Melt probabilities and surface temperature trends on the Greenland ice sheet using a Gaussian mixture model

The Greenland ice sheet has experienced significant melt over the past six decades, with extreme melt events covering large areas of the ice sheet. Melt events are typically analysed using summary statistics, but the nature and characteristics of the events themselves are less frequently analysed. Our work examines melt events from a statistical perspective by modelling 19 years of Moderate Resolution Imaging Spectroradiometer (MODIS) ice surface temperature data using a Gaussian mixture model. We use a mixture model with separate model components for ice and meltwater temperatures at 1139 locations spaced across the ice sheet. By considering the uncertainty of the ice surface temperature measurements, we use the two categories of model components to define a probability of melt for a given observation rather than using a fixed melt threshold. This probability can then be used to estimate the expected number of melt events at a given location. Furthermore, the model can be used to estimate temperature quantiles at a given location, and analyse temperature and melt trends over time by fitting the model to subsets of time. Fitting the model to data from 2001–2009 and 2010–2019 shows increases in melt probability for significant portions of the ice sheet, as well as the yearly expected maximum temperatures.

Estimating subpixel turbulent heat flux over leads from MODIS thermal infrared imagery with deep learning

The turbulent heat flux (THF) over leads is an important parameter for climate change monitoring in the Arctic region. THF over leads is often calculated from satellite-derived ice surface temperature (IST) products, in which mixed pixels containing both ice and open water along lead boundaries reduce the accuracy of calculated THF. To address this problem, this paper proposes a deep residual convolutional neural network (CNN)-based framework to estimate THF over leads at the subpixel scale (DeepSTHF) based on remotely sensed images. The proposed DeepSTHF provides an IST image and the corresponding lead map with a finer spatial resolution than the input IST image so that the subpixel-scale THF can be estimated from them. The proposed approach is verified using simulated and real Moderate Resolution Imaging Spectroradiometer images and compared with the conventional cubic interpolation and pixel-based methods. The results demonstrate that the proposed CNN-based method can effectively estimate subpixel-scale information from the coarse data and performs well in producing fine-spatial-resolution IST images and lead maps, thereby providing more accurate and reliable THF over leads.

A Case Study on Curling Stone and Sweeping Effect According to Sweeping Conditions

The purpose of this study was to use the same ice temperature and air temperature as the Pyeongchang Curling Stadium by using an Ice Chamber. Then, launch the stone at the same speed, and move according to the sweeping conditions (perpendicular to the axis of motion, along the axis of motion) of male and female elite curlers. The aim is to provide sports science information required for curling athletes by analyzing the distance of the stone, the change in the speed of a moved stone, the change in broom acceleration, and athletes’ muscle activity. The results of experiments conducted on four male and four elite female curlers are as follows. Under gender, the stone’s movement distance was long after the sweeping of male athletes, and the speed of the stone was not different according to the conditions. The broom’s acceleration did not show a difference in both the sweeping condition and the athlete’s gender condition, and the muscle activity did not show a significant difference in both the sweeping condition and the gender condition. In summary, it is thought that male athletes moved the stone farther by raising the ice surface temperature by vertical load than female athletes. Also, there was no statistically significant difference in muscle activity results, but it was found that there was a specific pattern of muscle activity in the pushing and pulling motions during the sweeping of male and female athletes. It is expected to be used as primary data.

Antarctic ice and snow surface temperature retrieval from MODIS and Landsat8

<p>Ice <span>surface temperature (IST) is of utmost importance to the ice sheet radiation budget and mass balance, which has been documented by many scientific researches. </span></p><p>This<span> research firstly proposes an effective approach to retrieve IST in the Antarctic area by presenting a modified split-window algorithm (SWA) and introducing a polynomial fitting for atmospheric transmittance simulation. The effectiveness was quantitatively validated by a comparative study with a Moderate Resolution Imaging Spectroradiometer (MODIS) IST product (MOD29) and automatic weather station (AWS) data from Zhongshan Station and the Ross</span> <span>Ice Shelf from 2004 to 2013. From the algorithm validation and data comparison, it was found that: 1) The polynomial fitting can better describe the relationship between water vapor and atmospheric transmittance, with higher determination coefficients (0.99887 for band 31 and 0.99895 for band 32, respectively) and lower residual sum of squares (0.000373 for band 31 and 0.000234 for band 32, respectively). 2) Using the Zhongshan Station data set, the retrieved ISTs by the proposed method were more accurate than the MOD29 product, with a bias of −0.61 K and a root-mean-square error (RMSE) of 1.32 K; comparatively, the bias for MOD29 was −1.33 K and the RMSE for MOD29 was 1.81 K. 3) The proposed method also obtained the highest accuracy in the other experiment using the Ross Ice Shelf data set, in which the bias and RMSE for the retrieved ISTs were −1.62 K and 2.34 K, respectively; the corresponding accuracies for MOD29 were −2.54 K and 3.04 K, respectively. Overall, it was found that the proposed method shows a robust performance in Antarctic IST retrieval for MODIS data.</span></p><p><span>Besides, an improved single-channel (SC) algorithm is proposed for retrieving the ice surface temperature of polar regions from Landsat8 band10 in this study. The improved algorithm avoids using Taylor's theorem and eliminates Taylor approximation error. In addition, the at</span><span>mospheric parameters suitable for polar regions are simulated and the effective mean atmospheric temperature is added to the fitting process. In order to maintain the advantage of the SC algorithm minimum input data requirements, the effective mean atmospheric temperature is obtained by using the existing parameters and iterative calculation. The results of sensitivity analysis show that the improved algorithm is not sensitive to atmospheric water vapor content but sensitive to the calibration precision of thermal infrared sensor. Theoretical verification results show that the RMSEs of the SC algorithm and the improved SC algorithm are 0.72 K and 0.33 K, respectively. Compared with MODIS land surface temperature product, the RMSE of the improved SC algorithm is 0.31K. Compared with the temperature of automatic weather stations, in the Antarctic, the RMSE of SC algorithm is of 1.48 K and the improved SC algorithm is 1.22 K. In conclusion, the improved SC algorithm performs better than SC algorithm in polar ice surface temperature retrieval.</span></p>

