Surface Snowmelt Research Articles

Toward a real validation of passive microwave snowmelt detection algorithms over the Antarctic Ice sheet

Antarctic Ice Sheet (AIS) surface snowmelt can profoundly impact climatological and hydrological processes, as well as energy and mass balances. Passive microwave remote sensing has proven highly effective in detecting snowmelt, and the accuracy of the algorithms is typically assessed using air temperature (Tair). Nonetheless, the occurrence of snowmelt cannot be solely determined by Tair being above the melting point, it can only provide evaluation of the algorithms rather than a real validation. This study is the first to conduct a reliable validation of six commonly used algorithms by using the melt rate data from a surface energy balance model, including the cross-polarized gradient ratio (XPGR) algorithm, the diurnal amplitude variation (DAV) algorithm, the Microwave Emission Model of Layered Snowpacks based (MEMLS-based) algorithm, the constant threshold algorithm (CTA), the Ashcraft and Long Algorithm (ALA), and the M + 30 K (M30 hereafter) algorithm. Results suggest that the M30 algorithm and MEMLS-based algorithm have overall better performances, with high overall accuracies (with a value of 95.81 % and 95.56 %) and high kappa coefficient (with a value of 0.69 and 0.68). Though Tair is not reliable for evaluating the algorithms, a threshold of Tair = − 0.8 ℃ can serve as an alternative criterion in the absence of melt rate data. Additionally, two algorithms with the highest accuracy were selected to investigate interannual snowmelt trends in the Antarctic and the sub-regions. The results show a significant increase in melt extent and density in the Wilkes and Adelie sub-region during the period 1979–2020.

Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals

Abstract. Greenland ice sheet mass loss continues to accelerate as global temperatures increase. The surface albedo of the ice sheet determines the amount of absorbed solar energy, which is a key factor in driving surface snow and ice melting. Satellite-retrieved snow albedo allows us to compare and optimise modelled albedo over the entirety of the ice sheet. We optimise the parameters of the albedo scheme in the ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) land surface model for 3 random years taken over the 2000–2017 period and validate over the remaining years. In particular, we want to improve the albedo at the edges of the ice sheet, since they correspond to ablation areas and show the greatest variations in runoff and surface mass balance. By giving a larger weight to points at the ice sheet's edge, we improve the model–data fit by reducing the root-mean-square deviation by over 25 % for the whole ice sheet for the summer months. This improvement is consistent for all years, even those not used in the calibration step. We also show the optimisation successfully improves the model–data fit at 87.5 % of in situ sites from the PROMICE (Programme for Monitoring of the Greenland Ice Sheet) network. We conclude by showing which additional model outputs are impacted by changes to the albedo parameters, encouraging future work using multiple data streams when optimising these parameters.

Temperature Response of Metabolic Activity of an Antarctic Nematode.

Because of climate change, the McMurdo Dry Valleys of Antarctica (MCM) have experienced an increase in the frequency and magnitude of summer pulse warming and surface ice and snow melting events. In response to these environmental changes, some nematode species in the MCM have experienced steady population declines over the last three decades, but Plectus murrayi, a mesophilic nematode species, has responded with a steady increase in range and abundance. To determine how P. murrayi responds to increasing temperatures, we measured metabolic heat and CO2 production rates and calculated O2 consumption rates as a function of temperature at 5 °C intervals from 5 to 50 °C. Heat, CO2 production, and O2 consumption rates increase approximately exponentially up to 40 °C, a temperature never experienced in their polar habitat. Metabolic rates decline rapidly above 40 °C and are irreversibly lost at 50 °C due to thermal stress and mortality. Caenorhabditis elegans, a much more widespread nematode that is found in more temperate environments reaches peak metabolic heat rate at just 27 °C, above which it experiences high mortality due to thermal stress. At temperatures from 10 to 40 °C, P. murrayi produces about 6 times more CO2 than the O2 it consumes, a respiratory quotient indicative of either acetogenesis or de novo lipogenesis. No potential acetogenic microbes were identified in the P. murrayi microbiome, suggesting that P. murrayi is producing increased CO2 as a byproduct of de novo lipogenesis. This phenomenon, in conjunction with increased summer temperatures in their polar habitat, will likely lead to increased demand for carbon and subsequent increases in CO2 production, population abundance, and range expansion. If such changes are not concomitant with increased carbon inputs, we predict the MCM soil ecosystems will experience dramatic declines in functional and taxonomic diversity.

