Influence of Particulate Matter on the Albedo of Qiangtang No. 1 Glacier, Tibetan Plateau

Abstract

The melting behavior of glaciers on and around the Tibetan Plateau is strongly influenced by their albedo. In this paper, we report continuous observations made on the Qiangtang (QT) No. 1 Glacier, located in the central Tibetan Plateau, during its 2013–2015 melting seasons. Surface snow on the QT No. 1 Glacier mainly had a dust content less than 600 ppm and a black carbon (BC) content less than 10 ppb. A strong negative correlation was observed between albedo and dust content up to a threshold concentration of 1000 ppm, although albedo remained constant when dust concentrations increased above this value. The radii of snow particles showed a log-normal distribution that had a mean value of ~500 μm, but maximum and minimum values of 2539 μm and 40 μm, respectively. Snow density showed a normal distribution with a total range of 193–555 kg/m³, although most snow had a density of 400 kg/m³. Snow, ice, and aerosol radiative (SNICAR) simulations showed that dust and BC in the surface snow of the QT No. 1 Glacier reduced the snow and ice albedo by 5.9% and 0.06%, respectively, during the ablation season in 2015; however, the simulated particle impact was greater than the albedo reduction measured from field data. We interpret that dust has played a significantly more important role in melting of the QT No. 1 Glacier than BC over the study period, which is mainly due to the scarcity of human activities in the region and the low concentration of BC being produced.

1. Introduction

More than 77,000 glaciers are present within the Asian Water Tower, and they cover a total area of ~83,350 km² [1]. Recent work has shown that hydroclimatic conditions within the Asian Water Tower are imbalanced due to the accelerated melting of ice and snow [2]. Most glaciers in this region have retreated over the past two decades [3]; indeed, glacial mass has reduced across the entire Asian Water Tower at an average rate of −21.1 ± 4.8 Gt per year during 2000–2019 [4]. Glaciers also record spatially heterogeneous melting, with the most serious retreats having been documented in the Himalayas and south-eastern Tibetan Plateau. The central Tibetan Plateau region has also been severely affected, although some glaciers on the northern and northwest margins of the Tibetan Plateau have shown minor accumulation and growth in recent years [5,6,7].

Temperature and precipitation are the main factors that determine whether a glacier will advance or retreat [7,8]. Solar radiation is the main source of energy that drives melting of snow and ice, with short-wave radiation being a significant contributor [9]. The effects of short-wave radiation are especially apparent in mountain glaciers, where solar radiation provides 75% of the total energy received [10]. The amount of energy absorbed by a glacier mainly depends on the albedo of its surface: for example, the albedo of fresh snow can reach values exceeding 0.9, while the albedo of impure snow and ice is less than 0.2 [10,11]. The main factors that affect the albedo of snow and ice are impurities (i.e., dust, black carbon, and volcanic ash), snow grain size, snow water content, snow density, snow depth, cloud layer, and sun altitude angle [12,13,14,15,16,17].

Previous research has shown that the mass balance of glaciers on the Tibetan Plateau correlates with variations in albedo, indicating that the latter can be used as an important metric to monitor changes in the former [18,19,20,21]. The measured albedo of the Muztagh Glacier in the Kunlun Mountains, Tibetan Plateau, shows a strong negative correlation with the concentration of particles in snow and ice [22]. Observations of the Zhadang Glacier show that the albedo of black carbon (BC) decreased by 28% during the glacier’s ablation period, while dust caused a reduction in albedo of 56%; thus, dust was considered as the main driving force for albedo reduction and glacial melting in the region [23]. Field observations made of the Muji Glacier show that the BC content of fresh snow is low, although BC accumulates on the surface of a glacier and reduces albedo during melting periods of snow and ice [24]. New snowfall on the surface of the Laohugou No. 12 Glacier contained average concentrations of 291.6 ppb BC and 38.4 ppm dust; however, during melting of snow and ice, both BC and dust accumulate on the surface of the glacier and become locally enriched. The average radiative forcing of BC and dust during the melting season of the Laohugou No. 12 Glacier was 17.5 W/m² and 11.8 W/m², respectively, indicating that BC played a major role in accelerating its ablation [25]. A study of the Urumqi No. 1 Glacier in the eastern Tien Shan Mountains showed that temporal and spatial variations in albedo across the glacier were mainly controlled by the transition in dominant surface type from snow to bare ice. These data suggested that surface albedo was homogenous during in the early ablation season, although became notably heterogeneous during the middle and late ablation season, and even showed a general increase with elevation, especially around the equilibrium line [26]. A study of snow and ice albedo in the Qilian Mountains indicated that the average albedo during summer can be considered as an effective proxy for changes in glacial mass [27]. Nonetheless, although much research has been performed on glacier albedo on the Tibetan Plateau, there are few studies that have investigated glacier albedo changes by using long-term field observations and simulations, especially in the central Tibetan Plateau.

