Changes In Albedo Research Articles

Reponses of Land Surface Albedo to Global Vegetation Greening: An Analysis Using GLASS Data

Global vegetation greening during recent decades has been observed from various remote sensing data. The global and regional climate can be altered by an increase in carbon storage, as well as changes in land surface albedo (LSA) and evaporation. However, the LSA changes induced by global vegetation greening are still not clear, and contrasting responses of LSA to vegetation changes were reported in previous studies. In this study, we analyzed the LSA in response to global vegetation greening using the Global Land Surface Satellite (GLASS) data and a vegetation-induced LSA change model. The results showed that vegetation greening trends could be observed worldwide, which resulted in contrasting LSA responses at regional scales (LSA increased as leaf area index (LAI) increased, or LSA decreased as LAI increased). Moreover, these contrasting LSA responses to global vegetation greening were effectively explained by the albedo difference between a vegetation and soil background. The results provide new insights into the relationship between LSA changes and global vegetation dynamics, and can support recommendations for policies of vegetation protection, and large-scale afforestation and deforestation.

Surface Albedo and Snowline Altitude Estimation Using Optical Satellite Imagery and In Situ Measurements in Muz Taw Glacier, Sawir Mountains

Glacier surface albedo strongly affects glacier mass balance by controlling the glacier surface energy budget. As an indicator of the equilibrium line altitude (ELA), the glacier snowline altitude (SLA) at the end of the melt season can reflect variations in the glacier mass balance. Therefore, it is extremely crucial to investigate the changes of glacier surface albedo and glacier SLA for calculating and evaluating glacier mass loss. In this study, from 2011 to 2021, the surface albedo of the Muz Taw Glacier was derived from Landsat images with a spatial resolution of 30 m and from the Moderate Resolution Imaging Spectroradiometer albedo products (MOD10A1) with a temporal resolution of 1 day, which was verified through the albedo measured by the Automatic Weather Station (AWS) installed in the glacier. Moreover, the glacier SLA was determined based on the variation in the surface albedo, with the altitude change along the glacier main flowline derived from the Landsat image at the end of the melt season. The correlation coefficient of >0.7, with a risk of error lower than 5%, between the surface albedo retrieved from remote sensing images and the in situ measurement data indicated that the method of deriving the glacier surface albedo by the remote sensing method was reliable. The annual average albedo showed a slight upward trend (0.24%) from 2011 to 2021. A unimodal seasonal variation in albedo was demonstrated, with the downward trend from January to August and the upward trend from August to December. The spatial distribution of the albedo was not entirely dependent on altitude due to the dramatic effects of the topography and glacier surface conditions. The average SLA was 3446 m a.s.l., with a variation of 160 m from 2011 to 2021. The correlation analysis between the glacier SLA and annual mean temperature/annual precipitation demonstrated that the variations of the average SLA on the Muz Taw Glacier was primarily affected by the air temperature. This study improved our understanding of the ablation process and mechanism of the Muz Taw Glacier.

What drives the decrease of glacier surface albedo in High Mountain Asia in the past two decades?

Glacier surface albedo is an important factor affecting glacier ablation, and a positive feedback mechanism has been observed between the surface albedo and mass balance of glaciers. It is important to understand the driving factors and mechanisms of glacier albedo changes (GAC). Based on the MODIS (Moderate resolution imaging spectroradiometer)-derived MOD10A1 and MYD10A1 albedo products, the glacier albedo trends in each MODIS grid cell during each melt season in High-Mountains Asia (HMA) from 2000 to 2020 were calculated. Decreasing glacier albedo trends were found, with a decline rate of 0.25 × 10−2 yr−1; in addition, the GACs exhibited great spatial differences among the 15 subregions. The geographical detector model (GDM) is a new spatial statistical method that can quantitatively reveal the driving forces of climate factors and light-absorbing particles on GAC under single-factor and two-factor interactions. These driving forces can be measured by the corresponding q value. The results showed that on the whole, solid precipitation (snowfall) had the strongest impact on GAC, followed by the glacier surface temperature. The q values of black carbon (BC) and dust were <0.1, but BC or dust had the greatest q value in the 9 subregions. The effects of each factor differed among different elevation zones. The interaction detector indicated that the q value under the influence of two factors was greater than that under a single factor, and the strongest interaction was between snowfall and BC, followed by between snowfall and dust. In 15 subregions, most of the greatest q values in each region corresponded to an interaction with BC or dust. Here, we obtained the main driving factors of GAC in different regions and emphasized the interactions between climatic factors and light-absorbing particles; these results provide references for further studies of glacier mass balance and surface albedo.

