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This study introduces a new method for nowcasting UV Index maps developed within the framework of the Austrian Solar UV Measurement Network. While we focus on the DACH region (Germany, Austria, and Switzerland) in this study, the same methods are routinely applied to nowcast UV Index maps for Europe. The primary objective is to improve public health measures by providing timely and area-wide UV Index values. The UV Index maps are based on clear-sky calculations using data from the Copernicus Atmosphere Monitoring Service. Cloud effects are integrated using cloud modification factors determined from Meteosat Second Generation satellite imagery. To assess the representativeness of the calculated UV Index maps, the corresponding pixel values are compared to ground-based measurements for the year 2022 at 27 locations in the DACH region. For all sky conditions, the satellite-derived UV Index values are within ±1.0 UV Index of the ground-measured UV Index for at least 91% of the data at stations below 500 m a.s.l. and in flatter landscapes. For high-altitude sites and in more pronounced topographies, the values for U1.0 decrease, with the lowest agreement of 74.8% found for the Sonnblick station located at 3109 m a.s.l. Discrepancies arise due to differences in the measurement methods: ground-based measurements capture the local conditions, while satellite-derived values represent the average values over larger areas. The clear-sky deviations are most pronounced at high-altitude, snow-covered sites due to uncertainties in the surface albedo. Under all sky conditions, cloud variability adds further uncertainties, particularly in complex terrain or broken cloud cover scenarios, where satellite cloud data lack the resolution to capture local fluctuations. This study discusses these uncertainties while also highlighting the potential of the generated UV Index maps to provide area-wide information to the population as a valuable complement to ground-based measurements. [ABSTRACT FROM AUTHOR]

ETAL is the operational EPS Ten-Day Albedo product, produced by the EUMETSAT Satellite Application Facility for Land Surface Analysis (LSA SAF). By back-processing the full catalogue of EPS-Metop radiance data from September 2007 to June 2021, we are able to 1) extend the temporal coverage (previously the archive only went back to 2015) and 2) improve the product archive that was based on near-real time (NRT) processing; the second point is achieved by using reanalyses instead of forecasts of atmospheric conditions and by not being exposed to missing data in the NRT radiance inputs. We present this reprocessed part of the ETAL data set, called ETAL-R, and assess its quality and consistency with respect to the original archive of NRT ETAL data (for the overlapping period 2015–2021), as well as its accuracy compared to albedo from MODIS and ground stations. ETAL-R exhibits reliable long-term stability and increased homogeneity compared to the NRT archive, and the comparison against the additional reference data shows satisfactory accuracy. Overall, ETAL-R is shown to be very consistent with the ETAL NRT archive while – under certain circumstances – improving it. [ABSTRACT FROM AUTHOR]

The land-atmosphere interaction of a topographically complex ice surface of high-altitude Yala Glacier station in the east Himalaya is studied. In the study site, shift in wind direction during October and November suggests the dominance of mountain-valley wind circulation. Tunnel effect is evident during the daytime owing to tall mountains, which affect the direction and speed of the wind flow. During the day, the snow cover evaporates and enhances the relative humidity (74%) and mixing ratio (0.005 kg kg− 1). In October, fresh snow cover reflects maximum amount of incoming shortwave (Sinc) into space than in November. On the other hand, November’s sensible heat flux is higher than that of October, indicating that more heat is transferred from the snow surface to the atmosphere. The difference between Sin-Sout in October and November is 133 ± 63 Wm−2 and 282 ± 130 Wm−2, respectively. Compared to October, the ice cover absorbs more Sinc in November, which increased the melting of ice cover. In October and November, the mean albedo during the day is 0.80 ± 0.06 and 0.57 ± 0.09, respectively. Between 1000 and 1100 local time in October, there is a noticeable shift in the albedo, ranging from 0.5 to 0.9, which reveals that the snowmelt has altered the surface albedo. The mean climate sensitivity in October and November are 0.006 ± 0.001 ºCWm− 2 and 0.007 ± 0.002 ºCWm− 2, respectively. Climate sensitivity strongly correlates with day-night temperature variation (dT). It is observed that dT is negatively correlated with relative humidity, incoming longwave (Linc), and outgoing longwave radiation (Lout) and positively correlated with wind speed, Sinc, and Sout. [ABSTRACT FROM AUTHOR]

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In current land surface models or satellite remote sensing retrievals, clear‐sky surface albedo (α) is usually assumed to be symmetrical and relies only on the solar elevation angle (SEA). Based on 1‐min high‐resolution measurements of surface radiation fluxes, this study demonstrated that the diurnal variations of clear‐sky surface albedo exhibited a significant asymmetrical pattern in both summer and winter seasons over a semi‐arid grassland of the China's Loess Plateau. The results indicated that α values in the morning were generally larger than those in the afternoon at the same SEA, and diurnal asymmetry of surface albedo was distinctly prominent with SEA <40° in summer (before 9:30 a.m.) or SEA <20° in winter (before 10:00 am), and tended to diminish at midday. The averaged morning/afternoon albedo differences under sunny days were 0.05 (30.4%) and 0.09 (37.8%) in summer and winter seasons, respectively. Air relative humidity was positively correlated with the diurnal asymmetry of surface albedo, ascribed to probable formation of dew in the morning. Depression of the dew point was negatively linked to the morning/afternoon albedo differences, which was attributed to the strong scattering of incident sunlight by dewdrops could enhance the morning surface albedo. Such diurnal asymmetry of surface albedo should be included in the parameterization scheme of mesoscale and region‐scale climate models in the semi‐arid areas of China's Loess Plateau. [ABSTRACT FROM AUTHOR]

Copyright of Arid Zone Research / Ganhanqu Yanjiu is the property of Arid Zone Research Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Several studies have noted elevation-dependent warming (EDW) in the Himalaya. However, understanding of its spatio-temporal patterns and impacts on the cryosphere remains limited, given the complex geographic and climatic conditions of the central Himalayan region. In this novel attempt to comprehend EDW in the central Himalaya, we utilized multisource satellites and modeled data spanning 2000–2020. Our analysis examined temporal and altitudinal variations in land surface temperature (LST) and air temperature, considering changes in surface albedo and cryosphere elements. The multi-temporal glacier inventory revealed an overall decline in glacier area from 2710 km2 in 2000–01–2658 km2 in 2020–21. This receded glacier area contributed to the development/expansion of glacial lakes or exposed bedrock, potentially amplifying solar radiation absorption and exerting positive surface albedo feedback on localized heating and glacier melting. Concurrent with glacier retreat, pro- and peri-glacial lakes increased in area and number by ∼28%, reaching 6.8 km2 (209) in 2020, with a notable ∼36% increase in area and ∼32% in number above 4600 m asl. Analysis of MODIS-derived land surface temperature and ERA5-Land modeled near-surface air temperature suggested an increasing temperature trend over the past two decades, with a higher rate of increase at higher elevations. Snow cover area and surface albedo, recorded from MODIS datasets, decreased, particularly at higher elevations, with temperature trends. These findings illustrate the pattern and impacts of EDW, which are expected to intensify due to the positive surface albedo feedback mechanism.