Snowmelt detection on the Antarctic ice sheet surface based on XPGR with improved ant colony algorithm

ABSTRACT This study presents an XPGR coupled with an improved ant colony algorithm to automatically detect the Antarctic ice sheet surface snowmelt and acquire high-precision snowmelt information. This approach first enlarges the difference between dry snow and wet snow using the XPGR algorithm and then utilizes an enhanced ant colony algorithm to adaptively find the best threshold for segmenting dry snow and wet snow. The dissimilarity matrix, which determines the initial clustering centre and utilizes Levy flight to modify the clustering radius dynamically, is a major advancement to the ant colony algorithm. The method proposed in this study was compared to the standard XPGR algorithm from October 2017 to February 2018 and from October 2019 to February 2020 to evaluate the practicality and rationale of the proposed method. The further verification of six automatic weather stations (AWS) shows that the method proposed in this study has higher accuracy.

Spatiotemporal Distribution Characteristics of Fire Scars Further Prove the Correlation between Permafrost Swamp Wildfires and Methane Geological Emissions

Affected by global warming, methane gas released by permafrost degradation may increase the frequency of wildfires, and there are few studies on wildfires in permafrost regions and their correlation with climate and regional methane emissions. The northwestern section of the Xiaoxing’an Mountains in China was selected as the study area, and the spatial relationship between permafrost and spring wildfires was studied based on Landsat TM and Sentinel-2 data. Combined with monitoring data of air temperature, humidity, and methane concentration, the impact of methane emissions on spring wildfires was analyzed. The study shows that the spatial distribution of fire scars in spring is highly consistent with permafrost, and the change trend of fire scars is in line with the law of permafrost degradation. Wildfires occur intensively during the snow melting period in spring, and the temporal variation pattern is basically consistent with the methane concentration. The number of fire points was positively correlated with air temperature and methane concentration in March and April, and spring wildfires in permafrost regions are the result of a combination of rising seasonal temperatures, surface snow melting, and concentrated methane emissions. Larger areas of discontinuous permafrost are more prone to recurring wildfires.

Hydrologic modeling of a perennial firn aquifer in southeast Greenland

AbstractA conceptual model, based on field observations and assumed physics of a perennial firn aquifer near Helheim Glacier (southeast Greenland), is evaluated via steady-state 2-D simulation of liquid water flow and energy transport with phase change. The simulation approach allows natural representation of flow and energy advection and conduction that occur in vertical meltwater recharge through the unsaturated zone and in lateral flow within the saturated aquifer. Agreement between measured and simulated aquifer geometry, temperature, and recharge and discharge rates confirms that the conceptual field-data-based description of the aquifer is consistent with the primary physical processes of groundwater flow, energy transport and phase change. Factors that are found to control simulated aquifer configuration include surface temperature, meltwater recharge rate, residual total-water saturation and capillary fringe thickness. Simulation analyses indicate that the size of perennial firn aquifers depends primarily on recharge rates from surface snowmelt. Results also imply that the recent aquifer expansion, likely due to a warming climate, may eventually produce lakes on the ice-sheet surface that would affect the surface energy balance.

Forest leaf litter nutrient discharge patterns in snowmelt surface runoff and watershed scale remote sensed simulation

The leaf litter decomposition is the important chain for the nutrient cycle in forest ecosystem, but its degradation dynamics and pulse discharge patterns in freeze-thawing watershed needed complete understanding. By integrating field observations and MODIS data, the temporal-spatial distributions of snow coverage and forest leaf litter biomass were analyzed. The critical period for snowmelt runoff under warming temperature and the relatively slow degradation patterns were identified. The on-site observations snowmelt runoff showed discharge concentration and fraction dynamics of typical forest leaf litter nutrients (carbon, nitrogen, and phosphorus) in thawing period. The snowmelt runoff flow and nutrient flux observed the linear regressions with the increased temperature from −8 °C to 6 °C (r2 = 0.443–0.987). The concentration of TOC, TN, and TP reached summit value around 50.0, 6.0, and 0.5 mg L−1 in the snowmelt runoff, respectively. The fraction analysis proved that the much high composition of dissolved organic fraction and the biggest organic phosphorus percentage was 94%. The comparison experiments of forest soil with or without leaf litter cover demonstrated that the leaf litter caused a lower discharge load in the snowmelt flow, and the leaf litter cover can decease the potential transport capability of the snowmelt runoff. Coupled with remote sensing data, the watershed leaf litter nutrient discharge model was developed with snowmelt hydrological process mode. The watershed averaged discharge of TOC, TN, and TP from deciduous broad-leaved forest leaf litter was around 851.99, 75.05, and 9.78 mg·m−2, respectively. The yearly simulation showed the spatial distribution variance of the nutrient discharge loads were held by different forest types, elevations, and slopes. The critical loss area identification provided new mitigations solution. The findings suggested that seasonal discharge of forest leaf litter nutrient in thawing period acted as a key contributor to watershed water pollution.