Qiangtang (QT) No. 1 Glacier (88.69° E, 33.29° N) is located ~20 km to the northwest of Shuanghu County, Tibetan Autonomous Region, in the central Tibetan Plateau (Figure 1a). This region is locally known as the Awu Snow Mountain and has a maximum altitude of 6100 m. It is a typical modern continental glacier that is oriented northwest–southeast and has a slope of less than 10° with no abrupt changes in terrain. The average thickness of the QT No. 1 Glacier is 51.28 m, its thickest point lies at 5822 m above sea level, its ice thickness is 132.15 m, and its volume of ice is 0.1236 km³ [28]. In this paper, we made field observations of snow and ice albedo and compared them with simulated results produced using the snow, ice, and aerosol radiative (SNICAR) online model. The dust and BC contents of snow and ice were obtained via laboratory analysis of samples collected from the study area, which allowed the impact on the snow and ice albedo to be quantified. These results expand our understanding of changes in the mass of glaciers and other water resources on the Tibetan Plateau.

2. Data and Methods

2.1. Field Observation

The albedo of the QT No. 1 glacier was measured, and samples were collected between the months of June and August in 2013, May and July in 2014, and June and August in 2015. Observations mainly included measurements of glacier albedo, snow particle size, and snow density, and surface snow samples were collected. Spectral data were measured with a MS-720 portable spectral radiometer manufactured by the EKO company, Tokyo, Japan, which has an effective wavelength of 350–1050 nm.

2.1.1. Observation and Calculation of Glacier Albedo

Measurements of albedo during the three observation periods were only taken in suitable weather, such as cloudless skies or low cloud cover. Measurements were taken at approximately equal time intervals between 10:00 and 16:00 using a 45° viewing angle probe. The same orientation was used at all times, which involved facing the sun directly to minimize the effects of shadows during the measurement. The probe was used at a consistent distance of 20 cm from the snow surface. At each site, measurements were taken using a white board and on the snow itself. Ten measurements were taken at each observation point and an average value was then calculated.

Albedo was calculated by combining the standard solar incident radiation spectrum provided by the American Society for Testing and Materials (ASTM G-173-03) using the following Equation (1).

$$\alpha =\frac{{\displaystyle {\int }_{{\lambda }_1}^{{\lambda }_2}\alpha \left(\lambda \right)F_{\lambda }^{\downarrow }d\lambda }}{{\displaystyle {\int }_{{\lambda }_1}^{{\lambda }_2}{F}_{\lambda }^{\downarrow }d\lambda }}$$

(1)

where $\alpha$ represents the albedo, $\lambda$ represents the wavelength, and $F_{\lambda }^{\downarrow }$ represents the solar incident radiation in the standard curve. In this study, ${\lambda }_1$ and ${\lambda }_2$ were 350 nm and 1050 nm, respectively.

2.1.2. Snow Particle Size Measurement

Snow particle size was measured by using both a portable high-definition digital microscope with a magnification of ~20–500 times and a calibration board with a 1-mm checkerboard pattern (Figure 2). Initially, measurements were made using a standard ruler. After adjusting the microscope to the appropriate magnification, the ruler was measured for calibration purposes and pictures were taken of snow particles to calculate their size. After this step, the magnification was fixed, the snow sample to be measured was sprinkled onto the checkerboard calibration board, and photographs were taken quickly using a high-definition digital microscope. Finally, snow particles were measured from photographs of snow particles taken in the field using Cooling Tech software. The in-field measurement process was conducted quickly in order to prevent the snow particles from melting and deforming.

