Soluble organic carbon (DOC) in snow and ice can effectively absorb the solar radiation in the ultraviolet and near ultraviolet band, which is also one of the important factors leading to the enhancement of snow and ice ablation. Through the continuous snow samples from November 2016 to April 2017 in Altay area, the data of DOC, TN and BC of snow in kuwei station in Altay area were obtained through the experimental analysis and test with the instrument. The time resolution was weeks and the ablation period was daily. 1. Unit: Doc and TN unit μ g-1 (PPM), BC unit ng g-1 (ppb), MAC unit M2 g-1
SHANGGUAN Donghui
Snow water equivalent (SWE) is an important parameter of the surface hydrological model and climate model. The data is based on the ridge regression algorithm of machine learning, which integrates a variety of existing snow water equivalent data products to form a set of snow water equivalent data products with continuous time series and high accuracy. The spatial range of the data is Pan-Arctic (45 N° to 90 N °), The data time series is 1979-2019. The dataset is expected to provide more accurate snow water equivalent data for the hydrological and climate model, and provide data support for cryosphere change and global change.
LI Hongyi, SHAO Donghang, LI Haojie, WANG Weiguo, MA Yuan, LEI Huajin
The basic meteorological data set of the China-Mongolia-Russia Economic Corridor meteorological station includes wind speed, wind direction, precipitation, temperature and snow depth. The time resolution is 3 hours. The site is scattered around the corridor and the number of sites is 29. The data set was extracted based on the National Oceanic and Atmospheric Administration's National Environmental Information Center (NCEI) hourly/sub-hour observation dataset. In addition to the data itself, each data includes information such as data quality assessment results and data acquisition methods. In addition, the precipitation data of each site is composed of 4 detection devices to ensure data stability. Snow depth data includes snow depth and equivalent water depth dimensions, ie the depth of water after the snow melts.
LI Shengyu, FAN Jinglong
The data include three data sets of Namcu and Muztagh Ata: an atmospheric aerosol data set of monthly average values of TSP, lithium, sodium and other elements; an atmospheric precipitation chemical data set of monthly average values of soluble sodium ions, potassium ions, magnesium ions, calcium ions and other ions; and a data set of chemical compositions of snow ice in the Zhadang Glacier of Namcu Basin of the concentrations of soluble sodium ions, potassium ions, magnesium ions, calcium ions and other ions in snow pits collected in different months. The data can be used in conducting located observations of atmospheric aerosol element content, precipitation chemistry, and glacier snow ice chemical records in the Namco and Muztagh Ata areas. The samples were processed at the Key Laboratory of Tibetan Environment Changes and Land Surface Processes of CAS using ICS2500 and ICS2000 ion-chromatographic analyzers to determine the concentration of soluble anions and cations in the samples. Data collection and processing: 1. The automatic rain gauges were erected in the typical regions of the Tibetan Plateau (the Namco Basin and the Muztagh Ata Peak area) to collect precipitation samples. The precipitation samples were collected using a SYC-2 type rainfall sampler that comprised a collector, rain sensor and gland drive. The sample collector was provided with a rain collection bucket and a dust collection bucket, and the weather condition was sensed by the rain sensor. The rain collection bucket would be opened when it started to rain, and the gland would be pressed onto the dust collection bucket. Meanwhile, the date and the rain start and end times were automatically recorded. When the rain stopped, the gland automatically flipped to the rain collection bucket to complete a rainfall record. The collected samples were placed in 20 mL clean high-density polyethylene plastic bottles and refrigerated in a -20 °C refrigerator. They were frozen during transportation and storage until right before being analyzed, when they would be taken from the refrigerator and thawed at room temperature (20 °C). They were then processed at the Key Laboratory of Tibetan Environment Changes and Land Surface Processes CAS using ICS2500 and ICS2000 ion-chromatographic analyzers to determine the concentration of soluble anions and cations in the precipitation. 