DynIceData:a gridded ice-water classification dataset at short-time intervals based on observations from multiple satellites over the marginal ice zone

High-resolution observations of short-term changes in sea ice are critical to understanding ice dynamics and also provide important information used in advice to shipping,especially in the Arctic.Although individual satellite sensors provide periodic sea ice obser-vations with spatial resolutions of tens of meters,information regarding changes that occur over short time intervals of minutes or hours is limited.In this study,a gridded ice-water classification dataset with a high temporal resolution was developed based on observations acquired by multiple satellite sensors in the Marginal Ice Zone(MIZ).This dataset-DynIceData-which combines Sentinel-1 Synthetic Aperture Radar(SAR)data with Gaofen-3(GF-3)SAR and SDGSAT-1 thermal infrared imagery was used to obtain observations of the MIZ with a range of temporal resolutions ran-ging from minutes to tens of hours.The areas of the Arctic covered include the Kara Sea,Beaufort Sea,and Greenland Sea during the period from August 2021 to August 2022.Object-oriented segmen-tation and thresholding were used to obtain the ice-water classifi-cation map from Sentinel-1 and GF-3 SAR image pairs and Sentinel-1 SAR and SDGSAT-1 thermal image pairs.The time interval between the images in each pair ranged from 1 minute to 68 hours.Ten-kilometer grid sample granules with a spatial resolution of 25 m for the GF-3 SAR data and 30 m for the SDGSAT-1 thermal data were used.The classification was verified as having an overall accuracy of at least 95.58%.The DynIceData dataset consists of 7338 samples,which could be used as reference data for further research on rapid changes in sea ice patterns at different short time scales and provide support for research on thermodynamic and dynamic models of sea ice in combination with other environmen-tal data,thus potentially improving the accuracy of sea ice forecast-ing using Artificial Intelligence.The dataset can be accessed at https://doi.org/10.57760/sciencedb.j00001.00784.

High pressure-differential thermal analysis of ice-water equilibrium at 1.5-5.0 GPa

It is well known that trace amount of water has important effects on the physical properties of minerals and melts. Strength and viscosity decrease, diffusion rate and electrical conductivity increase, seismic waves attenuate and liquidus temperatures are lowered by the addition of water. The effects make water one of the most active components of any geological system with implications for the evolution and dynamics of the earth.

Research on the Operational Conditions of Artificial Precipitation Enhancement in Liaoning Province

Taking precipitation process during May 17-18,2009 as an example,this paper analyzed and summarized the operational conditions of artificial precipitation enhancement in Liaoning Province.Operational conditions can be divided into two categories,namely,macro-weather and cloud micro-physical operational conditions,this paper described their respective indexes and criterions as well as their effect and application in formulation and command of artificial precipitation enhancement plan real-timely.

A novel scalable synthesis process of PPTA by coupling n-pentane evaporation for polymerization heat removal

In this study,we compared the effect of n-pentane and ice-water bath on removing the thermal effect in the poly（p-phenylene terephthalamide）（PPTA） polymerization process.The results indicate that the n-pentane can help to transfer the reaction heat faster and better.Adding suitable amount of n-pentanes into the PPTA preparation process not only improve the heat transfer,but also reduce the motor power in the polymerization process.Moreover,the introduction of n-pentane properly does not result in decrease of the inherent viscosity（η_（inh）） of polymer.Instead,it leads to increased viscosity of polymer during the PPTA preparation process.The results indicate that n-pentane can effectively transfer the reaction heat and avoid overheating during the polymerization of PPTA.

Measurement of Ice Movement in Water Using Electrical Capacitance Tomography

The permafrost with the highest altitude and largest area in the mid and low latitude is located in the Qinghad-Tibet Plateau. As most frozen soils contain ice particles which are very sensitive to temperature and other external parameters, thus influencing the stability of the embankment in permafrost regions, it is very important to develop techniques to prevent damages to railway embankments due to thaw settlement. In this paper, the electrical capacitance sensors are designed to study the freezing front movement in a vessel and ice movement in water, which is the first step to apply the ECT system to the study of frozen soil. Two sensor arrangements are put into use. First, the traditional closed electrode sensors are put into use. In this arrangement, the electrodes are attached to the outside of the pipe or vessel, and the cross-sectional distribution of ice and water could be reconstructed from the capacitances measured. Also, the ice moving track at the cross section could be reflected thoroughly.Since the traditional closed electrode sensors can not meet the needs of measuring the ice freezing front move- ment, a new electrode sensors structure, that is, the unclosed electrode sensors are designed to satisfy the specific test of frozen soil. In this arrangement, several pairs of electrodes are arranged along the height of the vessel. A sudden decrease in the measured capacitance is observed when the freezing front advances past the electrodes.Therefore, according to the capacitance variation, the ice movement can be reflected. In summary, electrical capacitance tomography has the advantages of being non-intrusive. With different electrode sensor arrangement, ice movement and ice freezing front can be obtained. The electrical capacitance sensor system can be applied to investigate the complicated phenomena in frozen soil.

Routeview:an intelligent route planning system for ships sailing through Arctic ice zones based on big Earth data

The potential of Arctic routes(ARs)has attracted global attention,and exploiting the Arctic has become an important strategy for many countries.However,there are still some challenges for ships sailing in Arctic ice zones,including harsh marine environments and the insufficient service capacity of sea ice information service systems.To better understand the route changes in the Arctic and extract real-time ship navigation routes,we developed an online interactive route planning system(RouteView)for ships sailing in the Arctic based on big Earth data.RouteView includes two main features:(1)an online calculation interface is provided for optimal routes along the Arctic Northeast Passage(NEP)60 days into the future by utilizing reinforcement learning(RL)based on sea ice and meteorological data,and(2)an online ice-water classification is established based on synthetic aperture radar(SAR)data and deep learning to help users extract the sea ice distribution in real time.This work can potentially enhance the safety of shipping navigation along the NEP and improve information extraction methods for ARs.

STUDY ON SEA ICE WITH GMS REAL-TIME DATA

By use of GMS-4 infrared brightness temperature and visible albedo data from January to February in 1995,the method for extracting of sea ice parameters is developed.The digital remote sensing picture is obtained on Liaodong Bay.Based on the difference in physical properties between ice and water,a criterion distinguishing ice from water is set up.Ice thickness has been calculated according to the relationship between ice thickness and brightness as well as albedo.Ice concentration is retrieved due to the difference on albedo between ice and water.The results indicate that the accuracy of ice-water distinguishing is 84.8%,the errors of ice thickness and ice concentration are 3.8 cm and 22%,respectively.