2.1.3. Measurement of Snow Density and Depth

Snow density was calculated by filling a stainless-steel cylinder of known volume and weight with snow in its natural state. Density was calculated using the equation ρ = m/v, where ρ is density, m is mass, and v is volume. Snow depth was measured by using the traditional method of digging snow pits.

2.1.4. Sample Collection

Thirteen observations (red circles in Figure 1c) were made on the QT No. 1 Glacier in 2013, and 12 observations were made in 2014 and 2015 (blue triangles in Figure 1c). Surface snow and ice samples were collected within 3–5 cm of the surface after each observation. Disposable gloves were worn during the sampling process and all sampling sites were located in downwind areas to avoid contamination of the samples. Collected samples were stored in Nalgene 1000-mL wide-mouth bottles and 50 mL vials.

2.2. Laboratory Analysis

Snow and ice samples collected in the field were returned to the laboratory, and sample pre-treatment was completed in the 1000-level ultra-clean laboratory at the Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Lhasa, using a Teflon filter with a pore size of 0.45 μm and a diameter of 47 mm, produced by Millipore. The BC content was measured using a single-particle soot photometer (SP2) analyzer housed in the Key Laboratory of Tibetan Environmental Changes and Land Surface Processes, Chinese Academy of Sciences.

3. Results

3.1. Particulate Characteristics

3.1.1. Temporal and Spatial Variations in Dust on the QT No. 1 Glacier during the Summer

Very little snow was documented on the QT No. 1 Glacier in 2014, such that its surface was essentially bare ice; as such, we did not analyze temporal and spatial variations in the dust of that year in this study. Here, we report analyses that document spatiotemporal variations in the characteristics of surface dust on the QT No. 1 Glacier in 2013 and 2015, as shown in Figure 3 and Figure 4, respectively. In the following sections, sample numbers are reported using “QT”, which represents Qiangtang, followed by the observation date and observation point.

In general, significantly more dust was observed in snow on the surface of the QT No. 1 Glacier in 2013 than in 2015. The highest dust concentration exceeded 4000 ppm in the 2013 samples, with samples taken at observation points 10 (sample QT20130812-10) and 11 (sample QT20130812-11) on 12 August 2013, recording 4185 ppm and 3183 ppm of dust, respectively, although the dust concentrations of most of the samples were less than 600 ppm. During the observation period in 2015, the highest dust content recorded in snow on the surface of the QT No. 1 Glacier was 182 ppm in sample QT20150813-5. Figure 4 shows that all dust contents from 2015 were less than 200 ppm.

We speculate that very different intensities of summer snowfall in 2013 and 2015 account for this notable difference in the glacier’s surface snow content between each year. Since no rain gauge was erected during the observation period, only snowfall events were recorded, and no accurate quantitative description of snowfall could be made. According to the observation records, snow fell continuously during the first ten days of July 2013, yet very little fell afterwards. Figure 3 shows that dust readily accumulated on the surface of the glacier from 21 July to 12 August in 2013; however, during the observation period in 2014, the surface of the glacier was almost bare and dust particles were washed away when the glacier melted. Figure 4 shows that the dust particles were enriched on the glacier surface in early June 2015; however, between middle to late June and early July in 2015, dust accumulation on the ice surface was significantly weaker. We suggest that this was mainly due to more snowfall having occurred during this period, as the depth of the snow crater at the top of the glacier reached 60 cm, which was the largest of all measurements taken during the three-year observation period. Dust was enriched on the glacier’s surface from middle to late July, but this concentration had decreased significantly by the middle of August and was lower than that recorded in 2013.