2. The atmospheric aerosol sampler installed at Namco Station was 4 m above the ground and included a vacuum pump, which was powered by solar panels and batteries. The air flux was recorded by an automatic flow meter, and the instantaneous flow rate was approximately 16.7 L/min. The air flux took the meteorological parameter conversion of the Namco area as the standard volume. A Teflon filter with a diameter of 47 mm and a pore size of 0.4 & mu; m was used. The sample interval was 7 days, and the total sample flow rate of each sample was approximately 120-150 m³. Each sample was individually placed in a disposable filter cartridge and stored at low temperature in a refrigerator. Before and after sampling, the filter was placed in a constant temperature (20 ± 5 °C) and constant humidity (40 & plusmn; 2%) environment for 48 hours and weighed with a 1/10000 electronic balance (AUW220D, Shimadu); the difference between the weights before and after was the weight of the aerosol sample on the filter. The collected samples were processed at the Key Laboratory of Tibetan Environment Changes and Land Surface Processes CAS by ICP-MS to determine the concentrations of 18 elements. Strict measures were taken during indoor and outdoor operations to prevent possible contamination. 3. A precleaned plastic shovel was used to collect a sample every 5 cm from the lower part of the snow pit (samples were collected every 10 cm in some snow pits). The samples were dissolved at room temperature, placed in 20 mL clean high-density polyethylene plastic bottles and stored in a refrigerator at -20 °C. The samples were frozen during transportation and storage until they were taken out of the refrigerator before the analysis and melted at room temperature. The samples were processed at the Key Laboratory of Tibetan Environment Changes and Land Surface Processes CAS using ICS2500 and ICS2000 ion-chromatographic analyzers to determine the concentrations of soluble anions and cations in the samples. Clean clothing, disposable masks and plastic gloves should be worn during the manual collection of glacier snow ice chemical samples to prevent contamination. The data set was processed by forming a continuous sequence of monthly mean values after the raw data were quality controlled. It meets the accuracy of routine monitoring research on precipitation, aerosol, snow and ice records in China and the world and is satisfactory for comparative study with relevant climate change records.
KANG Shichang
This data is generated based on meteorological observation data, hydrological station data, combined with various assimilation data and remote sensing data, through the preparation of the Qinghai Tibet Plateau multi-level hydrological model system WEB-DHM (distributed hydrological model based on water and energy balance) coupling snow, glacier and frozen soil physical processes. The time resolution is monthly, the spatial resolution is 5km, and the original data format is ASCII text format, Data types include grid runoff and evaporation (if evaporation is less than 0, it means condensation; if runoff is less than 0, it means precipitation is less than evaporation in the month). If the asc cannot be opened normally in arcmap, please top the first 5 lines of the asc file.
WANG Lei, CHAI Chenhao
Among many indicators reflecting changes in climate and environment, the stable isotope index of ice core is an indispensable parameter in ice core record research, and it is one of the most reliable means and the most effective way to restore past climate change. Meanwhile, ice core accumulation is a direct record of precipitation on the glacier, and high-resolution ice core records ensure continuity of precipitation records. Therefore, ice core records provide an effective means of restoring changes in precipitation. Stable isotopes from ice cores drilled throughout the TP have been used to reconstruct climate histories extending back several thousands of years. This dataset provides data support for studying climate change on the Tibetan Plateau.
XU Baiqing
As the “water tower of Asia”, Tibetan Plateau (TP) are the resource of major rivers in Asia. Black carbon (BC) aerosol emitted from surrounding regions can be transported to the inner TP by atmospheric circulation and consequently deposited in snow, which can significantly influence precipitation and mass balance of glaciers. By drilling and sampling ice cores and snow samples and measuring BC concentration, historical record and spatial distribution can be abtained. It can provide basic dataset to study the effects of BC to the environment and climate over the Tibetan Plateau, as well as the pollutants transport.