ETAL is the operational EPS Ten-Day Albedo product, produced by the EUMETSAT Satellite Application Facility for Land Surface Analysis (LSA SAF). By back-processing the full catalogue of EPS-Metop radiance data from September 2007 to June 2021, we are able to 1) extend the temporal coverage (previously the archive only went back to 2015) and 2) improve the product archive that was based on near-real time (NRT) processing; the second point is achieved by using reanalyses instead of forecasts of atmospheric conditions and by not being exposed to missing data in the NRT radiance inputs. We present this reprocessed part of the ETAL data set, called ETAL-R, and assess its quality and consistency with respect to the original archive of NRT ETAL data (for the overlapping period 2015–2021), as well as its accuracy compared to albedo from MODIS and ground stations. ETAL-R exhibits reliable long-term stability and increased homogeneity compared to the NRT archive, and the comparison against the additional reference data shows satisfactory accuracy. Overall, ETAL-R is shown to be very consistent with the ETAL NRT archive while – under certain circumstances – improving it.

Progression and development of many under- water and terrestrial life forms are influenced by many environmental factors, including the amount of ultraviolet radiation present at water and the Earth’s surface. Spectral measure of solar UV radiation helps us to understand the causes of change in environment and also raise public awareness about potential threats when the index value goes higher. This paper presents the value of UV index over six different locations of Nepal which are situated at different latitude and at different altitude. The numeral values of UV index during solar noon, provided by POWER data sets from year 2001 AD to 2021 AD, was used which were then compared with standard value categories of UV index based on WHO guideline. The UV index value for these locations were compared on monthly and annual basis. Upon analysis, it was found that during solar noon average value of UV index above Dolpa was highest with the value 9.10. The maximum value of UV index above other locations were: 8.43(Birgunj), 8.13(Hetauda), 6.14(Rolpa) and 5.45(Tulsipur) respectively. During mid-summer the value of UV index in each of these locations fall into high or very high category as per the WHO guideline. Thus, people from these locations are vulnerable to the exposure of harmful UV radiation. This study reveals that the special care should be taken during midday from June through August.

Copyright of Arid Land Geography is the property of Chinese Academy of Sciences, Xinjiang Institute of Ecology & Geography and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Satellite observations have shown widespread greening during the last few decades over the northern permafrost region, but the impact of vegetation greening on permafrost thermal dynamics remains poorly understood, hindering the understanding of permafrost‐vegetation‐climate feedbacks. Summer surface offset (SSO), defined as the difference between surface soil temperature and near‐surface air temperature in summer (June‐August), is often predicted as a function of surface thermal characteristics for permafrost modeling. Here we examined the impact of leaf area index (LAI), detected by satellite as a proxy to permafrost vegetation dynamics, on SSO variations from 2003 to 2021 across the northern permafrost region. We observed latitude‐ and biome‐dependent patterns of SSO changes, with a pronounced increase in Siberian shrublands and a decrease in Tibetan grasslands. Based on partial correlation and sensitivity analyses, we found a strong LAI signal (∼30% of climatic signal) on SSO with varying elevation‐ and canopy height‐dependent patterns. Positive correlations or sensitivities, that is, increases in LAI lead to higher SSO, were distributed in relatively cold and wet areas. Biophysical effects of permafrost greening on surface albedo, evapotranspiration, and soil moisture (SM) could link the connection between LAI and SSO. Increased LAI substantially reduced surface albedo and enhanced evapotranspiration, influenced energy redistribution, and further controlled interannual variability of SSO. We also found contrasting effects of LAI on surface SM, consequently leading to divergent impacts on SSO. The results offer a fresh perspective on how greening affects the thermal balance and dynamics of permafrost, which is enlightening for improved permafrost projections. Plain Language Summary: Climate change has caused substantial vegetation growth that was detected by satellite observations ("greening") over northern permafrost regions. However, the consequences or feedbacks of vegetation greening remain largely unknown, hindering the understanding of near‐surface thermal dynamics and bringing considerable uncertainty in model projections. Here we aimed to decipher the biophysical impact of permafrost greening on the summer surface offset (SSO), which is an indicator of permafrost degradation. We found latitude‐ and biome‐dependent patterns of SSO changes and divergent responses of SSO to greening. Increases in satellite‐observed leaf area index lead to higher SSO in relatively cold and wet areas but lower SSO in warm‐dry regions. Biophysical mechanisms associated with surface albedo, evapotranspiration, and SM can help explain various effects of greening on SSO. Our results highlight greening feedbacks on the thermal dynamics of permafrost with climate warming, calling for the improvement of current projections. Key Points: Vegetation greening impacts the thermal dynamics of permafrost surfaceBiophysical effects of greening on surface offset could be related to surface albedo, evapotranspiration, and soil moisture [ABSTRACT FROM AUTHOR]

Copyright of Arid Land Geography is the property of Chinese Academy of Sciences, Xinjiang Institute of Ecology & Geography and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Anthropogenic climate change is increasing the occurrence of wildfires, especially in northern high latitudes, leading to a shift in land surface climate. This study aims to determine the predominant climatic effects of fires in boreal forests to assess their impact on vegetation composition, surface albedo, and snow dynamics. The influence of fire-induced changes on Earth's radiative forcing is investigated, while considering variations in burn severity and postfire vegetation structure. Six burn sites are explored in central Alaska's boreal region, alongside six control sites, by utilizing Moderate Resolution Imaging Spectroradiometer (MODIS)-derived albedo, Leaf Area Index (LAI), snowmelt timing data, AmeriFlux radiation, National Land Cover Database (NLCD) land cover, and Monitoring Trends in Burn Severity (MTBS) data. Key findings reveal significant postfire shifts in land cover at each site, mainly from high- to low-stature vegetation. A continuous increase in postfire surface albedo and negative surface shortwave forcing was noted even after 12 years postfire, particularly during the spring and at high-severity burn areas. Results indicate that the cooling effect from increased albedo during the snow season may surpass the warming effects of earlier snowmelt. The overall climate impact of fires depends on burn severity and vegetation composition. [ABSTRACT FROM AUTHOR]

