Daily lake ice extent and cover proportion dataset of the Tibetan Plateau based on MODIS (2002-2018)
  • 2019-10-21
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There are many lakes on the Tibetan Plateau. The phenology and duration of lake ice age in this area is very sensitive to regional and global climate change, so it is used as a key indicator of climate change research, especially the comparative study of environmental changes in the Earth's three poles. However, due to its harsh natural environment and sparse population, it lacked routine field measurements of lake ice phenology. Using the Moderate-resolution Imaging Spectroradiometer (MODIS) to normalize the Different Snow Index (NDSI) data, the lake ice was monitored at a resolution of 500 meters to fill the observation gap. The traditional snow map algorithm was used to detect the daily ice volume and coverage extent of lakes under sunny condition. The spatial and temporal continuity of lake surface conditions was applied to re-determine the daily ice volume and coverage extent of lakes under cloud cover condition through a series of steps. Time series analysis was performed on 308 lakes larger than 3 k㎡ to determine effective record of lake ice extent and coverage, then to form a daily lake ice extent and coverage data set. And furthermore, four lake ice phenological parameters: freeze-up start ( FUS), freeze-up end (FUE), break-up start (BUS), and break-up end (BUE) can be obtained from 216 lakes of the data set, and two parameters: FUS and BUE can be obtained from the other 92 lakes.

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Global 0.05° near-surface freeze-thaw states data set (2002-2018)
  • 2019-10-21
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The near-surface freeze-thaw affects the water and energy exchanges mode and efficiency between the land and atmosphere. The transition of the freeze/thaw state affects the pattern of runoff concentration, which has an important impact on regional and global water cycle. Based on the remote sensing data of AMSR-E/2 passive microwave sensors and MODIS optical sensor, this data set uses the discriminant function algorithm and its downscaling method to produce a global mapping of near-surface freeze-thaw states with higher spatial resolution. This product covers the time period from 2002 to 2018 (daily), and spatial coverage is global scale (spatial resolution of 0.05°). It can be used to analyze the start/end time of global near-surface freeze/thaw states, the duration of freezing/thawing and their changing trends, and provide data support for studying the mechanism of water cycle and energy exchanges in the context of global change.

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River lake ice range / coverage data set v1.0
  • 2019-10-21
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There are many lakes in the Qinghai Tibet Plateau. The glacial phenology and duration of lakes in this region are very sensitive to regional and global climate change, so they are used as the key indicators of climate change research, especially the comparative study of the three polar environmental changes of the earth. However, due to its poor natural environment and sparse population, there is a lack of conventional field measurement of lake ice phenology. The lake ice was monitored with a resolution of 500 meters by using the normalized difference snow index (NDSI) data of MODIS. The traditional snow map algorithm is used to detect the lake daily ice amount and coverage under the condition of sunny days, and the lake daily ice amount and coverage under the condition of cloud cover are re determined through a series of steps based on the spatiotemporal continuity of the lake surface conditions. Through time series analysis, 308 lakes larger than 3km2 are identified as effective records of lake ice range and coverage, forming a daily lake ice range and coverage data set, including 216 lakes.

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River ice cover dataset of Erqis River Basin (2004-2005) v1.0
  • 2019-10-21
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River ice is the main component of the cryosphere, and the freezing of rivers in the polar region has a significant impact on the Arctic shipping and transportation industry. With the construction of "ice silk road" between China and Russia, monitoring the change of river ice in Erqis river basin can provide theoretical basis for river navigation. The sparse distribution of hydrological stations in the Arctic limits the study of river ice. The limited available data of hydrological stations show that the trend of river ice rupture is ahead of schedule, but the specific climate mechanism driving this trend is very complex. Therefore, optical data with high temporal resolution (such as MODIS products) are suitable for monitoring river ice phenology and mapping river ice cover range, which is helpful to understand the process of river ice rupture. Based on MODIS and passive microwave data, a method of monitoring river ice in Erqis River Basin by using different remote sensing data is realized in this study, in order to analyze the phenological parameters of river ice such as the time of river closure, the time of river closure, the speed of river opening, the speed of river closure and the duration of freezing period. At the same time, it is helpful to understand the response of river ice breaking process to Arctic climate warming.

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Product data set for key areas of Arctic sea ice (2017-2019) v1.0
  • 2019-10-21
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Because of its unique natural conditions and geographical location, the Arctic region plays a very important role in global change. Polar sea ice, as an important influencing factor of climate change, is a sensitive instrument of global climate change. The Yellow River Station, one of China's research stations in the Arctic, focuses on supporting the three scientific fields of global change and its regional response, the polar space environment and space climate, and the life characteristics and processes in the polar environment, providing an important platform for China's in-depth scientific research activities in the Arctic. Therefore, the product data set of data validation for key areas of Arctic sea ice in recent years is constructed to monitor the key areas of Arctic sea ice.

