Hydrologic and geomorphic processes in the Colville River delta, Alaska

The Colville basin drains the North Slope of Alaska and is one of several large Arctic river systems located within permafrost. The timing and style of fluvial processes in the earth's permafrost regions differ from those occurring in midlatitude settings. Moreover, in comparison to temperate-zone systems, rivers located entirely within permafrost perform most of their work during relatively short periods of time. This paper examines river ice hydrology and the resulting geomorphic processes that occur within the Colville delta, Alaska. Fluvial processes and landform development within the Colville delta occur after the flood-pulse is initiated by the breakup of river ice. During this 4-month period, the geomorphic processes are largely influenced by the movement of ice. The flood-pulse and accompanying river ice influences erosional and depositional processes and results in unique styles of sediment transport, deposition, and riverbank erosion.     

北极中央区海冰密集度与云量相关性分析

本文使用海冰密集度以及低云、中云、高云的日平均数据,借助滑动相关分析方法,研究了北极中央区海冰密集度与云量之间的相关性,分析了海冰与云的相互作用机制。研究表明,在春季海冰融化季节(4、5月)、秋季海冰冻结季节(10、11月),低云与海冰密集度之间表现为较好的负相关,表明在这段时间内冰区海面蒸发强烈,对低云的形成有重要贡献。在10月和11月,中云与海冰密集度也有很好的负相关,表明秋季低云可以通过抬升形成中云。高云与海冰密集度之间并没有明显的相关性,可能原因:一方面海冰的空间分布对高云无影响,另一方面,高云主要影响到达的短波辐射,从而影响海冰的融化和冻结速度,与海冰厚度有直接显著的关系,而与海冰密集度的关系不明显。此外,在海冰密集度与低云存在较好负相关的情况下会出现某些年份相关性不好的情况,我们的研究发现这是北极中央区与周边海区发生了海冰交换或云交换的结果。     

Climatic control on river discharge simulations,Zackenberg River drainage basin,northeast Greenland

A spatially distributed, physically based, hydrologic modeling system (MIKE SHE) was applied to quantify intra‐ and inter‐annual discharge from the snow and glacierized Zackenberg River drainage basin (512 km²; 20% glacier cover) in northeast Greenland. Evolution of snow accumulation, distribution by wind‐blown snow, blowing‐snow sublimation, and snow and ice surface melt were simulated by a spatially distributed, physically based, snow‐evolution modelling system (SnowModel) and used as input to MIKE SHE. Discharge simulations were performed for three periods 1997–2001 (calibration period), 2001–2005 (validation period), and 2071–2100 (scenario period). The combination of SnowModel and MIKE SHE shows promising results; the timing and magnitude of simulated discharge were generally in accordance with observations (R² = 0·58); however, discrepancies between simulated and observed discharge hydrographs do occur (maximum daily difference up to 44·6 m³ s^?1 and up to 9% difference between observed and simulated cumulative discharge). The model does not perform well when a sudden outburst of glacial dammed water occurs, like the 2005 extreme flood event. The modelling study showed that soil processes related to yearly change in active layer depth and glacial processes (such as changes in yearly glacier area, seasonal changes in the internal glacier drainage system, and the sudden release of glacial bulk water storage) need to be determined, for example, from field studies and incorporated in the models before basin runoff can be quantified more precisely. The SnowModel and MIKE SHE model only include first‐order effects of climate change. For the period 2071–2100, future IPCC A2 and B2 climate scenarios based on the HIRHAM regional climate model and HadCM3 atmosphere–ocean general circulation model simulations indicated a mean annual Zackenberg runoff about 1·5 orders of magnitude greater (around 650 mmWE year^?1) than from today 1997–2005 (around 430 mmWE year^?1), mainly based on changes in negative glacier net mass balance. Copyright © 2007 John Wiley & Sons, Ltd.     

The seasonal foot printing mechanism of spring Arctic sea ice in the Bergen climate models

The influence of spring Arctic sea ice variability on the Pacific Decadal Oscillation(PDO) like sea surface temperature(SST) variability is established and investigated using an Atmosphere Ocean General Circulation Model(AOGCM) of the Bergen Climate Model version 2(BCM2). The spring Arctic sea ice variability affects the mid-latitudes and tropics through the propagation of the anomalous Eliassen-Palm(E-P) flux from the polar region to mid- and low-latitudes during boreal spring. The pathway includes anomalous upward wave activity, which propagates to the high troposphere from near the surface of the polar region, turns southward between 500 h Pa and 200 h Pa and extends downward between 50°N and 70°N, influencing the near surface atmospheric circulation. The alteration of the near surface atmospheric circulation then causes anomalous surface ocean circulation. These circulation changes consequently leads to the SST anomalies in the North Pacific which may persist until the following summer, named seasonal "foot printing" mechanism(SFPM).     

Seasonal changes in sea ice conditions along the Northeast Passage in 2007 and 2012

Remote sensing data from passive microwave and satellite-based altimeters, associated with the data measured underway, were used to characterize seasonal and spatial changes in sea ice conditions along...     

Links between Arctic sea ice and extreme summer precipi- tation in China：an alternative view

Potential links between the Arctic sea-ice concentration anomalies and extreme precipitation in China are explored. Associations behind these links can be explained by physical interpretations aided by...     

An improved optical flow method to estimate Arctic sea ice velocity (winter 2014?2016)

1 Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology/Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China; 2 Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing 210023, China; 3 Collaborative Innovation Center of South China Sea Studies, Nanjing 210023, China     

Cross-calibration of brightness temperature obtained by FY-3B/MWRI using Aqua/AMSR-E data for snow depth retrieval in the Arctic

This study cross-calibrated the brightness temperatures observed in the Arctic by using the FY-3B/MWRI L1 and the Aqua/AMSR-E L2A. The monthly parameters of the cross-calibration were determined and evaluated using robust linear regression. The snow depth in case of seasonal ice was calculated by using parameters of the crosscalibration of data from the MWRI T_b. The correlation coefficients of the H/V polarization among all channels T_b of the two sensors were higher than 0.97. The parameters of the monthly cross-calibration were useful for the snow depth retrieval using the MWRI. Data from the MWRI T_b were cross-calibrated to the AMSR-E baseline.Biases in the data of the two sensors were optimized to approximately 0 K through the cross-calibration, the standard deviations decreased significantly in the range of 1.32 K to 2.57 K, and the correlation coefficients were as high as 99%. An analysis of the statistical distributions of the histograms before and after cross-calibration indicated that the FY-3B/MWRI T_b data had been well calibrated. Furthermore, the results of the cross-calibration were evaluated by data on the daily average T_b at 18.7 GHz, 23.8 GHz, and 36.5 GHz(V polarization), and at 89 GHz(H/V polarization), and were applied to the snow depths retrieval in the Arctic. The parameters of monthly cross-calibration were found to be effective in terms of correcting the daily average T_b. The results of the snow depths were compared with those of the calibrated MWRI and AMSR-E products. Biases of 0.18 cm to 0.38 cm were observed in the monthly snow depths, with the standard deviations ranging from 4.19 cm to 4.80 cm.