Abstract Satellite observations have shown widespread greening during the last few decades over the northern permafrost region, but the impact of vegetation greening on permafrost thermal dynamics remains poorly understood, hindering the understanding of permafrost‐vegetation‐climate feedbacks. Summer surface offset (SSO), defined as the difference between surface soil temperature and near‐surface air temperature in summer (June‐August), is often predicted as a function of surface thermal characteristics for permafrost modeling. Here we examined the impact of leaf area index (LAI), detected by satellite as a proxy to permafrost vegetation dynamics, on SSO variations from 2003 to 2021 across the northern permafrost region. We observed latitude‐ and biome‐dependent patterns of SSO changes, with a pronounced increase in Siberian shrublands and a decrease in Tibetan grasslands. Based on partial correlation and sensitivity analyses, we found a strong LAI signal (∼30% of climatic signal) on SSO with varying elevation‐ and canopy height‐dependent patterns. Positive correlations or sensitivities, that is, increases in LAI lead to higher SSO, were distributed in relatively cold and wet areas. Biophysical effects of permafrost greening on surface albedo, evapotranspiration, and soil moisture (SM) could link the connection between LAI and SSO. Increased LAI substantially reduced surface albedo and enhanced evapotranspiration, influenced energy redistribution, and further controlled interannual variability of SSO. We also found contrasting effects of LAI on surface SM, consequently leading to divergent impacts on SSO. The results offer a fresh perspective on how greening affects the thermal balance and dynamics of permafrost, which is enlightening for improved permafrost projections.

Agricultural water resources consumption and soil salinity interact with the distribution of radiation energy in arid salinized farmland. Understanding the temporal changes in energy distribution is necessary to enhance water resource use efficiency. Based on two years of monitoring the energy fluxes in a salinized sunflower field, it was found that field energy fluxes were dependent on available energy, and the temporal dynamics of energy distribution was strongly influenced by crop growth. As expected, soil moisture and meteorological conditions were the main factors limiting latent heat (LE) fluxes in the relatively dry year, with leaf area index showing a more significant positive correlation with LE under abundant soil moisture. Furthermore, path analysis revealed that soil moisture affected energy distribution at budding and flowering stages through the negative regulation of soil surface heat fluxes and the positive regulation of LE. The accumulation of soil salt decreased LE (with Pearson correlation coefficient of −0.59 and a total effect of −0.55), and positive regulated sensible heat (with Pearson correlation coefficient of 0.27 and a total effect of 0.31). Additionally, approximately 40% of actual evapotranspiration was contributed by groundwater, potentially influencing energy fluxes. Moreover, a negative correlation was observed between surface albedo and salinity, which might be another pathway influencing energy distribution. Our findings are important to understand energy distribution and water consumption during the crop growth period in salinized field in arid area.

The radiative budget is one of the key factors that influences climate change. The aim of this study was to analyze the radiative regime in Moscow using the RAD-MSU(BSRN) complex and to estimate the radiative effects of the main geophysical factors during the 2021–2023 period. This complex is equipped and maintained according to the recommendations of the Baseline Surface Radiation Network; however, it is not a part of this network. In cloudless conditions, the decrease in global shortwave irradiance (Q) is about 18–22% due to the aerosol content with a pronounced change in the direct to diffuse ratio. In winter, the increase in Q is about 45 W/m2 (or 9%) at h = 30° due to a high surface albedo and reduced aerosol and water vapor contents, while the net shortwave irradiance (Bsh) demonstrates a significant decrease due to the prevailing effects of snow albedo. In cloudy conditions, a nonlinear dependence of Q and Bsh cloud transmittance on the relative sunshine duration is observed. The mean changes in Q for the 2021–2023 against the 1955–2020 period are characterized by negative anomalies (−22%) in winter and positive anomalies in summer (+3%) due to the changes in cloudiness. This is in line with the global tendencies in the long-term changes in shortwave irradiance in moderate climates in Europe in recent years. [ABSTRACT FROM AUTHOR]

Scientific innovation is overturning conventional paradigms of forest, water, and energy cycle interactions. This has implications for our understanding of the principal causal pathways by which tree, forest, and vegetation cover (TFVC) influence local and global warming/cooling. Many identify surface albedo and carbon sequestration as the principal causal pathways by which TFVC affects global warming/cooling. Moving toward the outer latitudes, in particular, where snow cover is more important, surface albedo effects are perceived to overpower carbon sequestration. By raising surface albedo, deforestation is thus predicted to lead to surface cooling, while increasing forest cover is assumed to result in warming. Observational data, however, generally support the opposite conclusion, suggesting surface albedo is poorly understood. Most accept that surface temperatures are influenced by the interplay of surface albedo, incoming shortwave (SW) radiation, and the partitioning of the remaining, post‐albedo, SW radiation into latent and sensible heat. However, the extent to which the avoidance of sensible heat formation is first and foremost mediated by the presence (absence) of water and TFVC is not well understood. TFVC both mediates the availability of water on the land surface and drives the potential for latent heat production (evapotranspiration, ET). While latent heat is more directly linked to local than global cooling/warming, it is driven by photosynthesis and carbon sequestration and powers additional cloud formation and top‐of‐cloud reflectivity, both of which drive global cooling. TFVC loss reduces water storage, precipitation recycling, and downwind rainfall potential, thus driving the reduction of both ET (latent heat) and cloud formation. By reducing latent heat, cloud formation, and precipitation, deforestation thus powers warming (sensible heat formation), which further diminishes TFVC growth (carbon sequestration). Large‐scale tree and forest restoration could, therefore, contribute significantly to both global and surface temperature cooling through the principal causal pathways of carbon sequestration and cloud formation. [ABSTRACT FROM AUTHOR]

Desertification is one of the factors in the destruction of natural ecosystems in arid regions of the world. Knowing the areas exposed to desertification is very important to combat this phenomenon. Remote sensing is a practical tool for evaluating and monitoring land degradation and desertification. The current research aims at the desertification intensity evaluation in Bandar Mahshahr County based on the spectral indices derived from satellite images. To begin with, utilized the ENVI software to extract several indices, such as NDVI, SAVI, RVI, TGSI, and Albedo, from the satellite image captured by the Landsat 8 OLI in the region. Then, Linear regression was utilized to determine correlations of spectral indices in the region, and the desertification intensity in the region was classified. The results showed that the correlation coefficient between NDVI and Albedo indices was -0.83, between SAVI and Albedo indices was -0.78, and between RVI and Albedo indices was -0.77. The correlation coefficient between TGSI and Albedo indices was 0.86. The higher correlation between TGSI and Albedo indicates that the Albedo-TGSI model is more appropriate for evaluating the desertification intensity in the region. The desertification map of the Albedo-TGSI model showed that the areas with less desertification intensity are located mainly in the northern and eastern parts, and the areas with more desertification intensity were situated in the southern and southwestern parts of the region. [ABSTRACT FROM AUTHOR]