XU Baiqing
This dataset is derived from the paper: Xiaodan Wu, Kathrin Naegeli, Valentina Premier, Carlo Marin, Dujuan Ma, Jingping Wang, Stefan Wunderle. (2021). Evaluation of snow extent time series derived from AVHRR GAC data (1982-2018) in the Himalaya-Hindukush. The Cryosphere, 15,4261-4279. ln this paper, the performance of the AVHRR GAC snowpack product in the Hindu Kush Himalayas is comprehensively evaluated for the first time on a long time scale (1982-2018) based on ground station data, Landsat data, and MODIS snowpack product, respectively, including the consistency of the accuracy/precision of the product over a long time series, and the consistency of the product with Landsat and MODIS snowpack data in terms of spatial distribution. The main factors affecting the accuracy of the AVHRR GAC snowpack product are also revealed.
WU Xiaodan
In this study, an algorithm that combines MODIS Terra and Aqua (500 m) and the Interactive Multisensor Snow and Ice Mapping System (IMS) (4 km) is presented to provide a daily cloud-free snow-cover product (500 m), namely Terra-Aqua-IMS (TAI). The overall accuracy of the new TAI is 92.3% as compared with ground stations in all-sky conditions; this value is significantly higher than the 63.1% of the blended MODIS Terra-Aqua product and the 54.6% and 49% of the original MODIS Terra and Aqua products, respectively. Without the IMS, the daily combination of MODIS Terra-Aqua over the Tibetan Plateau (TP) can only remove limited cloud contamination: 37.3% of the annual mean cloud coverage compared with the 46.6% (MODIS Terra) and 55.1% (MODIS Aqua). The resulting annual mean snow cover over the TP from the daily TAI data is 19.1%, which is similar to the 20.6% obtained from the 8-day MODIS Terra product (MOD10A2) but much larger than the 8.1% from the daily blended MODIS Terra-Aqua product due to the cloud blockage.
ZHANG Guoqing
China's daily snow depth simulation and prediction data set is the estimated daily snow depth data of China in the future based on the nex-gdpp model data set. The artificial neural network model of snow depth simulation takes the maximum temperature, minimum temperature, precipitation data and snow depth data of the day as the input layer of the model, The snow depth data of the next day is used as the target layer of the model to build the model, and then the snow depth simulation model is trained and verified by using the data of the national meteorological station. The model verification results show that the iterative space-time simulation ability of the model is good; The spatial correlations of the simulated and verified values of cumulative snow cover duration and cumulative snow depth are 0.97 and 0.87, and the temporal and spatial correlations of cumulative snow depth are 0.92 and 0.91, respectively. Based on the optimal model, this model is used to iteratively simulate the daily snow depth data in China in the future. The data set can provide data support for future snow disaster risk assessment, snow cover change research and climate change research in China. The basic information of the data is as follows: historical reference period (1986-2005) and future (2016-2065), as well as rcp4.5 and rcp8.5 scenarios and 20 climate models. Its spatial resolution is 0.25 ° * 0.25 °. The projection mode of the data is ease GR, and the data storage format is NC format. The following is the data file information in NC Time: duration (unit: day) Lon = 320 matrix, 320 columns in total Lat = 160 matrix, 160 rows in total X Dimension: Xmin = 60.125; // Coordinates of the corner points of the lower left corner grid in the X direction of the matrix Y Dimension: Ymin = 15.125; // Coordinates of the corner points of the grid at the lower left corner of the Y-axis of the matrix
CHEN Hongju, YANG Jianping, DING Yongjian
This data is a 5km monthly hydrological data set, including grid runoff and evaporation (if evaporation is less than 0, it means condensation; if runoff is less than 0, it means precipitation is less than evaporation), simulated and output through the WEB-DHM distributed hydrological model of the Indus River basin, with temperature, precipitation, barometric pressure, etc. as input data.