Spatial Heterogeneity and Temporal Variation in Urban Surface Albedo Detected by High-Resolution Satellite Data

Albedo is one of the key parameters in the surface energy balance and it has been altered due to urban expansion, which has significant impacts on local and regional climate. Many previous studies have demonstrated that changes in the urban surface albedo are strongly related to the city’s heterogeneity and have significant spatial-temporal characteristics but fail to address the albedo of the urban surface as a unique variable in urban thermal environment research. This study selects Beijing as the experimental area for exploring the spatial-temporal characteristics of the urban surface albedo and the albedo’s uniqueness in environmental research on urban spaces. Our results show that the urban surface albedo at high spatial resolution can better represent the urban spatial heterogeneity, seasonal variation, building canyon, and pixel adjacency effects. Urban surface albedo is associated with building density and height, land surface temperature (LST), and fractional vegetation cover (FVC). Furthermore, albedo can reflect livability and environmental rating due to the variances of building materials and architectural formats in the urban development. Hence, we argue that the albedo of the urban surface can be considered as a unique variable for improving the acknowledgment of the urban environment and human livability with wider application in urban environmental research.

The impacts of urban anthropogenic heat and surface albedo change on boundary layer meteorology and air pollutants in the Beijing-Tianjin-Hebei region

In this study, present and future anthropogenic heat flux (AH) and surface albedo (SA) in Beijing are estimated and incorporated into the WRF-Chem/UCM model. A series of nested model simulations are conducted at 9 km and 27 km horizontal grid resolution with 30 layers in the vertical to explore the sensitivity of model results to urban surface characteristics during the study period from 23 February to 13 March 2014, and the impacts of anthropogenic heat and surface albedo changes in the future on urban meteorology and air pollutants in Beijing. Model validation demonstrates that the model with the up-to-date urban surface parameters apparently improves predictions for both meteorological variables and chemical species compared with model results with default urban parameters. The combined effect of SA increase and AH decrease leads to consistent decreases in T2 (air temperature at 2 m above ground), WS10 (wind speed at 10 m) and PBLH (planetary boundary layer height) by up to 1.2 °C, 0.4 m s−1 and 200 m (33%), respectively, in Beijing averaged over the study period. In response to the meteorological changes, near surface PM2.5 (particulate matter with aerodynamic equivalent diameter below 2.5 μm) concentration increases by up to 15.6 μg m−3 (8.6%), whereas O3 concentration decreases by 2.6 ppb (25.1%), respectively. In daytime, near surface cooling due to SA increase and AH decrease causes a strong downdraft over Beijing urban areas, a wind divergence near the surface and an upslope wind over the western mountain, resulting in aerosol transport from urban district to western mountain slope. At nighttime, surface cooling is weaker than that in daytime, leading to a weaker downdraft over Beijing and a slight downslope wind in the mountain. The combined changes in SA and AH lead to a decrease in T2 by 1.2 °C, a decrease of O3 concentration by approximately 20%, and increases in PM2.5 and its components by 10–17% in daytime averaged over the urban areas of Beijing during the study period, and the above changes are weaker during haze days than those in clean days. The changes in urban surface parameters in Beijing in the future may be benefit for mitigating heat wave and O3 pollution risks, but could increase fine aerosol level and human health risk, which require an optimal strategy for co-benefits of climate change mitigation and air pollution control in future city planning.