3.1.2. Relationships between Dust and Albedo

The dust concentration on the QT No. 1 glacier showed notable variation throughout 2013, although was typically less than 1000 ppm. The albedo ranged between 0.2 and 0.9, although was mostly greater than 0.5 (Figure 5a). The albedo decreased rapidly as dust concentration increased up to 1000 ppm; however, at dust concentrations greater than 1000 ppm, the albedo was more stable, only recording small changes with further dust accumulation (Figure 5a). The asterisk shown in Figure 5a marks an observation point that had exposed abundant water on the glacier, which could be clearly seen with the naked eye. Although the particle content at this observation point was low, the albedo was also very low; thus, water content of a snow layer has a strong influence on albedo, although this effect was not analyzed in detail in this paper. The dust content of the QT No. 1 Glacier in 2014 was lower than that in 2013, and mainly less than 250 ppm, which correlated with an albedo greater than 0.5 (Figure 5b). Additional observations showed that the dust content of surface snow in 2015 was less than 150 ppm, which is significantly lower than that recorded during the previous two years, and the albedo in 2015 had a value greater than 0.5 (Figure 5c). We offer two explanations for this phenomenon: (1) during the observation period in 2014, the surface of the glacier was extremely bare, and melting of the glacier melted caused widespread erosion and loss of dust particles; and/or (2) observations show that the QT No. 1 Glacier had the thickest snow cover in 2015 out of the entire study period, which indicates that the snow did not completely melt at the end of the observation period. As a result, dust enrichment was not as obvious when compared to the previous two years, resulting in a relatively low dust concentration in 2015.

Combined observations made during the three-year ablation period (Figure 5d) are generally consistent with the individual results collected in 2013, showing that a dust concentration below 1000 ppm has a significant impact on snow’s albedo.

3.1.3. Temporal and Spatial Variations of Black Carbon on the QT No. 1 Glacier during the Summer

The BC content of some surface snow samples collected from the QT No. 1 Glacier in 2015 was also examined using an SP2 analyzer. Our results show that the BC content of the surface snow on the QT No. 1 Glacier was very low during the observation period: total concentrations did not exceed 10 ppb, although the BC content in most areas on the glacier was less than 5 ppb (Figure 6). The BC content of surface snow on the QT No. 1 Glacier during the observation period was relatively high in early June, reached its minimum level in early July, and gradually increased from the end of July to the middle of August. The change correlates strongly with the changing dust concentrations documented on the glacier’s surface snow. As the rainy season in the study region typically does not begin in early June, the QT No. 1 Glacier showed only minor melting; however, sublimation allowed particles to accumulate on the glacier’s surface before this time, as shown by the high concentrations of BC documented in early June. Snow on the QT No. 1 Glacier increased significantly from the middle of June onwards but began to decrease around the middle to the end of July. Therefore, the BC concentration of surface snow on the QT No. 1 Glacier was low in early July and melting of the glacier intensified after late July, which allowed enrichment.

3.1.4. Relationship between BC and Albedo

Black carbon has a strong absorption effect on solar radiation, especially in the visible light band; for example, 10–100 ppb of BC in snow can reduce its albedo by 1–5% [29,30,31]. Nonetheless, the BC concentration and albedo of surface snow studied from the QT No. 1 Glacier in 2015 are poorly correlated, with notable increases in BC concentration only showing a minor decrease in albedo (Figure 7). We consider that there are a range of complex and diverse factors that affect snow albedo, even though BC is approximately 50-times more effective at absorbing solar radiation than dust, and approximately 200-times more effective than volcanic ash. In addition to impurities (e.g., dust and BC), other factors, such as snow particle size, snow water content, and snow density, also affect albedo. In addition, the BC content in the surface snow of the QT No. 1 Glacier was relatively low–mostly less than 5 ppb, although the dust content was relatively high, such that the correlation between albedo and BC concentration in surface snow in 2015 was not significant. The contribution of an individual factor to reducing albedo is difficult to identify when multiple factors operate simultaneously in the same snowfield [32]. As such, we simulated the contribution of particulate matter to reducing the albedo of snow and ice using SNICAR; the results of this modeling are presented in the discussion section.

