Mean Albedo Research Articles

Asymmetry in the Diurnal Variation of Land Surface Albedo and Its Impacts on Daily Mean Albedo Estimation

AbstractDaily mean albedo, a crucial variable of the earth radiation budget, is significantly affected by the diurnal variation of land surface albedo (DVLSA). The DVLSA typically exhibits asymmetry, thereby affecting the estimation of the daily mean albedo. However, the asymmetry in the DVLSA is generally ignored in daily mean albedo estimation. In this study, we investigated the influencing factors of the asymmetry in the DVLSA and evaluated its impacts on estimating the daily mean albedo based on field observations and simulated data. Our findings reveal that the asymmetry in the DVLSA varies among land cover types, with forests exhibiting more pronounced asymmetry compared to croplands, grasslands, and bare soil. The diurnal variation of the atmospheric conditions is the primary factor controlling the asymmetry in the DVLSA, with that of land surface conditions being a secondary factor. Neglecting the asymmetry in the DVLSA leads to estimation error in daily mean albedo, particularly pronounced during winter. The relative error of daily mean albedo can exceed 10% when the mean asymmetry index of diffuse irradiance fraction reaches 40%. However, the DVLSA retrieved from the satellite Bidirectional Reflectance Distribution Function product inadequately captures asymmetry, resulting in a relative error of approximately 13.7% in estimating daily mean albedo.

Observations and modeling of areal surface albedo and surface types in the Arctic

Abstract. An accurate representation of the annual evolution of surface albedo of the Arctic Ocean, especially during the melting period, is crucial to obtain reliable climate model predictions in the Arctic. Therefore, the output of the surface albedo scheme of a coupled regional climate model (HIRHAM–NAOSIM) was evaluated against airborne and ground-based measurements. The observations were conducted during five aircraft campaigns in the European Arctic at different times of the year between 2017 and 2022; one of them was part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in 2020. We applied two approaches for the evaluation: (a) relying on measured input parameters of surface type fraction and surface skin temperature (offline) and (b) using HIRHAM–NAOSIM simulations independently of observational data (online). From the offline method we found a seasonally dependent bias between measured and modeled surface albedo. In spring, the cloud effect on surface broadband albedo was overestimated by the surface albedo parametrization (mean albedo bias of 0.06), while the surface albedo scheme for cloudless cases reproduced the measured surface albedo distributions for all seasons. The online evaluation revealed an overestimation of the modeled surface albedo resulting from an overestimation of the modeled cloud cover. Furthermore, it was shown that the surface type parametrization contributes significantly to the bias in albedo, especially in summer (after the drainage of melt ponds) and autumn (onset of refreezing). The lack of an adequate model representation of the surface scattering layer, which usually forms on bare ice in summer, contributed to the underestimation of surface albedo during that period. The difference between modeled and measured net irradiances for selected flights during the five airborne campaigns was derived to estimate the impact of the model bias for the solar radiative energy budget at the surface. We revealed a negative bias between modeled and measured net irradiances (median: −6.4 W m−2) for optically thin clouds, while the median value of only 0.1 W m−2 was determined for optically thicker clouds.

Spatiotemporal Evolution of the Land Cover over Deception Island, Antarctica, Its Driving Mechanisms, and Its Impact on the Shortwave Albedo

The aim of this work is to provide a full description of how air temperature and solar radiation induce changes in the land cover over an Antarctic site. We use shortwave broadband albedo (albedo integrated in the range 300–3000 nm) from a spaceborne sensor and from field surveys to calculate the monthly relative abundance of landscape units. Field albedo data were collected in January 2019 using a portable albedometer over seven landscape units: clean fresh snow; clean old snow; rugged landscape composed of dirty snow with disperse pyroclasts and rocky outcrops; dirty snow; stripes of bare soil and snow; shallow snow with small bare soil patches; and bare soil. The MODIS MCD43A3 daily albedo products were downloaded using the Google Earth Engine API from the 2000–2001 season to the 2020–2021 season. Each landscape unit was characterized by an albedo normal distribution. The monthly relative abundances of the landscape units were calculated by fitting a linear combination of the normal distributions to a histogram of the MODIS monthly mean albedo. The monthly relative abundance of the landscape unit consisting of rugged landscape composed of dirty snow with dispersed clasts and small rocky outcrops exhibits a high positive linear correlation with the monthly mean albedo (R2 = 0.87) and a high negative linear correlation with the monthly mean air temperature (R2 = 0.69). The increase in the solar radiation energy flux from September to December coincides with the decrease in the relative abundance of the landscape unit composed of dirty snow with dispersed clasts and small rocky outcrops. We propose a mechanism to describe the evolution of the landscape: uncovered pyroclasts act as melting centers favoring the melting of surrounding snow. Ash does not play a decisive role in the melting of the snow. The results also explain the observed decrease in the thaw depth of the permafrost on the island in the period 2006–2014, resulting from an increase in the snow cover over the whole island.