Surface Dust Redistribution on Mars From Interannual Differences in Temperature and Albedo

AbstractThe present climate of Mars is punctuated by recurring dust storm events, where dust is lifted from the surface and is transported by the atmosphere. Dust addition or removal can brighten or darken the surface, as well as affect thermal insulating properties because of its low thermal conductivity. Of particular interest is the recurrence of global dust storms (GDSs) and whether their frequency is controlled by the replenishment or depletion of finite surface reservoirs between events. Global climate models predict changes in dust coverage before and after global storms, but output varies substantially regarding the amounts and locations of transported dust. The analysis of global, multiyear observations of surface temperature and albedo from orbit can constrain changes in dust coverage and/or thickness. We calculate and map interannual differences in surface temperature from Mars Year (MY) 24 through MY35 to identify regions of dust redistribution. Regional temperature changes across the MY25 GDS can be explained by changes in albedo and do not require changes in surface thermal properties, supporting extremely small dust thickness changes. Across the MY34 GDS, we find less extensive changes in surface temperature, indicating a reduced impact on dust redistribution compared to MY25. However, we identify a region between Acidalia and Arabia Terra that experienced substantial dust removal and positively correlates with visible high‐resolution orbital images. Our work supports minuscule changes in dust thickness from the observed GDSs and is consistent with effectively infinite dust reservoirs on timescales of at least 103 years.

Physical Controls on the Hydrology of Perennially Ice‐Covered Lakes, Taylor Valley, Antarctica (1996–2013)

AbstractThe McMurdo Dry Valleys, Antarctica, are a polar desert populated with numerous closed‐watershed, perennially ice‐covered lakes primarily fed by glacial melt. Lake levels have varied by as much as 8 m since 1972 and are currently rising after a decade of decreasing. Precipitation falls as snow, so lake hydrology is dominated by energy available to melt glacier ice and to sublimate lake ice. To understand the energy and hydrologic controls on lake level changes and to explain the variability between neighboring lakes, only a few kilometers apart, we model the hydrology for the three largest lakes in Taylor Valley. We apply a physically based hydrological model that includes a surface energy balance model to estimate glacial melt and lake sublimation to constrain mass fluxes to and from the lakes. Results show that lake levels are very sensitive to small changes in glacier albedo, air temperature, and wind speed. We were able to balance the hydrologic budget in two watersheds using meltwater inflow and sublimation loss from the ice‐covered lake alone. A third watershed, closest to the coast, required additional inflow beyond model uncertainties. We hypothesize a shallow groundwater system within the active layer, fed by dispersed snow patches, contributes 23% of the inflow to this watershed. The lakes are out of equilibrium with the current climate. If the climate of our study period (1996–2013) persists into the future, the lakes will reach equilibrium starting in 2300, with levels 2–17 m higher, depending on the lake, relative to the 2020 level.

Twelve-Year Cycle in the Cloud Top Winds Derived from VMC/Venus Express and UVI/Akatsuki Imaging

We present joint analysis of the UV (365 nm) images captured by the cameras on board ESA’s Venus Express and JAXA’s Akatsuki spacecraft. These observations enabled almost continuous characterization of the cloud top circulation over the longest period of time so far (2006–2021). More than 46,000 wind vectors were derived from tracking the UV cloud features and revealed changes in the atmospheric circulation with the period of 12.5 ± 0.5 years. The zonal wind component is characterized by an annual mean of −98.6 ± 1.3 m/s and an amplitude of 10.0 ± 1.6 m/s. The mean meridional wind velocity is −2.3 ± 0.2 m/s and has an amplitude of 3.4 ± 0.3 m/s. Plausible physical explanations of the periodicity include both internal processes and external forcing. Both missions observed periodical changes in the UV albedo correlated with the circulation variability. This could result in acceleration or deceleration of the winds due to modulation of the deposition of the radiative energy in the clouds. The circulation can be also affected by the solar cycle that has a period of approximately 11 years with a large degree of deviation from the mean. The solar cycle correlated with the wind observations can probably influence both the radiative balance and chemistry of the mesosphere. The discovered periodicity in the cloud top circulation of Venus, and especially its similarity with the solar cycle, is strongly relevant to the study of exoplanets in systems with variable “suns”.

