788) : 69-+
作者:  Yang, Xiao;  Pavelsky, Tamlin M.;  Allen, George H.
收藏  |  浏览/下载：42/0  |  提交时间：2020/05/13

More than one-third of Earth'  s landmass is drained by rivers that seasonally freeze over. Ice transforms the hydrologic(1,2), ecologic(3,4), climatic(5) and socio-economic(6-8) functions of river corridors. Although river ice extent has been shown to be declining in many regions of the world(1), the seasonality, historical change and predicted future changes in river ice extent and duration have not yet been quantified globally. Previous studies of river ice, which suggested that declines in extent and duration could be attributed to warming temperatures(9,10), were based on data from sparse locations. Furthermore, existing projections of future ice extent are based solely on the location of the 0-degrees C isotherm11. Here, using satellite observations, we show that the global extent of river ice is declining, and we project a mean decrease in seasonal ice duration of 6.10 +/- 0.08 days per 1-degrees C increase in global mean surface air temperature. We tracked the extent of river ice using over 400,000 clear-sky Landsat images spanning 1984-2018 and observed a mean decline of 2.5 percentage points globally in the past three decades. To project future changes in river ice extent, we developed an observationally calibrated and validated model, based on temperature and season, which reduced the mean bias by 87 per cent compared with the 0-degree-Celsius isotherm approach. We applied this model to future climate projections for 2080-2100: compared with 2009-2029, the average river ice duration declines by 16.7 days under Representative Concentration Pathway (RCP) 8.5, whereas under RCP 4.5 it declines on average by 7.3 days. Our results show that, globally, river ice is measurably declining and will continue to decline linearly with projected increases in surface air temperature towards the end of this century.


  
Estimation of Surface Soil Moisture With Downscaled Land Surface Temperatures Using a Data Fusion Approach for Heterogeneous Agricultural Land 期刊论文
WATER RESOURCES RESEARCH, 2019, 55 (2) : 1105-1128
作者:  Bai, Liangliang;  Long, Di;  Yan, La
收藏  |  浏览/下载：12/0  |  提交时间：2019/11/26
land surface temperature  surface soil moisture  data fusion  Landsat  MODIS  heterogeneous agricultural lands  
A Practical Single-Channel Algorithm for Land Surface Temperature Retrieval: Application to Landsat Series Data 期刊论文
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2019, 124 (1) : 299-316
作者:  Wang, Mengmeng;  Zhang, Zhengjia;  Hu, Tian;  Liu, Xiuguo
收藏  |  浏览/下载：19/0  |  提交时间：2019/04/09
land surface temperature  Landsat series data  single-channel algorithm  Planck'  s function  atmospheric correction  
Evaluating the influence of spatial resolution of Landsat predictors on the accuracy of biomass models for large-area estimation across the eastern USA 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2018, 13 (5)
作者:  Deo, Ram K.;  Domke, Grant M.;  Russell, Matthew B.;  Woodall, Christopher W.;  Andersen, Hans-Erik
收藏  |  浏览/下载：21/0  |  提交时间：2019/04/09
above-ground forest biomass  large-area estimation  Landsat data  spatial resolution of predictors  LiDAR  design-based estimates