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Patterns and trends of Northern Hemisphere snow mass from 1980 to 2018 期刊论文
NATURE, 2020, 581 (7808) : 294-+
作者:  Ibrahim, Nizar;  Maganuco, Simone;  Dal Sasso, Cristiano;  Fabbri, Matteo;  Auditore, Marco;  Bindellini, Gabriele;  Martill, David M.;  Zouhri, Samir;  Mattarelli, Diego A.;  Unwin, David M.;  Wiemann, Jasmina;  Bonadonna, Davide;  Amane, Ayoub;  Jakubczak, Juliana;  Joger, Ulrich;  Lauder, George V.;  Pierce, Stephanie E.
收藏  |  浏览/下载:37/0  |  提交时间:2020/05/25

Warming surface temperatures have driven a substantial reduction in the extent and duration of Northern Hemisphere snow cover(1-3). These changes in snow cover affect Earth'  s climate system via the surface energy budget, and influence freshwater resources across a large proportion of the Northern Hemisphere(4-6). In contrast to snow extent, reliable quantitative knowledge on seasonal snow mass and its trend is lacking(7-9). Here we use the new GlobSnow 3.0 dataset to show that the 1980-2018 annual maximum snow mass in the Northern Hemisphere was, on average, 3,062 +/- 35 billion tonnes (gigatonnes). Our quantification is for March (the month that most closely corresponds to peak snow mass), covers non-alpine regions above 40 degrees N and, crucially, includes a bias correction based on in-field snow observations. We compare our GlobSnow 3.0 estimates with three independent estimates of snow mass, each with and without the bias correction. Across the four datasets, the bias correction decreased the range from 2,433-3,380 gigatonnes (mean 2,867) to 2,846-3,062 gigatonnes (mean 2,938)-a reduction in uncertainty from 33% to 7.4%. On the basis of our bias-corrected GlobSnow 3.0 estimates, we find different continental trends over the 39-year satellite record. For example, snow mass decreased by 46 gigatonnes per decade across North America but had a negligible trend across Eurasia  both continents exhibit high regional variability. Our results enable a better estimation of the role of seasonal snow mass in Earth'  s energy, water and carbon budgets.


Applying a bias correction to a state-of-the-art dataset covering non-alpine regions of the Northern Hemisphere and to three other datasets yields a more constrained quantification of snow mass in March from 1980 to 2018.


  
Spin squeezing of 10(11) atoms by prediction and retrodiction measurements 期刊论文
NATURE, 2020, 581 (7807) : 159-+
作者:  Lan, Jun;  Ge, Jiwan;  Yu, Jinfang;  Shan, Sisi;  Zhou, Huan;  Fan, Shilong;  Zhang, Qi;  Shi, Xuanling;  Wang, Qisheng;  Zhang, Linqi;  Wang, Xinquan
收藏  |  浏览/下载:37/0  |  提交时间:2020/07/03

The measurement sensitivity of quantum probes using N uncorrelated particles is restricted by the standard quantum limit(1), which is proportional to 1/root N. This limit, however, can be overcome by exploiting quantum entangled states, such as spin-squeezed states(2). Here we report the measurement-based generation of a quantum state that exceeds the standard quantum limit for probing the collective spin of 10(11) rubidium atoms contained in a macroscopic vapour cell. The state is prepared and verified by sequences of stroboscopic quantum non-demolition (QND) measurements. We then apply the theory of past quantum states(3,4) to obtain spin state information from the outcomes of both earlier and later QND measurements. Rather than establishing a physically squeezed state in the laboratory, the past quantum state represents the combined system information from these prediction and retrodiction measurements. This information is equivalent to a noise reduction of 5.6 decibels and a metrologically relevant squeezing of 4.5 decibels relative to the coherent spin state. The past quantum state yields tighter constraints on the spin component than those obtained by conventional QND measurements. Our measurement uses 1,000 times more atoms than previous squeezing experiments(5-10), with a corresponding angular variance of the squeezed collective spin of 4.6 x 10(-13) radians squared. Although this work is rooted in the foundational theory of quantum measurements, it may find practical use in quantum metrology and quantum parameter estimation, as we demonstrate by applying our protocol to quantum enhanced atomic magnetometry.


  
Elongation and Stability of a Linear Dune 期刊论文
GEOPHYSICAL RESEARCH LETTERS, 2019
作者:  Rozier, Olivier;  Narteau, Clement;  Gadal, Cyril;  Claudin, Philippe;  du Pont, Sylvain Courrech
收藏  |  浏览/下载:21/0  |  提交时间:2020/02/17
solitary linear dune  steady-state morphology  sand flux estimation  finger dune  elongating dune  
Distribution network monitoring: Interaction between EU legal conditions and state estimation accuracy 期刊论文
ENERGY POLICY, 2018, 115: 78-87
作者:  Blaauwbroek, Niels;  Kuiken, Dirk;  Nguyen, Phuong;  Vedder, Hans;  Roggenkamp, Martha;  Slootweg, Han
收藏  |  浏览/下载:22/0  |  提交时间:2019/04/09
Electrical distribution network  Measurement data  Legal framework  Privacy  State estimation  Monitoring accuracy  
Global coupled sea ice-ocean state estimation 期刊论文
CLIMATE DYNAMICS, 2017, 49 (3)
作者:  Fenty, Ian;  Menemenlis, Dimitris;  Zhang, Hong
收藏  |  浏览/下载:15/0  |  提交时间:2019/04/09
Adjoint  State estimation  Sea ice  ECCO2  Coupled ocean model  Sea ice concentration data  Assimilation  4DVAR  
Ocean heat content variability and change in an ensemble of ocean reanalyses 期刊论文
CLIMATE DYNAMICS, 2017, 49 (3)
作者:  Palmer, M. D.;  Roberts, C. D.;  Balmaseda, M.;  Chang, Y. -S.;  Chepurin, G.;  Ferry, N.;  Fujii, Y.;  Good, S. A.;  Guinehut, S.;  Haines, K.;  Hernandez, F.;  Koehl, A.;  Lee, T.;  Martin, M. J.;  Masina, S.;  Masuda, S.;  Peterson, K. A.;  Storto, A.;  Toyoda, T.;  Valdivieso, M.;  Vernieres, G.;  Wang, O.;  Xue, Y.
收藏  |  浏览/下载:40/0  |  提交时间:2019/04/09
Heat content  Temperature  Variability  Climate change  Global warming  Energy budget  Ocean reanalyses  Ocean state estimation  Ocean models  Inter comparison  Ocean  Observations  Data assimilation  
Wireless Sensing, Monitoring and Optimization for Campus-Wide Steam Distribution 科技报告
来源:US Department of Energy (DOE). 出版年: 2011
作者:  [null]
收藏  |  浏览/下载:21/0  |  提交时间:2019/04/05
Energy efficiency  steam distribution system  wireless sensor networks  state estimation  steam trap diagnostics  flow rate estimation  spectrogram