3.2. The Properties of Snow and the Influence of Other Factors

3.2.1. Snow Particle Size

Several photographs of snow particles from the QT No. 1 Glacier were taken using a portable photomicroscope. From these, 3330 measurements of snow particle sizes were made, with most being irregular in shape, although we noted that older snow tended to be more circular than younger snow. Figure 8 shows the measured particle size distribution, which has an approximately log-normal distribution. Snow particle radii ranged from 2539 μm to 40 μm, with the most frequent radius being ~500 μm. Figure 9 shows the relationship between albedo of the QT No. 1 Glacier and particle size for data collected in 2015; these data show that albedo decreases significantly as particle size increases.

3.2.2. Snow Density

Snow density represents the difference in the softness of snow, with old and new snow often showing significant differences. Measurements of snow density on the surface of the QT No. 1 Glacier show a range of values between 193 kg/m³ and 555 kg/m³, with a median value of approximately 400 kg/m³, which roughly fit a normal distribution (Figure 10). We note, however, that snow density values of 193 kg/m³ that were measured during snowfall events were not included in the fitting procedure.

These data show an inverse relationship between density and albedo (Figure 11). Increases in snow density are caused by the compaction of snow, which transforms fresh snow to grain snow, and then grain snow to glacier ice. Other properties of snow cover also change as the density increases, such as an increase in snow particle size and the continuous deposition of pollutants on the snow surface, all of which are factors that reduce albedo. Therefore, the decrease in albedo cannot be simply attributed to an increase in snow density.

3.2.3. Snow Surface Properties and Their Reflectance Spectra

Albedo observations were conducted during multiple ablation seasons on many types of glacier surface coverage, including fresh snow and ice-covered cryoconite. The reflectance spectra of each type of surface were different, although each showed the same general trend (Figure 12). Photographs in Figure 12 parts (a) to (f) show the evolution on the QT No. 1 Glacier’s surface, from fresh snow to being covered with cryoconite. This process was associated with the aging of the snow and an increase in pollutants, such that the albedo gradually decreased, and the reflection spectrum in the visible and near-infrared bands decreased significantly. The reflection spectrum shown in Figure 12d is significantly different from that of other snow surfaces, which is due to the snow containing a large amount of water. This water reduced the particulate matter content of the snow and thus reduced its albedo. The reflectance spectrum shown in Figure 12d is also notably lower than those for other snow cover types, especially in the near-infrared band, and there are other significant differences in albedo that represent unusual snow-surface characteristics. For example, enrichment of particulate matter clearly reduces the amount of reflected light at visible and near-infrared wavelengths. Figure 12g plots all spectra on the same diagram for ease of comparison

Snow has a certain degree of transparency, although it becomes opaque when it reaches a particular thickness; thus, the surface beneath thin snow layers also influences albedo. Most glaciers have relatively thin surface snow. During the ablation periods of the QT No. 1 Glacier, the surface snow thicknesses were consistently less than 100 cm, with mean values of ~30 cm. During field work, we compared the albedo before and after the removal of surface snow. For example, on 16 June 2015, after a snowfall event on the QT No. 1 Glacier, we removed 9.5 cm of surface snow observation point 3 to expose the ice surface. We subsequently used a brush to remove residual snow particles and measure the albedo of the new surface. The blue line in Figure 13 shows the reflection spectrum before removing the surface snow, and the red line shows the post-removal spectrum. A comparison of both curves shows a significant reduction in reflectance after removing the surface snow and the albedo decreased from 0.9 to 0.5 (Figure 13). Thus, the presence or absence of surface snow has a significant effect on a glacier’s albedo.

4. Discussion

Twenty-six albedo results that had relatively complete sets of observational parameters and snow thicknesses greater than 10 cm were chosen for comparison with simulated results produced by the SNICAR model. Parameters that were missing from some points were replaced by observations of adjacent points made at similar times (

Table 1. Comparison of the measured albedo with simulated albedo for the QT No. 1 Glacier in 2015.