WANG Lei, LIU Hu
This data set comes from the book: glaciers in Hengduan Mountain area, which belongs to the series of scientific investigation in Hengduan Mountain Area of Qinghai Tibet Plateau. The chief editor is Li Jijun, the deputy chief editor is Su Zhen, and the guiding unit is Institute of geography, Chinese Academy of Sciences. The research team of the book is the Qinghai Tibet Plateau comprehensive research team of the Chinese Academy of Sciences, and the publishing house is Science Press. Due to abundant rainfall and deep snow cover in some areas of Hengduan Mountain. Avalanche, wind blown snow and abnormal snowfall have become a common natural disaster, which has caused great damage to the work and life of local residents. This book makes a detailed record of the snow disaster in Hengduanshan area. The data includes two workbooks and two pictures, which are the statistical table of snow damage status and damage degree, the regional characteristics of avalanche, the topographic cutting degree map of Western Sichuan, Northern Yunnan and southeastern Tibet, and the damage scope map of Hengduanshan avalanche.
LI Jijun
Based on AVHRR-CDR SR products, a daily cloud-free snow cover extent dataset with a spatial resolution of 5 km from 1981 to 2019 was prepared by using decision tree classification method. Each HDF4 file contains 18 data elements, including data value, data start date, longitude and latitude, etc. At the same time, to quickly preview the snow distribution, the daily file contains the snow area thumbnail, which is stored in JPG format. This data set will be continuously supplemented and improved according to the real-time satellite remote sensing data and algorithm update (up to may 2019), and will be fully open and shared.
HAO Xiaohua
The data is an excel file, which includes four tables named as follows: Altay Snow DOC Time Series, Altay Snow Pit Data, Altay Snow MAC (absorption section) and Central Asia Mos Island Glacier BC, OC, DUST Data. Altay snow DOC table includes seven columns including sample number, sampling date, sampling time, sampling depth, DOC-PPM, BC-PPb and TN-PPM, and 47 sample data. Altay snow pit table includes 8 columns including snow pit number, sample number, sampling date, sampling time, sampling depth, DOC-PPM, BC-PPb and TN-PPM, and 238 sample data. Altay snow MAC table includes: sampling time, MAC and AAE, a total of three columns, and 46 sample data. The BC, OC and DUST data tables of glaciers in Central Asia's Muse Island include 8 columns: code no (sample number), Latitude (latitude), Longitude (longitude),/m a.s.l (altitude), snow type (snow type), BC, OC and DUST, which are analyzed by sampling time. There are 105 rows of data in total. Abbreviation explanation: DOC: Dissolved Organic Carbon MAC: mass absorption cross section BC: black carbon DUST: Dust OC: Organic carbon TN: Total Nitrogen PPM: ug g-1 (microgram per gram) PPb: ng g-1 (nanogram per gram)
ZHANG Yulan
The Asian water tower region, with the Qinghai-Tibet Plateau as the core, is the most widely distributed snow area on Earth except for the North and South Poles. The topographic heterogeneity of the Asian water tower region is great, and the snow in the region shows a thin snow layer and large patchy distribution, resulting in the high time-varying characteristics of the snow in the region, so there is an urgent need for daily-scale dynamic monitoring data of snow cover. This dataset is based on the MODIS global surface reflectance product, MO/YD09GA, using the Multiple Endmember Spectral Mixture Analysis- Automatic-selected Endmembers (MESMA -AGE) and interpolation algorithm based on spatial and temporal information to construct a MODIS day-by-day cloud-free snow cover dataset for the Asian water tower region from 2000 to 2020. With high spatial resolution Landsat images as “ground truth”, the root mean square error is 0.14, which is better than the two snow datasets MODSCAG and MOD10A1 commonly used internationally. The time series of this dataset is from February 26, 2000 to March 31, 2020, which can provide quantitative spatial distribution information of snowpack for mountain hydrological models, land surface models, and numerical weather forecasts.