AUTOMATED DEVICE FOR ICE SURFACE QUALITY ASSESSMENT

Results of ice quality assessment depending on various conditions of the environment and ice preparation are presented in article. The optimum indicators of the studied values influencing the ice surface quality are revealed. It is possible to estimate ice speed qualities objectively with the device, that imitates skater sliding. The purpose of the study is to determine the dependence of the sliding friction coefficient on the parameters of water treatment, the conditions for freezing the ice surface, the temperature of the ice surface, hardness and other parameters. The imitation is the movement of the mobile platform mounted on skates, supplied with the module transferring to the personal computer the values of skates sliding on the ice surface friction parameters. To measure the distance traveled by the device, the laser ranging method was used. The efficiency of the developed device and the technique of its application for assessment of ice quality on sports arenas are shown. The dependences of the quality of the ice surface on the surface temperature of the ice, air temperature, temperature of the poured water are considered. Accounting of these indicators during competitions allows to create «fast» ice for high sports results demonstration. The best values of the range of the device were recorded with the following parameters: ice surface temperature – from –3,5 to –4,5 °С, concrete slab temperature – –6 °С, ice thickness – 27–29 mm, filled water temperature – 50–55 °С, cutting the top layer of ice with an ice-filling machine – 100 %. The worst values of the range of the device were obtained with the following parameters: ice surface temperature – from –5,3 to –5,4 °С, filled water temperature – 30–35 °С, the top layer of ice was not cutby an ice-filling machine.

Experimental Investigation of the Tractive Performance of Pneumatic Tires on Ice

ABSTRACT This investigation was motivated by the need for performance improvement of pneumatic tires in icy conditions. Under normal operation, the pneumatic tire is the only force-transmitting component between the terrain and the vehicle. Therefore, it is critical to grasp the understanding of the contact mechanics at the contact patch under various surfaces and operating conditions. This article aims to enhance the understanding of the tire-ice contact interaction through experimental studies of pneumatic tires traversing over smooth ice. An experimental design has been formulated that provides insight into the effect of operational parameters, specifically general tire tread type, slip ratio, normal load, inflation pressure, ice surface temperature, and traction performance. The temperature distribution in the contact patch is recorded using a novel method based on thermocouples embedded in the contact patch. The drawbar pull is also measured at different conditions of normal load, inflation pressure, and ice temperatures. The measurements were conducted using the Terramechanics Rig at the Advanced Vehicle Dynamics Laboratory. This indoor single-wheel equipment allows repeatable testing under well-controlled conditions. The data measured indicates that, with the appropriate tread design, the wheel is able to provide a higher drawbar pull on smooth ice. With an increase in ice surface temperature, a wet film is observed, which ultimately leads to a significant decrease in traction performance.

The Influence of Isotropic Surface Roughness of Steel Sliders on Ice Friction Under Different Testing Conditions

Ice friction is affected by various system and surface-related parameters such as ice temperature, ambient air temperature and humidity, relative sliding velocity, specific surface pressures and surface texture (waviness, roughness) as well as the macroscopic geometry of the samples. The influences of these parameters cannot be easily separated from each other. Therefore, ice friction is a very complex tribological system and it is challenging to draw sound conclusions from the experiments. In this work, ice friction experiments with stainless steel samples that have different isotropic surface roughness values were carried out. Two tribological experimental setups were used: (i) an inclined ice track where the sliding velocity of the freely sliding steel samples was determined and (ii) an oscillating tribometer, where the coefficient of friction was assessed. For both experimental setups, the environmental parameters such as air temperature, relative humidity and ice surface temperature as well as the test parameters such as normal load and surface pressure were kept as constant as possible. The results of the experiments are discussed in relation to the ice friction mechanisms and the friction regimes.

On the warm bias in atmospheric reanalyses induced by the missing snow over Arctic sea-ice

Over the past decades, the Arctic has been warming more than any other region in the world with profound socio-economic consequences. One of the key elements for understanding this rapid climate change is the surface energy budget. However, in the Arctic this budget is not consistently described across the various climate models, reanalyses and observation products. Recognising the physical causes of these inconsistencies is highly relevant for improving climate predictions and projections. Here we show that a 5 to 10 °C warm bias of the sea-ice surface temperature in global atmospheric reanalyses and weather forecasts is mainly caused by a missing representation of the snow layer on top of the sea-ice. Due to the low thermal conductivity of snow compared to sea-ice, a thin snow layer reduces the conductive heat flux much more efficiently than sea-ice, and thus insulates the cold atmosphere from the relatively warm ocean.