Intercalibration of Brightness Temperatures From FY-3 MWRI for Surface Snowmelt Detection Over Polar Ice Sheets

Surface snowmelt is a vital environmental parameter that affects energy exchanges between polar ice sheets and the atmosphere. Due to the difficulties of continuous in-situ measurements, passive microwave remote sensing technology has become a major method for obtaining ice sheet surface snowmelt states over large areas. Feng Yun-3 (FY-3) series satellites, the second generation of Chinese polar-orbiting meteorological satellite missions, have great potential for providing long-term polar ice sheet surface snowmelt state products. In this study, we establish a monthly inter-calibration model to synergize brightness temperatures from the Microwave Radiation Imager (MWRI) aboard different FY-3 satellites. Based on the calibrated continuous brightness temperature record, an improved snowmelt algorithm is proposed by using an adaptive thresholding method, which does not rely on in-situ observation data. After inter-calibration, the consistency of the melt extent obtained by different sensors is considerably better than before, with the bias decreasing from 85 pixels to 3 pixels in the Greenland Ice Sheet (GrIS) and from 16 pixels to 6 pixels in the Antarctic Ice Sheet (AIS). Evaluation of the snowmelt result is conducted with the automatic weather station (AWS) air temperature, and a promising accuracy is found with an overall accuracy above 92% in the AIS and approximately 86% in the GrIS. This study provides new possibilities for a long-term continuous snowmelt product by connecting FY-3B, FY-3C, FY-3D, and its successors FY-3F and FY-3G. The inter-calibration coefficients and FY-3 crossing times are available at https://doi.org/10.6084/m9.figshare.20657712.v1.

Sea Surface States Detection in Polar Regions Using Measurements of Ground-Based GNSS Interferometric Reflectometry

This article analyzes the interferometric measurements of ground-based global navigation satellite systems (GNSSs) stations and proposes a novel method for sea surface states detection. The novel technique benefits from a cost-effective data collection from a large number of global GNSS stations. In this study, we extend a traditional GNSS interferometry reflectometry (GNSS-IR) model so that it can be applied to a multilayer surface by considering the surface roughness, total reflectivity, and penetration loss in multilayer situations. Based on this model, the wavelet analysis is used to perform parameterization on the interferometric observations represented by the signal to noise ratio (SNR). An integration factor and power curve are also proposed to characterize the surface state transition. One-year data from an Arctic geodetic GNSS station in the north of Canada are collected for analysis to validate the proposed approach in comparison with the existing methods based on the amplitude and damping factors. The results show that the new method demonstrates good usability and sensitivity to detect surface state transitions, e.g., icing, snowfall, and snow melting. However, the amplitude and damping factor-based methods derived from the single-layer model are only able to detect the pure ice surface and cannot respond to thick snow conditions. Finally, the high-resolution spaceborne images confirm the reliability of this method, exhibiting a great potential for long-term coastal sea surface detection based on the global geodetic GNSS stations and later being expected to be applied to sense cryosphere surface states.