Solid precipitation is not only the main supply for glacier mass, but also exerts an important influence on surface albedo and intensifies glacier melting. However, precipitation type observation is very scarce in the high alpine glaciers, which limits the precise simulation of glacier mass balance. This study assessed three discrimination methods of precipitation types including Ding method, Dai method and Froidurot method based on surface albedo observation data on the Laohugou Glacier No. 12 (LHG Glacier) in western Qilian Mountains. The results showed that Ding method had a best applicability on the LHG Glacier, the other two need to calibrate parameters when they are used in the high elevation glacier region. Then we fitted the relationship between snowfall probability and fresh snow albedo, and put forward a revised formula to simulate fresh snow albedo based on Ding method, which is expected to reduce the uncertainty in glacier mass and energy balance model. Finally, we found a best air temperature threshold of 4°C for discriminating monthly precipitation types. In order to accurately simulate the glacier melt, it is necessary to obtain the threshold temperature appropriately in different glacier region with different elevation and humidity. [ABSTRACT FROM AUTHOR]

Satellite-based surface albedo data are widely used to monitor and analyse the global climate and environmental changes. Korea continuously retrieves surface albedo from the Communication, Ocean and Meteorological Satellite (COMS)/Meteorological Imager sensor (MI) and GEO-KOMPSAT-2A (GK-2A)/Advanced Meteorological Imager sensor (AMI). However, the quality of these surface albedo outputs differs due to differences in the algorithms, input data and resolution, which limits their long-term use as climate data. By analyzing errors in the surface albedo data from COMS/MI and GK-2A/AMI and applying corrections, continuous climate monitoring can be enhanced. This study developed a correction model based on machine learning using multiple linear regression (MLR), random forest (RF) and deep neural network (DNN) models to consider the albedo data error characteristics of each satellite. The best performing RF model was used for correction. The errors of the corrected RF COMS/MI data were reduced; when validated with insitu data, the Root Mean Square Error (RMSE) of the COMS/MI improved from 0.056 to 0.023, similar to the RMSE of 0.019 of GK2A/AMI. It also showed stability in the time series validation with GLASS satellite data, with a consistent mean RMSE of 0.036. [ABSTRACT FROM AUTHOR]

In polar regions, positive feedback of snow and ice albedo can intensify global warming. While recent significant decreases in Arctic surface ice albedo have drawn considerable attention, Antarctic surface albedo variability remains underexplored. Here, satellite albedo product CLARA-A2.1-SAL is first validated and then used to investigate spatial and temporal trends in the summer albedo over the Antarctic from 1982 to 2018, along with their association with Antarctic sea ice changes. The SAL product matches well surface albedo observations from eight stations, suggesting its robust performance in Antarctica. Summer surface albedo averaged over the entire ice sheet shows a downward trend since 1982, albeit not statistically significant. In contrast, a significant upward trend is observed in the sea ice region. Spatially, for ice sheet surface albedo, positive trends occur in the eastern Antarctica Peninsula and the margins of East Antarctica, whereas other regions exhibit negative trends, most prominently in the Ross and Ronne ice shelves. For sea ice albedo, positive trends are observed in the Ross Sea and the Weddell Sea, but negative trends are observed in the Bellingshausen and the Amundsen Seas. Between 2016 and 2018, an unusual decrease in the sea ice extent significantly affected both sea ice and Antarctic ice sheet (AIS) surface albedo changes. However, for the 1982–2015 period, while the effect of sea ice on its own albedo is significant, its impact on ice sheet albedo is less apparent. Air temperature and snow depth also contribute much to sea ice albedo changes. However, on ice sheet surface albedo, the influence of temperature and snow accumulation appears limited. [ABSTRACT FROM AUTHOR]

The surface radiation data observed from June 2020 to June 2021 at the Tashkurgan National Basic Climate Station on the Eastern Pamir Plateau were used to analyze the variations of radiation components and surface albedo in various time scales and weather conditions over this region.The results show that： （1） the variation of radiation flux in the daily average value shows a "V" curve； the annual exposure of downward shortwave radiation， upward shortwave radiation， downward longwave radiation， upward longwave radiation and net radiation are 5001.6， 1370.3， 6090.7， 8550.8 and 1189.0 MJ·m-2， respectively.On the seasonal scale， the radiation flux variations present the patterns with presummer > spring > autumn > winter， and the upward shortwave radiation is highest in winter.（2） with changing weather， the radiation flux is different.when it is sunny， all the radiation flux changes are smoother single-peak type， when it is less cloudy and cloudy， the they are irregular single-peak type， when it is precipitation， they are multi-peak type excepting in winter， the mean radiation flux changes perform sunny > less cloudy > cloudy > precipitation.（3） The average value of surface albedo during the observation period is 0.29， the maximum value occurs in January and the minimum value occurs in July， at 0.58 and 0.24 respectively； seasonally， the surface albedo is maximum in winter and minimum in summer； the surface albedo is "U"-shaped in spring， summer and autumn， and inverted "U"-shaped in winter.The surface albedo values decreasewhen it rains and increase when it snows， indicating that the precipitation types have different effects on the surface albedo.

Nighttime light (NTL) can provide valuable information about human activities. The temporal NTL variation has been previously explored, but the effect of environmental factors has not been fully considered. Here, this article focused on the environmental effect on NTL time series in China, using the visible infrared imaging radiometer suite (VIIRS) monthly products, Earth Observations Group (EOG) product, and Black Marble product, from January 2014 to December 2020. It was found that the NTL variations were statistically correlated with aerosols, vegetation, and surface albedo. NTL variations were negatively correlated with aerosol and vegetation, but positively correlated with surface albedo. Aerosol optical depth was important to explain the NTL variation among environmental factors. In 79% of urban areas in China, the adjusted R-squared of NTL and the three factors surpassed that of NTL and the two factors (vegetation and surface albedo) based on EOG product. In 60% of urban areas in China, the adjusted R-squared of NTL and the three factors surpassed that of NTL and the two factors (vegetation and surface albedo), based on Black Marble product. Both EOG monthly product and Black Marble monthly product were affected by aerosols, surface albedo, and vegetation at multiple scales. However, Black Marble product was less affected by aerosols than EOG product. This article suggests that environmental effect is crucial in the NTL variation. Understanding NTL temporal variation can improve the accuracy of time series VIIRS imagery for socioeconomic applications.