Mid-summer snow-free albedo across the Arctic tundra was mostly stable or increased over the past two decades

Arctic vegetation changes, such as increasing shrub-cover, are expected to accelerate climate warming through increased absorption of incoming radiation and corresponding decrease in summer shortwave albedo. Here we analyze mid-summer shortwave land-surface albedo and its change across the pan-Arctic region based on MODerate resolution Imaging Spectroradiometer satellite observations over the past two decades (2000–2021). In contrast to expectations, we show that terrestrial mid-summer shortwave albedo has not significantly changed in 82% of the pan-Arctic region, while 14% show an increase and 4% a decrease. The total median significant change was 0.014 over the past 22 years. By analyzing the visible and near-/shortwave-infrared range separately, we demonstrate that the slight increase arises from an albedo increase in the near-/shortwave infrared domain while being partly compensated by a decrease in visible albedo. A similar response was found across different tundra vegetation types. We argue that this increase in reflectance is typical with increasing biomass as a result of increased multiple reflection in the canopy. However, CMIP6 global land surface model albedo predictions showed the opposite sign and different spatial patterns of snow-free summer albedo change compared to satellite-derived results. We suggest that a more sophisticated vegetation parametrization might reduce this discrepancy, and provide albedo estimates per vegetation type.

Spatiotemporal variations in surface albedo during the ablation season and linkages with the annual mass balance on Muz Taw Glacier, Altai Mountains

ABSTRACT Melt-albedo feedback on glaciers is recognized as important processes for understanding glacier behavior and its sensitivity to climate change. This study selected the Muz Taw Glacier in the Altai Mountains to investigate the spatiotemporal variations in albedo and their linkages with mass balance, which will improve our knowledge of the recent acceleration of regional glacier shrinkage. Based on the Landsat-derived albedo, the spatial distribution of ablation-period albedo was characterized by a general increase with elevation, and significant east–west differences at the same elevation. The gap-filling MODIS values captured a nonsignificant negative trend of mean ablation-period albedo since 2000, with a total decrease of approximately 4.2%. From May to September, glacier-wide albedo exhibited pronounced V-shaped seasonal variability. A significant decrease in annual minimum albedo was found from 2000 to 2021, with the rate of approximately −0.30% yr−1 at the 99% confidence level. The bivariate relationship demonstrated that the change of ablation-period albedo explained 82% of the annual mass-balance variability. We applied the albedo method to estimate annual mass balance over the period 2000–2015. Combined with observed values, the average mass balance was −0.82 ± 0.32 m w.e. yr−1 between 2000 and 2020, with accelerated mass loss.

Evaluating the Potential of Landsat Satellite Data to Monitor the Effectiveness of Measures to Mitigate Urban Heat Islands: A Case Study for Stuttgart (Germany)

The urban heat island (UHI) effect is a serious health risk for people living in cities and thus calls for effective mitigation strategies in urban areas. Satellite data enable monitoring of the surface urban heat island (SUHI) over large areas at high spatial resolution. Here we analysed SUHI in the city of Stuttgart (Germany) based on land surface temperature (LST) data from Landsat at 30 m resolution. The overall SUHI in Stuttgart decreased by 1.4 °C between the investigated time periods 2004–2008 and 2016–2020, while the absolute LST increased by 2.5 °C. We identified local hotspots of strong warming and cooling in Stuttgart through the change in SUHI and categorised them based on the predominant land cover change occurring at the hotspot using the Normalised Difference Vegetation Index (NDVI) from Landsat as well as visual information on land cover changes from Google Earth Pro. The establishment of green roofs, as well as albedo changes, are predominantly responsible for cooling spots, while warming spots are mostly associated with the sealing of surfaces. This highlights that vegetation has a dominant influence on SUHI development in Stuttgart. Combining satellite-based LST data with visual information thus provides an effective method to identify local warming and cooling hotspots, which allows monitoring of the success of city policies against heat stress and guides future policy.