Forest Leaf Litter Nutrient Discharge Patterns in Snowmelt Surface Runoff and Watershed Scale Remote Sensed Simulation

Forest Leaf Litter Nutrient Discharge Patterns in Snowmelt Surface Runoff and Watershed Scale Remote Sensed Simulation

Meteorological parameters and water balance components of Priyadarshini Lake at the Schirmacher Oasis, East Antarctica

The meteorological parameters and water balance components of Priyadarshini Lake at Schirmacher Oasis, East Antarctica, were studied using meteorological data procured from the India Meteorological Department (IMD) weather station, Maitri and field observations in summer seasons of 2017–2018 and 2018–2019. Meteorological data was analysed (daily temporal and diurnal variation) for 2018, and the water balance components were estimated for January–February of 2018. The present work revealed the status of meteorological parameters (air temperature, relative humidity, wind speed, and snowfall) at Schirmacher Oasis compared to long-term historical trends at the east and west regions of Antarctica. As Priyadarshini Lake is non-endorheic, it transferred freshwater to the sea at the rate of ∼335 × 103 m3/month during summer season of 2018. The water consumption by Maitri station (term W) is very minimal compared to other terms and does not play a substantial role in the lake's water balance. The limited availability of topographic and historical hydro-meteorological data limits the application of physically based hydrological models to simulate snow melt surface runoff at the inflow and assess the impact of climate change on hydrological regimes of the lake. Thus, long term monitoring of the lake with a permanent gauging network for inflows and outflow will pronounce our understanding and enable the option to assess linkage with changing climate.

Influence of aerosol radiative effects on surface temperature and snow melt in the Himalayan region

Recent increases in surface temperature and snow melt acceleration in the Himalayan region are influenced by many factors. Here we investigate the influence of absorbing aerosols, including black carbon and dust, on surface temperature and snow melt in western, central, and eastern parts of the India-Nepal Himalayan region (INHR). We compare 40-y simulations (1971–2010) one with all evolving forcing agents representative of a present-day aerosol scenario, compared to a low aerosol forcing scenario. The difference between these scenarios shows a significant increase in surface air temperature, with higher warming in parts of Western and Central Himalaya (~0.2–2 °C) in the months of April and May. Higher absorbing aerosol (BC and dust abundance) both at the surface and in the atmospheric column, in the present-day aerosol simulations, led to increases in atmospheric radiative forcing and surface shortwave heating rate forcing (SWHRF), compared to the low aerosol forcing case. Therefore, the absorbing aerosols cause anomalous atmospheric heat energy transfer to land due to high surface SWHRF and changes in surface energy flux, leading to snow melt. The present model version did not parameterize snow albedo feedback, which would increase the magnitudes of the changes simulated here.

Spatial and Temporal Variations in Pigment and Species Compositions of Snow Algae on Mt. Tateyama in Toyama Prefecture, Japan.

Snow algae are photosynthetic microbes that inhabit the melting snow surface in alpine and polar regions. We analyzed the pigment and species composition of colored snow collected on Mt. Tateyama in Japan during the melting seasons of 2015 and 2016. High-performance liquid chromatographic analyses of the pigments extracted from the colored snow showed that their composition varied within the study area and were classified into four types: Type A (astaxanthin-monoester dominant), Type B (medium astaxanthin-monoester content), Type C (abundant primary carotenoids and free-astaxanthin), and Type D (abundant primary carotenoids and astaxanthin diesters). Types A and B were most commonly observed in the study area, whereas Types C and D appeared only at specific sites. Analysis of the 18S ribosomal RNA (18S rRNA) gene revealed six major amplicon sequence variants (ASVs) of snow algae, belonging to the Sanguina, Chloromonas, and Chlainomonas groups. The relative abundance of the algal ASVs showed that Sanguina was dominant (>48%) in both Types A and B, suggesting that the difference in astaxanthin abundance between the two types was caused by the production of pigments in the algal cells. The algal community structures of Types C and D differed from those of Types A and B, indicating that the primary carotenoids and astaxanthin diesters were derived from certain algal species in these types. Therefore, astaxanthin-rich Sanguina algae mostly induced the red snow that appeared widely in this alpine area; however, they were partially dominated by Chloromonas or Chlainomonas algae, causing different pigment compositions.

Impact of Nitrate Vulnerable Zones and Catchment Sensitive Farming on Water Quality in UK: Case Study of Ingbirchworth and Scout Dyke Reservoirs