Data	Point	Local Time	Dust (ppm)	BC (ppb)	Snow Grain Effective Radius (μm)	Snowpack Thickness (m)	Snowpack Density ρ (kg/m3)	Albedo _In Situ	Albedo _SNICAR
04062015	1	10:20	11.35	3.97	477	0.30	431	0.90	0.82
04062015	3	10:40	89.49	3.97	571	0.28	354	0.84	0.73
04062015	5	11:30	30.10	3.97	457	0.17	276	0.90	0.78
06062015	2	10:00	27.70	1.64	294	0.25	344	0.83	0.84
06062015	4	9:00	112.09	0.65	549	0.17	352	0.80	0.75
06062015	5	8:10	33.50	6.47	530	0.14	408	0.80	0.82
06062015	8	11:30	24.37	3.11	642	0.12	333	0.82	0.75
06062015	9	12:00	49.60	3.72	582	0.20	426	0.80	0.74
06062015	10	12:30	155.52	0.57	836	0.10	555	0.75	0.68
06062015	11	13:00	36.95	11.50	899	0.10	387	0.82	0.71
09062015	5	10:10	25.33	1.64	365	0.12	244	0.88	0.81
25062015	10	10:00	25.29	2.69	1105	0.18	410	0.80	0.72
04072015	2	10:40	12.50	0.24	213	0.50	379	0.86	0.87
04072015	4	11:00	4.33	0.68	218	0.40	379	0.88	0.88
06072015	4	10:00	3.98	0.68	560	0.46	398	0.87	0.83
15072015	2	9:00	2.20	0.10	998	0.58	391	0.92	0.81
20072015	1	9:30	30.75	0.77	358	0.56	438	0.86	0.83
20072015	2	11:20	19.40	0.77	560	0.58	438	0.85	0.79
20072015	3	11:50	7.76	0.77	560	0.48	438	0.86	0.81
23072015	5	10:00	36.18	1.25	893	0.27	402	0.83	0.74
25072015	1	8:30	16.39	0.39	842	0.60	396	0.82	0.80
25072015	2	9:10	14.41	0.43	842	0.51	398	0.84	0.79
25072015	3	9:30	9.84	0.45	842	0.42	425	0.84	0.79
25072015	4	10:00	27.52	0.28	926	0.33	393	0.81	0.74
25072015	6	11:00	26.32	0.28	926	0.15	373	0.79	0.73
28072015	2	10:00	27.60	1.66	1076	0.44	464	0.79	0.73

). Most of the simulation results were consistent with observations, indicating an overall degree of accuracy, although simulated albedo reductions were generally larger than measured values.

All dust concentrations in Table 1 were measured during fieldwork. The following replacements were made: BC concentrations for points 1, 3, and 5 were replaced by the measured concentration at point 2 on 4 June 2015; the measured concentration at point 4 on 4 July 2015 was used to replace the BC concentration at point 4 for the adjacent date on 6 July 2015; the measured BC concentration at point 2 replaced the concentrations at adjacent points 1 and 3 on 20 July 2015; and the measured BC concentration at point 4 replaced the adjacent point 6 on 25 July 2015. In addition, snow particle size and snow density values also needed replacement by values of adjacent points in the following cases: the measured values for point 2 replaced the snow particle size at point 3, and the snow density at points 1 and 3 on 20 July 2015; and snow particle size at point 1 was used to replace the snow particle sizes at points 2 and 3 on 25 July 2015.

The results reported in

Table 2. Comparison between the effects of dust concentration, BC concentration, and snow particle size on albedo, as determined by field measurements and SNICAR.