Impacts of burn severity on short-term postfire vegetation recovery, surface albedo, and land surface temperature in California ecoregions.

Wildfire burn severity has important implications for postfire vegetation recovery and boundary-layer climate. We used a collection of Moderate Resolution Imaging Spectroradiometer (MODIS) datasets to investigate the impact of burn severity (relative differenced Normalized Burn Ratio, RdNBR) on vegetation recovery (Enhanced Vegetation Index, EVI), albedo change, and land surface temperature in seven California ecoregions, including: Southern California Mountains (SCM), Southern California Coast (SCC), Central California Foothills (CCF), Klamath (K), Cascades (C), Eastern Cascades (EC), and Sierra Nevada (SN). A statewide MODIS-derived RdNBR dataset was used to analyze the impact of burn severity on the five-year postfire early-summer averages of each biophysical variable between the years 2003-2020. We found that prefire EVI values were largest, and prefire albedo and temperature were lowest in the K, C, EC, and SN ecoregions. Furthermore, the largest changes between prefire and first-year postfire biophysical response tended to occur in the moderate and high burn severity classes across all ecoregions. First-year postfire albedo decreased in the K, C, EC, and SN but increased in the SCM, SCC, and CCF ecoregions. The greatest decreases, but most rapid recovery, of EVI occurred after high severity fires in all ecoregions. After five-years post-fire, EVI and land surface temperature did not return to prefire levels in any burn severity class in any ecoregion.

Numerical simulation of the surface flux of an alpine grassland in the source region of the Yellow River by the land surface model

The simulation performance of the land surface model Community Land Model 5.0 (CLM5.0) is tested by using the eddy correlation system and micrometeorological tower observational data at the Maqu observation field in 2016. The results show that the CLM5.0 model has a good simulation effect on the soil temperature and can well reflect the seasonal variation characteristics of soil temperature. In addition, the model can well simulate the seasonal variation in shallow soil moisture (5 cm and 10 cm). However, the deviations between the simulated and observed values are large. CLM5.0 cannot simulate the water holding capacity of shallow soil well, resulting in its underestimation. The simulation performance of the upward longwave radiation and net radiation is substantially better than that of the upward shortwave radiation due to the change in surface albedo caused by precipitation from March to July. CLM5.0 can also well reproduce the variation trend of the latent heat flux and 5 cm soil heat flux (heat exchange of soil at 5 cm). When the leaf area index (LAI) and Medlyn slope values are changed to 10%, 20%, and 50% of the default values, the simulation effects of soil moisture at depths of 5 cm and 10 cm are significantly improved, and the best simulation effects are achieved at 0.5 times the default values. This result indicates that lower LAI and Medlyn slope values are more suitable for simulating shallow soil moisture.

Deep Reinforcement Learning for the Optimal Angle Control of Tracking Bifacial Photovoltaic Systems

An optimal tilt-angle control based on artificial intelligence (AI control) for tracking bifacial photovoltaic (BPV) systems is developed in this study, and its effectiveness and characteristics are examined by simulating a virtual system over five years. Using deep reinforcement learning (deep RL), the algorithm autonomously learns the control strategy in real time from when the system starts to operate. Even with limited deep RL input variables, such as global horizontal irradiance, time, tilt angle, and power, the proposed AI control successfully learns and achieves a 4.0–9.2% higher electrical-energy yield in high-albedo cases (0.5 and 0.8) as compared to traditional sun-tracking control; however, the energy yield of AI control is slightly lower in low-albedo cases (0.2). AI control also demonstrates a superior performance when there are seasonal changes in albedo. Moreover, AI control is robust against long-term system degradation by manipulating the database used for reward setting.