The rivers and water streams are considered as a source of fresh drinking water for the human being on earth. The main source of water entering to these reservoirs is surface run off, snow melting and underground water. The water at the river’s mouth is generally in the form of small streams which are considered clean but as they flow down the catchment, pollutants and nutrients start to enter in larger amounts due to anthropogenic activities and advanced land use by human beings. As per inspection of chief inspector “Drinking Water Inspectorate (DWI)” in 2016, out of more than 4600 water bodies and 3700 rivers in England, only one sixth could get “good” status and two third could get “moderate” status as per European union standards. This is though a good achievement in Europe but alarming also, as all rivers are required to have achieved specified “good” standards by 2021 (extended to 2027 for some categories). This phenomenon is pronouncing more complications in drinking water reservoirs or compensatory reservoirs from where water is taken out to utility companies and treated for domestic water supply incurring an enormous cost on its treatment before human consumption. The clean water standards can be achieved only if a strict control is implemented on entry of pollutants/ nutrients from surface run off using thorough catchment scale sensitive strategies. UK has been implementing strict measures under Environment Agency (EA), Department for Environment, Food and Rural Affairs (DEFRA) and other organizations like “Natural England”, “River Trust” and water utility/ supply companies to achieve desired standards of water quality in rivers by managing the whole catchment as per European union water framework directive (EU WFD) 2000.The catchment sensitive farming and nitrate vulnerable zones policies were started in 1992 and has been in full practice by implementing different stewardship schemes and fertilizers control measures in farmlands and arable lands. Ingbirchworth reservoir and Scout Dyke compensatory reservoir have been under catchment sensitive stewardship schemes to control quantities of nutrients especially nitrates and other pollutants since 2006 to maintain good quality water reservoirs for drinking and compensation to Don river. A partial success has been achieved in controlling the values of nitrates, phosphates, and suspended solids to enter from catchment farmlands by controlling the use of slurry/ fertilizers and implementation of good farming techniques. However, temporal and special variations show a variable result of presence of nitrates, phosphates and suspended solids at different streams in different times, more than specified limits of 11.3mg/L, 0.1mg/L and 25mg/L respectively. This requires more holistic efforts to control the bad practices in farming in adjacent farm/arable lands and improvements in stewardship schemes for catchment sensitive farming in Ingbirchworth areas.

A model for estimating snow depth on a far-infrared system snowmelt surface and its optimum operating conditions

A model for estimating snow depth on a far-infrared system snowmelt surface and its optimum operating conditions

Recent changes in pan-Antarctic region surface snowmelt detected by AMSR-E and AMSR2

Abstract. Surface snowmelt in the pan-Antarctic region, including the Antarctic ice sheet (AIS) and sea ice, is crucial to the mass and energy balance in polar regions and can serve as an indicator of climate change. In this study, we investigate the spatial and temporal variations in surface snowmelt over the entire pan-Antarctic region from 2002 to 2017 by using passive microwave remote sensing data. The stable orbits and appropriate acquisition times of the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) and the Advanced Microwave Scanning Radiometer 2 (AMSR2) enable us to take full advantage of daily brightness temperature (Tb) variations to detect surface snowmelt. The difference between AMSR-E/2 ascending and descending 36.5 GHz Tb values in vertical polarization (DAV36) was utilized to map the pan-Antarctic region snowmelt, as this method is unaffected by snow metamorphism. We evaluated the DAV36 algorithm against ground-based measurements and further improved the method over the marginal sea ice zone by excluding the effect of open water. Snowmelt detected by AMSR-E/2 data was more extensive and persistent than that detected by the Special Sensor Microwave/Imager (SSM/I) data. Continuous melt onset (CMO) ranged from August in the marginal sea ice zone to January in the Antarctic inland, and the early transient melt events occurred several days to more than 2 months earlier. The pan-Antarctic region CMO was significantly correlated (R=0.54, p<0.05) with the summer Southern Annular Mode (SAM). The decreased AIS melt extent was very likely linked (R=-0.82, p<0.01) with the enhanced summer SAM.

Source, timing and dynamics of ionic species mobility in the Svalbard annual snowpack