Compositional characterization of a primordial S-type asteroid family of the inner main belt

Context. Recently, a primordial family of moderate-albedo asteroid fragments was discovered in the inner main belt. Its age was estimated to be 4.4 ± 1.7 Gyr. However, there is a lack of compositional characterization, which is important to the study of the earliest collisions in the main belt. Aims. In addition to the previously identified members and the parameters that define the family’s borders (V shape), we expanded the list of family members to include asteroids located within the central region of the V shape. These additional potential members were selected based on their diameter (larger than 7 km) and their geometric visible albedo (greater than or equal to 12%). Subsequently, we conducted a spectroscopic survey to determine the dominant taxonomy and composition of this family. This allowed us to further refine the list of family members by removing interlopers. Methods. From an initial list of 263 asteroids that are considered to be potential members of the aforementioned primordial family, we retrieved their spectra in the visible and near-infrared range from the literature and from the Gala DR3 spectral catalog of Solar System objects. For asteroids with no or poor signal-to-noise ratio spectra in the literature, we carried out new ground-based observations. We obtained new spectra for 33 members of the family using the 1.82 m Asiago Telescope for the visible spectroscopy, while for near-infrared spectroscopy, we used the 3.58 m Telescopio Nazionale Galileo (TNG) and the 4.30 m Lowell Discovery Telescope (LDT). Results. In total, we collected spectra for 261 potential members of the primordial S-type family out of 263. We determined their spectral taxonomy and properties, such as spectral slopes and absorption band parameters, when existing. Using the taxonomical characterization and the orbital space parameters, we identified and removed 71 interlopers from the potential members list. The final list of the primordial S-type family members includes 190 asteroids. The family is dominated by S-complex (~71%) asteroids with a mineralogy similar to ordinary chondrites and pyroxene-rich minerals. The family also contains members classified as L-types and V-types. (~15% and ~9%, respectively). Conclusions. The mean albedo of the family is ~23%, and its largest probable remnant is the asteroid (30) Urania. The estimated size of the family parent body ranges between 110 and 210 km. This size range is compatible with the progenitor of H and L chondrites.

Balanço de Radiação sobre água de Baixa Turbidez Purificada Artificialmente para Irrigação de Fumo Cultivado sob Sombreamento. II. Análise do Albedo da água e Modelagem da Radiação Líquida

Abstract The albedo of a water surface and the energy available for evaporation are strongly correlated and studying such processes is of paramount importance for water security at farm and regional levels. In this paper, water albedo (αw) and net all-wave radiation (Rn) were analyzed after being measured above the surface of an artificially cleaned and low-turbidity water used for tobacco irrigation. It was observed that αw decreased as the sun elevation (θ) increased, especially for clear and near clear skies. The results showed that αw can be reasonably predicted with a power law model either in terms of θ or Sg (incoming solar radiation) across different cloud cover conditions. From this study, a mean daily albedo of 0.05 is recommended. Three approaches were considered for estimation of daily Rn. In the first, a linear regression model strongly fitted Rn data in terms of Sg solely. The second option based on the definition of Rn was [0.95Sg - Lnet(56)], where Lnet(56) is net longwave (LW) radiation as used in the FAO56 model for reference evapotranspiration estimation, and the third was [0.95Sg - Lnet(MLR)], where MLR stands for multiple linear regression. The disadvantages of approaches (1) and (3), based on regressions, is that they are constrained to the type of water stored in the farm and the climatic conditions of the region. The performance of approach (2), where Lnet(56) is a widely used model, was comparable to the others can potentially be improved with a site-specific calibration. All three approaches for estimating daily Rn proposed in this study can possibily be extended to clear water that did not go through any filtration process.