Identifying the main factors influencing the land surface temperature (LST) of each local climate zone (LCZ) built type is of great significance for controlling LST. This study investigated the main factors influencing the LST of each LCZ built type in two Asian megacities: Tokyo and Shanghai. Each area in both megacities was classified according to the LCZ scheme. The diurnal LST, pervious surface fraction (PSF), surface albedo (SA), average building height ( 〈 B H 〉 ), and gross building coverage ratio (λp) of each LCZ were also calculated. Finally, the influence of the properties of each LCZ built type on LST was investigated. The results demonstrated that the main factors influencing LST of different LCZ built types differed in Tokyo and Shanghai. 〈 B H 〉 was the main factor influencing LST for compact mid-rise and open high-rise types in Tokyo, and the compact mid-rise type in Shanghai; PSF was the main factor influencing LST for other LCZ built types. Moreover, both 〈 B H 〉 and PSF negatively correlated with LST. Based on the above results and characteristics of each LCZ built type, specific LST mitigation strategies for each LCZ built type were proposed for Tokyo and Shanghai. The approach in this study can contribute to perspectives for urban planners and policymakers to develop highly feasible and reasonable LST mitigation strategies. [ABSTRACT FROM AUTHOR]

Deforestation is an important environmental problem and a key promoter of regional climate change through modifying the surface albedo. The objective of this research was to characterize the impact of deforestation and land use changes on surface albedo (α) and climate patterns in a tropical highland region of Mexico, between the years 2014 and 2021. The main land cover types are coniferous forests (CF), oak and gallery woodlands (OGW), and annual agriculture (AA), which represent more than 88% of the regional territory. We used 2014 and 2021 Landsat 8 OLI images with topographic and atmospheric correction in order to develop an inventory of albedo values for each land cover type in both time scenarios. Albedo images were generated by using the equation proposed by Liang in 2001, which is based on the reflectance of the bands 2, 3, 4, 5, and 7. Differences in albedo values were calculated between the years 2014 and 2021, and those differences were correlated with variations in climate parameters, for which we used climate data derived from the WRF model. In addition, the different land use changes found were classified in terms of triggers for increasing or decreasing surface albedo. We used the Mann–Whitney U Test to compare the 2021 − 2014 climatic deviations in two samples: Sample A, which included sites without albedo change in 2021; and Sample B, including sites with albedo change in 2021. Results showed that between 2014 and 2021, at least 38 events of land use change or deforestation occurred, with albedo increments between 1 and 11%, which triggered an average increment of 2.16% (p < 0.01; Mann–Whitney U Test) of the regional surface albedo in comparison to the 2014 scenario. In this period, the albedo for CF, OGW, and AA also increased significantly (p < 0.001; Mann–Whitney U Test) by +79, +12, and +9%, respectively. In addition, the regional albedo increment was found to be significant and negatively correlated (p < 0.01 Spearman's coefficient) with relative humidity (RH), maximum temperature (Tmax), and minimum temperature (Tmin), and correlated (p < 0.01) positively with diurnal temperature range (DTR). The Mann–Whitney U Test revealed that 2021 climatic variations in Sample B sites are statistically different (p < 0.05) to 2021 climatic variations in Sample A sites, which demonstrates that albedo changes are linked to a decrease in minimum temperature and relative humidity and an increase in DTR. Conversion of CF and OGW into AA, perennial agriculture (PA), or grassland (GR) always yielded an albedo increment, whilst the conversion of AA to irrigation agriculture (IA) or PA triggered a decrease in albedo, and finally, the pass from GR or AA to protected agriculture (PA) caused albedo to increase or decrease, depending on the greenhouse covers materials. Reducing deforestation of CF and OGW, conversion of AA or GR into PA, and selecting adequate greenhouse covers could help to mitigate regional climate change. [ABSTRACT FROM AUTHOR]

It can be challenging to fuse remotely-sensed images with large differences in spatial resolutions. In this paper, we used additive wavelet transform (AWT) to fuse Landsat-8 (30 m) and unmanned aerial vehicle (UAV) images (7 cm and 3.7 cm for thermal and multispectral images, respectively) as one of the primary studies. AWT image fusion generated sharpened Landsat-8 (L-8) images which were significantly correlated with coarse resolution images, while also well preserving the spatial details. Surface albedo (α0), normalized difference vegetation index (NDVI), and surface temperature (ST) were computed from multispectral and thermal sensors on board of UAV and L-8 platforms. High-resolution UAV and AWT sharpened L-8 images were then used in ETLook model to estimate evapotranspiration (ET) across an agricultural farm enriched with century-old biochar. High spatio-temporal analysis demonstrated a significant decrease in α0 across the biochar patches during the early development stages of winter wheat. Moreover, biochar significantly stimulated the development of wheat canopies towards the middle of the cropping season. There were however no impacts at the end of the season due to dense wheat canopies covering the aggravated dark colour soil across the biochar patches. ST was not affected by biochar either at the beginning or towards the end of the season. Neither was there any impact of biochar on actual ET over the season. Our approach can help to develop robust techniques for fusion of UAV and satellite images in light of climate-smart agriculture, and is also applicable to other farms with any specific precision agricultural treatments.

Copyright of Plateau Meteorology is the property of Plateau Meteorology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Management practices that increase the surface albedo of cultivated land could mitigate climate change, with similar effectiveness to practices that reduce greenhouse gas emissions or favor natural CO _2 sequestration. Yet, the efficiency of such practices is barely quantified. In this study, we quantified the impacts of seven different management practices on the surface albedo of winter wheat fields (nitrogen fertilizer, herbicide, fungicide, sowing, harvest, tillage, and crop residues) by analyzing observed daily albedo dynamics from eight European flux-tower sites with interpretable machine learning. We found that management practices have significant influences on surface albedo dynamics compared with climate and soil conditions. The nitrogen fertilizer application has the largest effect among the seven practices as it increases surface albedo by 0.015 ± 0.004 during the first two months after application, corresponding to a radiative forcing of −4.39 ± 1.22 W m ^−2 . Herbicide induces a modest albedo decrease of 0.005 ± 0.002 over 150 d after application by killing weeds in the fallow period only, resulting in a magnitude of radiative forcing of 1.33 ± 1.06 W m ^−2 which is higher than radiative forcing of other practices in the same period. The substantial temporal evolution of the albedo impacts of management practices increases uncertainties in the estimated albedo-mediated climate impacts of management practices. Although these albedo effects are smaller than published estimates of the greenhouse gas-mediated biogeochemical practices, they are nevertheless significant and should thus be accounted for in climate impact assessments.