YEREL METEOROLOJİK VERİ KAYITLARI İLE SEKBANDEMİRLİ KIRSAL BÖLGESİNDE GÜNLÜK VE MEVSİMSEL FOTOVOLTAİK ISI ADASININ İNCELENMESİ VE DEĞERLENDİRİLMESİ

Photovoltaic Power Plants have a considerable share among solar energy conversion technologies toward environmentally sustainable and economically feasible electricity production. However, when a rural region's land surface formed by natural soil types is covered by a Photovoltaic Power Plant (PVPP)'s dark-colored solar modules in large numbers, an artificial albedo (reflectivity) change is expected on that surface. Because of the heat exchange between these modules and the air surrounding them due to albedo alteration, the region's natural weather conditions may experience Photovoltaic Heat Island Effect (PVHIE) as a result of external and time-dependent air temperature oscillations caused by the warming-cooling cycles of solar modules. To observe and analyze a possible PVHIE trend, it has been conducting a field study project since October 2017 for a PVPP near the Sekbandemirli rural region in the Kutahya city of Turkey. The weather data, including air temperature and wind (direction and speed) at every 10-minute and hourly intervals, are collected by the three weather monitoring stations installed at the specific locations inside and outside the PVPP field. The plant's hourly average power output and module temperature data can also be monitored. After conducting statistical, correlational, and graphical analyses, the results show some temporal PVHI formations at the PVPP field center daily and on a seasonal basis. The plant center's air temperature tends to be warmer (up to the 6°C difference) during daytimes and colder (up to the (-3)°C difference) during nighttimes.

Changes in snow and ice surface albedo and its impact on snow and ice area in the Wind River Range, Wyoming, USA

ABSTRACT Glacial and snow melt in the Wind River Range, Wyoming feed headwaters for the Missouri and Colorado River Systems, covering much of the western United States. Identifying the factors that have the greatest impact on snow and ice melt is important to managing the water resources in this region. This study examined snow and ice albedo, summer temperature and precipitation, and winter precipitation as potential significant factors related to snow and ice area changes. The Mann–Kendall statistical test was used to analyze changes in surface albedo on snow and ice over time (1985 to 2016) as derived from Landsat imagery among 5 basins in the Wind River Range. As well, a stepwise regression analysis was utilized in determining the significance of albedo along with summer mean temperature, total summer precipitation, and total winter precipitation in predicting snow and ice area. Among all the variables, albedo was found to have the greatest significance in relation to snow and ice area change. The significance of albedo on snow and ice melting in the Wind River Range is likely due to a positive feedback effect coupled with possible effects from annual increases in particulates from forest fires and fossil fuel production.

Simulating Aerosol Lifecycle Impacts on the Subtropical Stratocumulus‐to‐Cumulus Transition Using Large‐Eddy Simulations

AbstractObserved stratocumulus to cumulus transitions (SCTs) and their sensitivity to aerosols are studied using a large‐eddy simulation (LES) model that simulates the aerosol lifecycle, including aerosol sources and sinks. To initialize, force, and evaluate the LES, we used a combination of reanalysis, satellite, and aircraft data from the 2015 Cloud System Evolution in the Trades field campaign over the Northeast Pacific. The simulations follow two Lagrangian trajectories from initially overcast stratocumulus (Sc) to the tropical shallow cumulus region near Hawaii. The first trajectory is characterized by an initially clean, well‐mixed Sc‐topped marine boundary layer (MBL), then continuous MBL deepening and precipitation onset followed by a clear SCT and a consistent reduction of aerosols that ultimately leads to an ultra‐clean layer in the upper MBL. The second trajectory is characterized by an initially polluted and decoupled MBL, weak precipitation, and a late SCT. Overall, the LES simulates the observed general MBL features. Sensitivity studies with different aerosol initial and boundary conditions reveal aerosol‐induced changes in the transition, and albedo changes are decomposed into the Twomey effect and adjustments of cloud liquid water path and cloud fraction. Impacts on precipitation play a key role in the sensitivity to aerosols: for the first case, runs with enhanced aerosols exhibit distinct changes in microphysics and macrophysics such as enhanced cloud droplet number concentration, reduced precipitation, and delayed SCT. Cloud adjustments are dominant in this case. For the second case, enhancing aerosols does not affect cloud macrophysical properties significantly, and the Twomey effect dominates.