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Data set of lake ice type in alpine region (2015-2018) v1.0
  • 2019-10-21
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Lake ice is an important parameter of the cryosphere, its change is closely related to the climate parameters such as temperature and precipitation, and can directly reflect the climate change, so it is an important indicator of the regional climate parameter change. However, because the research area is often located in the area with poor natural environment and few population, large-scale field observation is difficult to carry out, so sentinel 1 satellite data is used. The spatial resolution of 10 m and the temporal resolution of better than 30 days are used to monitor the changes of different types of lake ice, which fills the observation gap. Hmrf algorithm is used to classify different types of lake ice. Through time series analysis of the distribution of different types of lake ice in three polar regions with a part area of more than 25km2, a lake ice type data set is formed. The distribution of different types of lake ice in these lakes can be obtained. The data includes the serial number of the processed lake, the year in which it is located and the serial number in the time series, vector and other information. The data set includes the algorithm used, sentinel-1 satellite data used, imaging time, polar area, lake ice type and other information. Users can determine the changes of different types of lake ice in the time series according to the vector file.

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Remote sensing inversion data set of Arctic sea ice melting pool coverage (2000-2019) v1.0
  • 2019-10-21
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Under the sunshine in summer, the snow covered on the ice surface melts, forming a pool of different shapes and sizes on the ice surface. The melting pool caused by the melting of sea ice surface will reduce the albedo of sea ice, which will have a significant impact on the energy balance of the polar region, increase the absorption and accelerate the melting process of sea ice. Among the factors that affect the albedo of sea ice, the melting pool is one of the most important and dramatic. With the change of climate, the melting rate of ice is faster and faster in summer. It has an important impact on the energy balance of the earth's surface. The acceleration of ice melting may also make the melting pool, an important natural phenomenon, become one of the most significant ice surface features in the Arctic sea ice melting season. The albedo of the melting pool is between sea water and sea ice. The study of the ice melting pool is also an important part of the study of the rapid change mechanism of the Arctic sea ice. Because of the similar microwave signal characteristics between sea ice melting pool and sea surface, and the uncertainty of mapping the coverage of melting pool with microwave data influenced by wind speed and other factors, the most reliable remote sensing method for the coverage of melting pool is to map the coverage of sub-pixel melting pool with MODIS and MERIS data. This data set includes the Arctic sea ice melting pool coverage retrieved by subpixel decomposition using MODIS observation data.

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Arctic high latitude and polar sea ice density, range, thickness, albedo (2002-2018)
  • 2019-10-21
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Sea ice is the ice formed by the freezing of sea water on the sea surface, and the re freezing of precipitation on the sea ice surface also becomes a part of sea ice. Sea ice changes not only affect the stratification, stability and convection of the ocean, but also affect the large-scale temperature and salt environment. In addition, due to the high albedo and insulation of sea ice, it can change the radiation state of the polar surface and affect the energy and material exchange between air and sea. The change of sea ice not only affects the local marine ecological environment and the local atmospheric environment, but also affects the weather and climate of other regions in the way of remote correlation through complex feedback process. Through the evaluation, this data set presents four parameters related to polar sea ice: sea ice density, range, thickness and albedo. To provide a basis for the study of polar and global climate change.

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River lake ice phenology data in QPT (2002-2018) v1.0
  • 2019-10-21
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River lake ice phenology is sensitive to climate change and is an important indicator of climate change. 308 excel file names correspond to Lake numbers. Each excel file contains six columns, including daily ice coverage information of corresponding lakes from July 2002 to June 2018. The attributes of each column are: date, lake water coverage, lake water ice coverage, cloud coverage, lake water coverage and lake ice coverage after cloud treatment. Generally, the ice cover area ratio of 0.1 and 0.9 is used as the basis to distinguish the lake ice phenology. The excel file contained in the data set can further obtain four lake ice phenological parameters: Fus, fue, bus, bue, and 92 lakes. Two parameters, Fus and bue, can be obtained.

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The 1-km Permafrost Zonation Index Map over the Tibetan Plateau
  • 2019-10-02
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Based on a recently developed inventory of permafrost presence or absence from 1475 in situ observations, we developed and trained a statistical model and used it to compile a high‐resolution (30 arc‐ seconds) permafrost zonation index (PZI) map. The PZI model captures the high spatial variability of permafrost distribution over the QTP because it considers multi- ple controlling variables, including near‐surface air temperature downscaled from re‐ analysis, snow cover days and vegetation cover derived from remote sensing. Our results showed the new PZI map achieved the best performance compared to avail- able existing PZI and traditional categorical maps. Based on more than 1000 in situ measurements, the Cohen's kappa coefficient and overall classification accuracy were 0.62 and 82.5%, respectively. Excluding glaciers and lakes, the area of permafrost regions over the QTP is approximately 1.54 (1.35–1.66) ×106 km2, or 60.7 (54.5– 65.2)% of the exposed land, while area underlain by permafrost is about 1.17 (0.95–1.35) ×106 km2, or 46 (37.3–53.0)%.

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