Nature-based solutions for mitigating climate change focus largely on land management to reduce carbon emissions and enhance carbon sequestration. Tree planting, commonly advocated for carbon offset, threatens grassland biodiversity and may induce positive radiative forcing (warming) by lowering albedo. Before making decisions about land-use changes in grasslands, an understanding of the fine-scale albedo of grassy versus woody vegetation is needed. Existing satellite-based albedo products offer global coverage with temporally fine, but spatially coarse, resolution, whereas fine-scale in situ grassland albedo data are sparse. We examined the hypotheses that albedo varies seasonally between grass type patches, between shrub and grass patches, and with grazing at the patch scale. Using a tripod-mounted albedometer, we quantified albedo of seven distinct grassland patches in South Africa’s eastern Karoo during early and late dormancy and growing seasons. Patches included intensely-grazed grazing lawn ( Cynodon dactylon ), grazed and less-grazed red tussock grass ( Themeda triandra ), grazed and less-grazed white tussock grass ( Eragrostis lehmanniana ), shrub ( Pentzia incana ) encroached grass, and bare ground. Season influenced albedo in all patches and, additionally, we found strong differences for the same period between years due to varying rainfall and temperature patterns. For grass-dominated patches, albedo differences were most pronounced during early dormancy, likely due to an effect of grass inflorescences. Albedo of intensely-grazed grazing lawns was consistently higher than other patches, except during early dormancy when white tussock grass albedo was equally high. We found no albedo difference between grazed and less-grazed tussock patches of either red or white grass. Shrub-encroached patches exhibited consistently lower albedo than other patches. Our findings underscore the nuanced relationship between grassland patches and albedo, with shrub encroachment, proposed afforestation, and certain grasses possibly increasing warming potential through reduced albedo. As climate initiatives extend into grasslands, understanding these patterns is essential for climate change mitigation and grassland conservation.

The paper aims to compare the accuracy of three methods of solving the atmospheric correction problem for a Lambertian surface using high spatial resolution remotely sensed data. Three couples of formulas are presented. Each couple contains a formula for expressing the reflectance in a target pixel at the upper boundary of the atmosphere via albedo in target and adjacent pixels of the surface and a formula for the surface albedo in a target pixel via reflectances. The derivation of each couple of formulas is given. Derivation conditions are presented. Formulas of only one couple are found by solving the radiation transport equation in 1D geometry. Formulas of two other couples include values obtained by solving the transport equation in 3D geometry. Results of testing the accuracy of all formulas when solving an atmospheric correction problem on data of high (30 m) spatial resolution are given. Problems with aerosol optical depths from 0.2 to 2 for a wavelength of (lambda)=0.55(mu)m for all possible albedo values (from 0.1 to 0.9) in target and adjacent pixels are considered. It is shown that only one couple of formulas out of the three gives high accuracy under any condition. Formulas of the two other couples give sufficient accuracy (with less than 10 % error) only for a small value of the aerosol optical depth and a small difference of the albedo of the target and adjacent pixels.

A two-dimensional energy balance climate model has been built to investigate the climate on Mars. The model takes into account the balance among solar radiation, longwave radiation, and energy transmission and can be solved analytically by Legendre polynomials. With the parameters for thermal diffusion and radiation processes being properly specified, the model can simulate a reasonable surface atmospheric temperature distribution but not a very perfect vertical atmospheric temperature distribution compared with numerical results, such as those from the Mars Climate Database. With varying solar radiation in a Martian year, the model can simulate the seasonal variation of the air temperature on Mars. With increasing dust content, the Martian atmosphere gradually warms. However, the warming is insignificant in the cold and warm scenarios, in which the dust mixing ratio varies moderately, whereas the warming is significant in the storm scenario, in which the dust mixing ratio increases dramatically. With an increasing albedo value of either the polar cap or the non-ice region, Mars gradually cools. The mean surface atmospheric temperature decreases moderately with an increasing polar ice albedo, whereas it increases dramatically with an increasing non-ice albedo. This increase occurs because the planetary albedo of the ice regions is smaller than that of the non-ice region.

The aerosol direct radiative effect (ADRE) is controlled by both aerosol distributions and environmental factors, making it interesting and important to quantitatively assess their effects on the ADRE inhomogeneity and climate trends. By analyzing the ADRE in the 21st century from a global reanalysis data set, we find that the spatial variability of the ADRE and its trends can be well explained by a linear regression model. In this model, scattering and absorbing aerosol optical depths (AODs) are used, along with critical environmental variables such as surface albedo and cloud radiative effect, as predictors. Based on this model, we find that approximately 70% of the ADRE inhomogeneity is due to the AOD distributions and the remainder is attributable to environmental factors. This study also shows that a stronger cooling effect of the scattering aerosols in the Northern Hemisphere drives northward cross‐equator meridional energy transport, although this transport exhibits a declining trend over the last two decades. The changes in surface albedo and cloud radiative effect strongly influence the trends in the regional ADRE and the meridional energy transport driven by them. In particular, the reduction of surface albedo (sea ice) is primarily responsible for the enhancement of the cooling ADRE, as well as an associated trend in meridional energy transport, in the Arctic. Plain Language Summary: Aerosols are particles produced by natural events such as volcanic eruptions and anthropogenic emissions such as fossil fuel combustion. They can scatter and absorb incoming solar radiation, leading to a strong local cooling or warming effect on the Earth's climate. The impact of aerosols on the Earth's radiative balance is known as the aerosol direct radiative effect (ADRE). Factors that can affect ADRE include the types and amounts of aerosols and the environmental conditions such as surface albedo and clouds. This study proposed a regression model to predict the distributions and trends of global ADRE. According to the results, 70% of the ADRE variability is contributed by aerosols, while the rest is influenced by surface albedo and clouds. The high aerosol concentrations in the Northern Hemisphere require energy to be transported from the South Hemisphere to the North. However, this demand has decreased over the past two decades. Changes in surface albedo and clouds have a significant impact on the ADRE trend. In particular, the retreating sea ice plays a major role in the ADRE trend in the Arctic. Key Points: Nonaerosol factors contribute significantly to the spatial inhomogeneity of the aerosol direct radiative effect (ADRE) and its trends in recent decadesThe hemispheric difference in scattering aerosols drives northward cross‐equator energy transport, which shows a declining trendChanges in the surface albedo due to sea ice melt strongly influence the ADRE trends in, and the energy transport to, the Arctic [ABSTRACT FROM AUTHOR]