Nearly all ice core archives from the Arctic and middle latitudes (such as the Alps), apart from some very high elevation sites in Greenland and the North Pacific, are strongly influenced by melting processes. The increases in the average Arctic temperature has enhanced surface snow melting even of higher elevation ice caps, especially on the Svalbard Archipelago. The increase of the frequency and altitude of winter “rain on snow” events as well as the increase of the length of the melting season have had a direct impact on the chemical composition of the seasonal and permanent snow layers due to different migration processes of water-soluble species, such as inorganic ions. This re-allocation along the snowpack of ionic species could significantly modify the original chemical signal present in the annual snow. This paper aims to give a picture of the evolution of the seasonal snow strata with a daily time resolution to better understand: a) the processes that can influence deposition b) the distribution of ions in annual snow c) the impact of the presence of liquid water on chemical re-distribution within the annual snow pack. Specifically, the chemical composition of the first 100 cm of seasonal snow on the Austre Brøggerbreen Glacier (Spitsbergen, Svalbard Islands, Norway) was monitored daily from the 27th of March to the 31st of May 2015. The experimental period covered almost the entire Arctic spring until the melting season. This unique dataset gives us a daily picture of the snow pack composition, and helps us to understand the behaviour of cations (K+, Ca2+, Na+, Mg2+) and anions (Br−, I−, SO42−, NO3−, Cl−, MSA) in the Svalbard snow pack. We demonstrate that biologically related depositions occur only at the end of the snow season and that rain and melting events have different impacts on the snowpack chemistry.

Enhanced winter snowmelt in the Antarctic Peninsula: Automatic snowmelt identification from radar scatterometer

Surface snowmelt affects the energy balance through melt-albedo feedback and may endanger the ice shelves in the Antarctic Peninsula (AP) through hydrofracture. Here, we introduce an automatic snowmelt identification algorithm based on Quick Scatterometer and Advanced Scatterometer. The proposed method can provide self-adaptive thresholds for snowmelt detection based on Rosin thresholding, and is able to detect weak melt signals with a wavelet denoising procedure. Results suggest the AP surface snowmelt has slightly declined during 1999–2018 in the context of recent cooling. However, winter melt index (i.e., melt days times the area of melting) has significantly increased (above the 99% confidence level) with a rate of 83% decade−1. Unprecedented winter snowmelt was found in 2015/2016 when about one-third of the AP experienced snowmelt in late May. This may be attributed to the intrusions of marine air and the enhanced föhn-driven warming resulted from the abnormal northwesterly flow driven by a significant deepening of the Amundsen Sea Low.

Atmospheric Moisture as a Factor of Land Degradation Neutrality in Forest–Steppe Landscapes

Analysis of data from meteorological observations near the Kursk Biosphere Station, Institute of Geography, Russian Academy of Sciences, for the past 40 years shows a steady increase in temperature against the background of an increasing deficit of precipitation in this area. At the same time, the precipitation is characterized by a high instability and a contrast distribution by year, as well as by an increase in the number and duration of dry periods. Precipitation (in particular, snow accumulation) is an important source of moisture and a significant factor of functioning for forest–steppe landscapes. It is shown that different landscape types can have a two- to fourfold difference in snow accumulation, which plays a decisive role in the formation of moisture reserves. Agrolandscapes are deficient in moisture, which contributes to deeper freezing of soils, as well as to the deterioration of their water permeability and the development of a surface snowmelt runoff from fields, which leads to landscape degradation. The essence of the concept of land degradation neutrality, which mainly concerns the maintenance of global sustainable land use, is to obtain objective parameters for state of landscapes and to assess the proportion of lands exposed to degradation. Atmospheric moisture in forest–steppe landscapes is a significant factor determining their functioning and can be used as a local indicator of the concept.

Thermal performances of porous snow by a hydronic heating system at different weather conditions

The snow on the road in the cold regions is easy to cause slippery conditions, which are dangerous for vehicles and people. To remove the slippery conditions, the hydronic snow melting system has been applied to remove the snow on the road. This study proposed a transient finite volume model with snow porous characteristics, to analyze the snow melting performances by a hydronic heating system. Three primary environmental parameters (snow thickness, wind velocity, and air temperature) were selected to compare the average road surface temperature and snow melting ratio. Then, the snow melting performances using a hydronic road heating system were analyzed. The results showed that the snow melting ratio was rapidly dropped as the snow thickness was increased from 10 to 90 mm. The snow thickness had a slight influence on the average road surface temperature in the melting process, whereas it had a significant impact after the snow was completely cleared. When the wind velocity was increased to 5 m s−1, the critical melting ratio appeared at around 0.7. The wind velocity had a significant influence on average road surface temperature when the average road surface temperature increased more than 273.15 K. There is a critical air temperature existed between 263.15 and 258.15 K, which limits the snow melting process at current supplied fluid temperature (313.15 K), indicating that more energy was need to supply to overcome cold weather. This study offers a good reference for the design of a hydronic snow melting system in severely cold regions.