Rapid Warming in the Australian Alps from Observation and NARCliM Simulations

The Australian Alps are the highest mountain range in Australia, which are important for biodiversity, energy generation and winter tourism. Significant increases in temperature in the past decades has had a huge impact on biodiversity and ecosystem in this region. In this study, observed temperature is used to assess how temperature changed over the Australian Alps and surrounding areas. We also use outputs from two generations of NARCliM (NSW and Australian Regional Climate Modelling) to investigate spatial and temporal variation of future changes in temperature and its extremes. The results show temperature increases faster for the Australian Alps than the surrounding areas, with clear spatial and temporal variation. The changes in temperature and its extremes are found to be strongly correlated with changes in albedo, which suggests faster warming in cool season might be dominated by decrease in albedo resulting from future changes in natural snowfall and snowpack. The warming induced reduction in future snow cover in the Australian Alps will have a significant impact on this region.

Irrigation and warming drive the decreases in surface albedo over High Mountain Asia

Human and climate induced land surface changes resulting from irrigation, snow cover decreases, and greening impact the surface albedo over High Mountain Asia (HMA). Here we use a partial information decomposition approach and remote sensing data to quantify the effects of the changes in leaf area index, soil moisture, and snow cover on the surface albedo in HMA, home to over a billion people, from 2003 to 2020. The study establishes strong evidence of anthropogenic agricultural water use over irrigated lands (e.g., Ganges–Brahmaputra) which causes the highest surface albedo decreases (≤ 1%/year). Greening and decreased snow cover from warming also drive changes in visible and near-infrared surface albedo in different areas of HMA. The significant role of irrigation and greening in influencing albedo suggests the potential of a positive feedback cycle where albedo decreases lead to increased evaporative demand and increased stress on water resources.

Estimating glacier mass balance in High Mountain Asia based on Moderate Resolution Imaging Spectroradiometer retrieved surface albedo from 2000 to 2020

AbstractGlacier surface albedo is a key parameter of the glacier mass and energy balance process. Many scholars have used the albedo method to study mass balance for an individual glacier, but less attention has been given to large‐area glaciers. Based on Moderate Resolution Imaging Spectroradiometer (MODIS) retrieved glacier surface albedo and in situ mass balance, the correlations between albedo and mass balance are reported. The minimum/mean method (the whole glacier albedo is calculated by averaging the minimum/mean albedo of each grid cell), the MODIS snow albedo products (MxD10A1) and the MCD43A3 shortwave albedo were tested during the melt season (June–August) for four glaciers in the High Mountain Asia (HMA). Results reveal that albedo is well correlated with mass balance, the correlation (r) ranging from 0.41 to 0.90. Overall, the minimum method is better than the mean method, and MxD10A1 is better than MCD43A3. The albedo changes were calculated based on the MxD10A1 and the mean method, and a linear relationship is established between albedo changes and digital elevation models (DEMs) calculated mass balance from 2000 to 2016. A strong linear correlation (r = .9) is found between albedo changes and mass balance while excluding some areas that have insignificant seasonal variation in albedo, and the reconstructed albedo–mass balance relationship can be used to retrieve mass balance in large‐scale glaciers. Furthermore, the average loss of mass from 2000 to 2020 is calculated as −0.225 ± 0.040 m w.e.a−1. The greatest glacier mass loss is concentrated in the southeastern part of HMA, the mass loss in the north and west is less than that in the southeast, and the glacier mass is in a state of aggravated loss in recent years. Our study also offers a new method for estimating the large‐scale glacier mass balance.