The Surface ALbedo VALidation (SALVAL) online platform is designed to allow producers of satellite-based albedo products to move to operational validation systems. The SALVAL tool integrates long-term satellite products, global in situ datasets, and community-agreed-upon validation protocols into an online and interactive platform. The SALVAL tool, available on the ESA Cal/Val portal, was developed by EOLAB under the framework outlined by the Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) Land Product Validation (LPV) subgroup, and provides transparency, consistency, and traceability to the validation process. In this demonstration, three satellite-based albedo climate data records from different operational services were validated and intercompared using the SALVAL platform: (1) the Climate Change Service (C3S) multi-sensor product, (2) the NASA MODIS MCD43A3 product (C6.1) and (3) Beijing Normal University's Global LAnd Surface Satellites (GLASS) version 4 products. This work demonstrates that the three satellite albedo datasets enable long-term reliable and consistent retrievals at the global scale, with some discrepancies between them associated with the retrieval processing chain. The three satellite albedo products show similar uncertainties (RMSD = 0.03) when comparing the best quality retrievals with ground measurements. The SALVAL platform has proven to be a useful tool to validate and intercompare albedo datasets, allowing them to reach stage 4 of the CEOS LPV validation hierarchy. [ABSTRACT FROM AUTHOR]

The rapid loss of Arctic Sea ice cover and thickness diminishes the surface albedo, which increases the ocean's absorption of solar heat and exacerbates the Arctic amplification effect. According to the most recent research from the Intergovernmental Panel on Climate Change, the Sixth Assessment Report (IPCC, AR6), the extent of summer sea ice is anticipated to decrease below 1 million km2 by the 2050s as a result of the extreme climate. Nevertheless, past and future changes in sea ice albedo radiative forcing and the resulting economic cost remain to be explored in systematic and multi-disciplinary manners. In this study, we first analyze the evolution of Arctic sea ice radiative forcing (SIRF) from 1982 to 2100 using a radiative kernel method based on albedo data from the Polar Pathfinder-Extent (APP-x) and Coupled Model Intercomparison Project 5 (CMIP5). Then, the SIRF is converted to CO2 equivalent emissions via the Dynamic Integrated Model of Climate and Economy (DICE) model. Finally, the associated costs are calculated using the substitute cost method, based on the social cost of carbon to achieve the Paris Agreement targets. The results show that the average Arctic SIRF was −0.75 ± 0.1 W · m − 2 between 1982 and 2020, and increased by 0.12   W · m − 2 during this period. The SIRF in April–June accounts for nearly 77% of the average annual value, with a maximum absolute value of –3.2 W · m − 2 in May. Through model transformation, it is shown that the Arctic SIRF rising leads to global warming comparable to the effect of an increase of 34.5 Gt of CO2 in the atmosphere relative to pre-industrialization, and results in a loss of 24.4–48.8 trillion USD for climate regulation service (CRS). From 2020 to 2100, in the representative concentration pathway (RCP) 8.5, the Arctic SIRF is projected to increase by 0.31   W · m − 2 . Combined with the discount rate, the estimated average annual cost over the period ranges from 6.7–13.3 trillion USD. These findings provide a systematic understanding of the radiative effect of Arctic sea ice change on the global climate and the corresponding economic cost. [ABSTRACT FROM AUTHOR]

The estimation of urban irrigation water requirements has often been approached from an agricultural perspective. This approach is flawed, as the intention of estimating agricultural water is to optimize yield. Recent studies have reported that urban irrigation systems waste about 34% of water, an alarming number for arid cities. The intention for urban irrigation is complex and dependent on the microclimates created by the development of the landscape. In this paper, we investigate the role of the urban landscape on the irrigation water requirements in arid cities. The role of the landscape in determining the irrigation water requirements is examined through the changes in surface-heat energy exchanges. The effects of landscapes are examined through land use change, buildings' geometry and orientation, and vegetation types. The irrigation water requirement is assessed as the function of urban evapotranspiration and irrigation efficiency. The development of land use characteristics includes the transition from undeveloped (natural) surfaces to residential, commercial, road surfaces, or vegetated surfaces. The orientation and geometry of the streets are assessed by changes in sky view factor values due to building geometry. Three landscapes varying in vegetation type and water use are investigated. The study focuses on understanding the heat exchanges and their effects on irrigation water requirements in arid climates. Two major cities were studied: Las Vegas Valley and Phoenix metropolitan. The study concludes that the development of hardscapes, including commercial and road infrastructures, increases the overall surface temperature by 2 °C per unit change in albedo, thereby increasing evapotranspiration and urban irrigation water requirement. In addition, landscape diversity also plays a crucial role in changing the irrigation water requirement. This study highlights the importance of making development decisions in urban settings and their effects on water resources. It also contributes by providing the major factors changing the urban irrigation requirement. The study can help urban water managers and climatologists to develop improved urban irrigation models. [ABSTRACT FROM AUTHOR]

Vegetation cover creates competing effects on land surface temperature: it typically cools through enhancing energy dissipation and warms via decreasing surface albedo. Global vegetation has been previously found to overall net cool land surfaces with cooling contributions from temperate and tropical vegetation and warming contributions from boreal vegetation. Recent studies suggest that dryland vegetation across the tropics strongly contributes to this global net cooling feedback. However, observation‐based vegetation‐temperature interaction studies have been limited in the tropics, especially in their widespread drylands. Theoretical considerations also call into question the ability of dryland vegetation to strongly cool the surface under low water availability. Here, we use satellite observations to investigate how tropical vegetation cover influences the surface energy balance. We find that while increased vegetation cover would impart net cooling feedbacks across the tropics, net vegetal cooling effects are subdued in drylands. Using observations, we determine that dryland plants have less ability to cool the surface due to their cooling pathways being reduced by aridity, overall less efficient dissipation of turbulent energy, and their tendency to strongly increase solar radiation absorption. As a result, while proportional greening across the tropics would create an overall biophysical cooling feedback, dryland tropical vegetation reduces the overall tropical surface cooling magnitude by at least 14%, instead of enhancing cooling as suggested by previous global studies. [ABSTRACT FROM AUTHOR]