Category	Group	Serial Number	Dust Concentration (ppm)	BC Concentration (ppb)	Snow Particle Radius (μm)	Field Measurement of Albedo	Field Measurement of Albedo Changes (%)	SNICAR Simulated Albedo	SNICAR Simulation of Albedo Changes (%)
First	(1)	06062015-4	112.09	0.65	549	0.80		0.75
		20072015-2	3.82	0.77	560	0.85	6.06	0.79	5.06
	(2)	06062015-10	155.52	0.57	836	0.75		0.68
		25072015-1	16.39	0.39	842	0.82	9.44	0.80	15.00
Second	(3)	06062015-11	36.95	11.50	899	0.82		0.71
		23072015-5	36.18	1.25	893	0.84	2.00	0.74	4.05
Third	(4)	06062015-2	27.70	1.64	294	0.83		0.84
		28072015-2	27.60	1.66	1076	0.78	6.33	0.73	13.10

are grouped together according to particle concentration and other influencing factors for ease of comparison. Particle concentration mainly refers to the concentration of dust and BC. In addition, since snow density and snow thickness showed relatively little change, they had a relatively minor influence on the albedo, and so only snow particle size was included in the category of “other factors”. We approximated the relative influences of measured dust, BC, and snow particle size on albedo, and grouped them together for comparison with simulated results (Table 2).

In the first category, BC concentration and snow particle size were fixed, although the dust concentration varied. Two groups of samples were defined: (1) 20150606-4 and 20150720-2, and (2) 20150606-10 and 20150725-1. In the second category, the dust concentration and snow particle size remained the same, but the BC concentration varied. In this category, only one group was defined: (3) 20150606-11 and 20150723-5. In the third category, the concentrations of dust and BC were kept the same, although the snow particle size varied. This was defined by one group: (4) 20150606-2 and 20150728-2. Of these three categories, only the first records differences in dust concentration, and so can characterize the effect of dust concentration on albedo. Inter-sample dust concentrations in groups (1) and (2) increased by ~108 ppm and ~139 ppm, respectively, while the measured albedo decreased by 6.06% and 9.44%, and SNICAR-simulated albedo decreased by 5.06% and 15%, respectively. Samples in the second category only exhibited differences in BC concentration, so were used to constrain how BC concentration influences albedo. The concentration of BC in group (3) increased by ~10 ppb and the measured albedo decreased by 2%. Previous studies have found that 15 ppb of BC in snow can reduce albedo by ~1% [31,33], which is consistent with our measured results from the QT No. 1 Glacier, although the SNICAR simulation results predicted a 4.05% reduction in albedo. Samples in the third category defined above can be used to examine the effect of snow particle size on albedo. In group (4), the snow particle size increased by 782 μm, while the measured albedo decreased by 6.33% and the SNICAR simulated albedo decreased by 13.10%. These data show that dust had the most significant effect on the albedo of the QT No. 1 Glacier, followed by snow particle size and then BC.

A comparison of measured albedo changes caused by dust concentration, BC concentration, and snow particle size with albedo changes simulated by SNICAR shows that the modeled albedo changes are generally greater than the measured albedo changes, although the patterns of reduction are relatively consistent for each variable. Two of the parameters involved with the field-measured albedo grouping were similar to each other, and we considered them to be the same in our analysis in order to exclude them as variables that affect albedo. This simplification may explain some of the differences between the measured and simulated results. The absolute differences in SNICAR simulation results for albedo changes within each group were small, although the albedo simulated by SNICAR was lower than the measured albedo, which tended to produce a higher rate of change than the measured albedo. Furthermore, changes in particle concentration and particle size cause non-linear changes of albedo, which decreases rapidly at low particle sizes/concentrations, but levels out as particle size/concentration continues to increase. Therefore, different initial particle size values will affect the degree of albedo reduction. As the albedo of a surface is not controlled by a single factor, the individual contribution by discrete variables must be determined; as such, we used the SNICAR model to perform simple quantitative analysis of the effect of particles on the albedo of the QT No. 1 Glacier. We adopted the following procedure:

The measured parameters of each point in the model were used to calculate the albedo, which was recorded as αSNICAR.

Other parameters remained unchanged, and the BC concentration was set to 0, allowing the albedo to be calculated without considering BC. This value was recorded as αSNICAR_BC

Other parameters remained unchanged, and the dust concentration was set to 0, allowing the albedo to be calculated without considering dust. This value was recorded as αSNICAR_dust.