JIANG Lingmei, PAN Fangbo , WANG Gongxue , PAN Jinmei, SHI Jiancheng, ZHANG Cheng
The SZIsnow dataset was calculated based on systematic physical fields from the Global Land Data Assimilation System version 2 (GLDAS-2) with the Noah land surface model. This SZIsnow dataset considers different physical water-energy processes, especially snow processes. The evaluation shows the dataset is capable of investigating different types of droughts across different timescales. The assessment also indicates that the dataset has an adequate performance to capture droughts across different spatial scales. The consideration of snow processes improved the capability of SZIsnow, and the improvement is evident over snow-covered areas (e.g., Arctic region) and high-altitude areas (e.g., Tibet Plateau). Moreover, the analysis also implies that SZIsnow dataset is able to well capture the large-scale drought events across the world. This drought dataset has high application potential for monitoring, assessing, and supplying information of drought, and also can serve as a valuable resource for drought studies.
WU Pute, TIAN Lei, ZHANG Baoqing
Based on long-term series Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products, daily snow cover products without data gaps at 500 m spatial resolution over the Tibetan Plateau from 2002 to 2021 were generated by employing a Hidden Markov Random Field (HMRF) modeling technique. This HMRF framework optimally integrates spectral, spatiotemporal, and environmental information together, which not only fills data gaps caused by frequent clouds, but also improves the accuracy of the original MODIS snow cover products. In particular, this technology incorporates solar radiation as an environmental contextual information to improve the accuracy of snow identification in mountainous areas. Validation with in situ observations and snow cover derived from Landsat-8 OLI images revealed that these new snow cover products achieved an accuracy of 98.31% and 92.44%, respectively. Specifically, the accuracy of the new snow products is higher during the snow transition period and in complex terrains with higher elevations as well as sunny slopes. These gap-free snow cover products effectively improve the spatiotemporal continuity and the low accuracy in complex terrains of the original MODIS snow products, and is thus the basis for the study of climate change and hydrological cycling in the TP.
HUANG Yan , XU Jianghui
The fractional snow cover (FSC) is the ratio of snow cover area (SCA) to unit pixel area. The data set is made by bv-blrm snow area proportional linear regression empirical model; The source data used are mod09ga 500m global daily surface reflectance products and mod09a1 500m 8-day synthetic global surface reflectance products; The production platform uses Google Earth engine; The data range is global, the data preparation time is from 2000 to 2021, the spatial resolution is 500 meters, and the temporal resolution is year by year. This set of data can provide quantitative information of snow cover distribution for regional climate simulation and hydrological models.
MA Yuan
The data include K, Na, CA, Mg, F, Cl, so 4 and no 3 in the glacier runoff of zhuxigou, covering most of the inorganic dissolved components. The detection limit is less than 0.01 mg / L and the error is less than 10%; The data can be used to reflect the contribution of chemical weathering processes such as sulfide oxidation, carbonate dissolution and silicate weathering to river solutes in zhuxigou watershed, and then accurately calculate the weathering rates of carbonate and silicate rocks, so as to provide scientific basis for evaluating the impact of glaciation on chemical weathering of rocks and its carbon sink effect.
WU Guangjian
Record the original collection process of glacier, runoff, soil and air microbial samples. 1) Collection of ice and snow microbial samples: wear clean gloves during collection and collect ice and snow into clean self sealing bags. 2) Collection of ice dust microbial samples: insert the hose into the bottom of the ice and snow cave, suck the sediment and melt water into the sampling bottle with a syringe, store them at low temperature and bring them back to the laboratory. Both the sediment and melt water on the top of the ice dust cave are used to extract environmental DNA. 3) Runoff includes ice runoff and glacier front runoff, and the runoff melt water is directly collected into the sampling bottle or water collection bag. 4) Collection of soil in front of Glacier: collect soil samples with shovel, put the soil into clean whirl Pak sampling bag after passing 2mm soil sieve, and then store it at low temperature for subsequent soil DNA extraction. 5) Air membrane sample collection: place the designed sampling device at the sampling point. The lower part of the device is a battery (continuous operation for 48h), and the upper part contains two filter membranes to collect air microorganisms for DNA extraction. 6) for real-time monitoring of physical and chemical properties in Glacier runoff and melt water, use YSI multi parameter water quality instrument to directly put it into the sample to be measured to obtain temperature, do, chlorophyll concentration, etc.
LIU Yongqin
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