In this paper, a method previously developed for reconstructing daily erythemal ultraviolet (UVery) doses in Novi Sad (Serbia) was improved and used for estimating daily UVery over the period 1971–2018. The proposed new method uses reanalysed total ozone column (TOC) data and snow cover as an input and is based on the empirical relationship between relative sunshine duration and relative UVery doses. Introducing reanalysed TOC data and snow cover data significantly improved the quality and accuracy of the reconstructed UVery time series, particularly in the winter season. The reconstructed time series revealed the statistically significant increase in summer and winter UVery in the 1980s and the first half of the 1990s (+8.78% and + 13.14% per decade, respectively), which was linked to the statistically significant decline in TOC (−4.13 and −7.36% per decade, respectively). The study focuses on days with high erythemal UV dose (highUVery), which is defined based on the 90th percentile of the daily UVery for each month. Moreover, the influence of low TOC, low cloud cover conditions, and high surface albedo on highUVery was analysed on a seasonal basis. The results of this study show that highUVery days increased from the 1980s, particularly strongly in the period of TOC depletion. A fraction of highUVery days in the last two decades was large (12.29%), which is higher than in the previous periods (6.97 and 8.68% in the period before and during TOC depletion, respectively). The occurrence of highUVery days was influenced mostly by low cloud cover (89.71% of days), and low TOC (82.23% of days). In the winter season, high surface albedo influenced the appearance of 19.18% of highUVery days. However, overall the interaction of low cloud cover and low TOC in all seasons most often led to the appearance of highUVery days. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As a major crop type in the global agroecosystem, paddy rice fields contribute to global greenhouse gas emissions. Surface albedo plays a vital role in estimating carbon emissions. However, it is difficult to find a broadband albedo estimation over paddy rice fields. The objective of this study was to derive an applicable method to improve albedo estimation over a paddy rice field. Field multiangle reflectance and surface albedo were collected throughout the growing season. A physically based model (AMBRALS) was utilized to reconstruct the directional reflectance into the spectral albedo. Multiple spectral albedos (at the wavelengths of 470, 550, 660, 850, 1243, 1640 and 2151 nm) were calculated, and new narrowband to broadband conversion coefficients were derived between the observed spectral albedo and broadband albedo. The conversion schemes showed high consistency with the field albedo observations in the shortwave (285–3000 nm), infrared (700–3000 nm), and visible (400–700 nm) bands. This method can help improve albedo estimation in partially submerged environments. [ABSTRACT FROM AUTHOR]

Based on the observation data of the meteorological environment monitoring system (QT-1010) and the open vorticity correlation system (LI-7500DS), we used the block aerodynamics and energy balance ratio method to analyze the surface radiation budget and energy balance closure characteristics of the grassland in the eastern arid region of Northwest China at different time scales. We found that (1) The daily variation curve of the surface radiation flux is unimodal, and the variation amplitude of each component is as follows: R s ↓> R L ↑> R L ↓> R s ↑. (2) The monthly peak of each radiation component occurs in summer, and the time of reaching the peak of different components has a lag. The changes of radiation components in sunny and cloudy days are multi-modal. In the precipitation weather, the fluctuation of each radiation flux is unimodal. The average annual surface albedo () is 0.24, which is higher in winter than in summer. There is a linear relationship between surface albedo and soil moisture. (3) The Net radiation (R net) dominates the sensible heat in spring and the latent heat in summer. H/R net and G n /R net are both positive in a day, H/R net and LE/R net fluctuate wildly before and after sunrise, and G n is dominant at night. (4) The energy closure is manifested as summer > winter > Autumn > spring, and the energy closure is good throughout the year. [ABSTRACT FROM AUTHOR]

Obtaining surface albedo data with high spatial and temporal resolution is essential for measuring the factors, effects, and change mechanisms of regional land-atmosphere interactions in deserts. In order to obtain surface albedo data with higher accuracy and better applicability in deserts, we used MODIS and OLI as data sources, and calculated the daily surface albedo data, with a spatial resolution of 30 m, of Guaizi Lake at the northern edge of the Badain Jaran Desert in 2016, using the Spatial and Temporal Non-Local Filter-based Fusion Model (STNLFFM) and topographical correction model (C model). We then compared the results of STNLFFM and C + STNLFFM for fusion accuracy, and for spatial and temporal distribution differences in surface albedo over different underlying surfaces. The results indicated that, compared with STNLFFM surface albedo and MODIS surface albedo, the relative error of C + STNLFFM surface albedo decreased by 2.34% and 3.57%, respectively. C + STNLFFM can improve poor applicability of MODIS in winter, and better responds to the changes in the measured value over a short time range. After the correction of the C model, the spatial difference in surface albedo over different underlying surfaces was enhanced, and the spatial differences in surface albedo between shifting dunes and semi-shifting dunes, fixed dunes and saline-alkali land, and the Gobi and saline-alkali land were significant. C + STNLFFM maintained the spatial and temporal distribution characteristics of STNLFFM surface albedo, but the increase in regional aerosol concentration and thickness caused by frequent dust storms weakened the spatial difference in surface albedo over different underlying surfaces in March, which led to the overcorrection of the C model. [ABSTRACT FROM AUTHOR]

Surface reflectance anisotropy and insufficient multi-angular observations are the main challenges in albedo estimation from satellite observations. Numerous studies have been developed for albedo retrieval from a single directional reflectance by associating the anisotropy information extracted from coarse-resolution bidirectional-reflectance distribution function (BRDF) data. The contribution of land-cover type (LCT) and the Normalized Difference Vegetation Index (NDVI) in distinguishing reflectance anisotropy in these methods remains controversial. This study first proposed an approach to extracting a priori BRDF (F) from the MODIS BRDF/albedo product by considering the distribution characteristics of the model parameters. LCT- and NDVI-based F were also extracted from the corresponding subset. Then, the F-based albedo was derived from simulated or satellite directional reflectance and the anisotropic information of F. Finally, the directional reflectance and F-based albedo were compared with the MODIS albedo or ground measurement, in order to show the ability of F to compensate for the effect of reflectance anisotropy in the albedo retrieval process. The method was fully validated by the global and time-series MODIS BRDF data. The results showed that reflectance anisotropy has an aggregated distribution pattern, and F can represent the reflectance anisotropy of most pixels within a tile. The improvement of LCT and NDVI only occurs when the tile contains a large area of vegetated and barren ground. With the exception of the hotspot and large viewing-zenith-angle area in the forward hemisphere, the F-based shortwave albedo has high consistency with the MODIS albedo product. A comparison with the ground measurements and MODIS albedo showed that the F-based albedo from a single directional reflectance generally achieves an absolute accuracy requirement, with a root-mean-square error (RMSE) of 0.027 and 0.036. [ABSTRACT FROM AUTHOR]