The effects of dust and BC on the albedo of the QT No. 1 Glacier were individually calculated by using Equations (2) ($\Delta {\alpha }_{dust}$) and (3) ($\Delta {\alpha }_{BC}$), respectively:

$$\Delta {\alpha }_{dust}=\frac{{\alpha }_{dust}-\alpha }{\alpha }\times 100$$

(2)

$$\Delta {\alpha }_{BC}=\frac{{\alpha }_{BC}-\alpha }{\alpha }\times 100$$

(3)

Here, $\mathsf{\alpha }$, ${\alpha }_{dust}$, and ${\alpha }_{BC}$ represent the simulation results of the SNICAR model, αSNICAR, αSNICAR_dust, and αSNICAR_BC, respectively.

Calculations performed using 26 samples collected in 2015 that had relatively complete sets of observation parameters (Table 1) produced an average dust content of 24.29 ppm, an average BC content of 1.5 ppb, and an average albedo in the SNICAR model of 0.7861. When the dust concentration in the model was set to 0, the average albedo increased to 0.8314, and when the BC concentration in the model was set to 0, the average albedo increased to 0.7865. Equations (2) and (3) were used to calculate that albedo changes caused by dust and BC in the QT No. 1 Glacier and produced values of ~5.90% and ~0.06%, respectively. The mean radiative forcing from dust and BC calculated by the SNICAR model were 39.78 W/m² (with a range of 10.17–94.37 W/m²) and 0.42 W/m² (with a range of 0.05–1.31 W/m²), respectively (

Table 3. Influence of particulate matter on the albedo on the QT No. 1 Glacier snow during July 2015.

Model	∆αdust	∆αBC	RFdust	SD	RFBC	SD
	%	%	W/m2		W/m2
SNICAR	5.90	0.06	39.78	21.90	0.42	0.37

). These results show that the BC had a much smaller influence on the albedo of the QT No. 1 Glacier than dust, which we interpret to be due to the glacier being located in the center of the Tibetan Plateau where human activities are scarce, meaning that very low levels of BC are produced via anthropogenic activities.

5. Conclusions

We made observations of albedo on the QT No. 1 Glacier in the central Tibetan Plateau during melting seasons in 2013, 2014, and 2015, and analyzed its influencing factors. Our main conclusions are as follows:

(1)

Particulate matter has a significant effect on albedo. During the melting season, particulate matter is continuously enriched on the surface of a glacier. Most of the observed dust contents in the study region were below 600 ppm, although certain areas recorded values exceeding 1000 ppm. All measured BC contents were very low, with most below 10 ppb. A strong correlation was documented between dust content and albedo. Below a dust concentration of 1000 ppm, albedo decreased rapidly as dust content increased; however, albedo stabilized when dust concentrations exceeded 1000 ppm. Albedo showed a decreasing trend as BC concentration increased, but with a weak correlation between each variable.

(2)

Snow cover characteristics influence albedo. In particular, albedo decreased as snow particle size and snow density increased. Observed snow particle sizes in the study area showed a roughly log-normal distribution, with a mean radius of ~500 μm and a total range of 40–2539 μm. Snow density values showed a normal distribution, with a median occurrence of 400 kg/m³ and a total range of 193–555 kg/m³.

(3)

Snow surface conditions also have a significant impact on albedo. In the study region, the albedo of a sample site on the QT No. 1 Glacier decreased from 0.9 to 0.5 after removing 9.5 cm of fresh snow. The enrichment of particulate matter also had a significant effect on the reflectance spectrum of sampled surfaces, especially in the visible and near-infrared bands.

(4)

Our measurements from the QT No. 1 Glacier show that dust has the most significant effect on albedo, followed by snow particle size, and finally BC. SNICAR simulations assessing the influence of particulate matter predicted a greater albedo reduction than was measured during our fieldwork, although overall trends were consistent. Other simulation results indicated that dust and BC on the QT No. 1 Glacier during the 2015 melting season reduced the albedo by 5.90% and 0.06%, respectively, and that average radiative forcing reached 39.78 W/m² and 0.42 W/m², respectively. Dust therefore plays a more important role in the melting of the QT No. 1 Glacier than BC, which is mainly due to the rarity of human activity in the region and the low concentration of BC.