A Direct Estimation Method for Daily Mean Albedo With Multiple Observations From FY-4A AGRI and Himawari-8 AHI

A Direct Estimation Method for Daily Mean Albedo With Multiple Observations From FY-4A AGRI and Himawari-8 AHI

An evaluation of the NOAA global daily gap-filled VIIRS surface albedo

The land surface albedo product of visible infrared imaging radiometer suite (VIIRS) in National Oceanic and Atmospheric Administration (NOAA)’s operational system provides real-time, global daily mean surface albedo, which is a required parameter in the estimation of the daily shortwave net radiation budget. The global gridded VIIRS albedo product is derived from the level-2 granule surface albedo product, which is generated using a Direct Estimation Method. Special gridding and compositing algorithms were developed for aggregating the granular albedo data into the gridded albedo product. This paper describes the design and evaluation of the NOAA VIIRS gridded daily surface albedo product. The cloudy condition, retrieval path, retrieval method, and observing geometry are the criteria in deciding the priority order in the composition processing. The proposed albedo product possesses a complete spatial coverage over global land and ice surface and provides a timely response to surface dynamics. The validation of satellite retrieved daily mean albedo against ground counterparts over a series of well-maintained networks demonstrates the reliability of the composed albedo considering the interference of the seasonal surface heterogeneity conditions around each site. The inter-comparison between the S-NPP and NOAA-20 VIIRS albedo shows good agreement, except for a minor bias related to solar/view angle differences. The cross-comparison between VIIRS albedo and MODIS albedo shows good consistency with some deviations related to the controversy between their upstream snow mask.

Modeling of surface energy balance for Icelandic glaciers using remote-sensing albedo

Abstract. During the melt season, absorbed solar energy, modulated at the surface by albedo, is one of the main governing factors controlling surface melt variability for glaciers in Iceland. An energy balance model was applied with the possibility of utilizing spatiotemporal Moderate Resolution Imaging Spectroradiometer (MODIS) satellite-derived daily surface albedo driven by high-resolution climate forcing data to reconstruct the surface energy balance (SEB) for all Icelandic glaciers for the period 2000–2021. The SEB was reconstructed from April through September for 2000–2021 at a daily time step with a 500 m spatial resolution. Validation was performed using observations from various glaciers spanning distinct locations and elevations with good visual and statistical agreement. The results show that spatiotemporal patterns for the melt season have high annual and interannual variability for Icelandic glaciers. The variability was influenced by high climate variability, deposition of light-absorbing particles (LAPs) from volcanic eruptions and dust hotspots in pro-glacial areas close to the glaciers. Impacts of LAPs can lead to significant melt enhancement due to lowering of albedo and increased short-wave radiative energy forced at the surface. Large impacts on the SEB were observed for years with high LAP deposits, such as the volcanic eruption years of 2004, 2010 and 2011 and the sand- and dust-rich year of 2019. The impacts of volcanic eruptions and other LAP events were estimated using historical mean albedo under the same climatology forcing to provide estimations of melt energy enhancements. The impact of LAPs was often significant even though the glaciers were far away from the eruption location. On average, the melt enhancements due to LAPs were ∼27 % in 2010, ∼16 % in 2011 and ∼14 % in 2019 for Vatnajökull, Hofsjökull and Langjökull.

Changes in glacier albedo and the driving factors in the Western Nyainqentanglha Mountains from 2001 to 2020

AbstractGlacier surface albedo dominates glacier energy balance, thus strongly affecting the glacier mass balance. Glaciers in the Western Nyainqentanglha Mountains (WNM) experienced large mass losses in the past two decades, but long-term changes of glacier albedo and its drivers are less understood. In this study, we retrieved glacier albedo with MODIS reflectance data to characterize the spatiotemporal variability of albedo from 2001 to 2020. Air temperature, rainfall, snowfall and deposition of light-absorbing impurities (LAIs) were evaluated as potential drivers of the observed variability in glacier albedo. The results showed that: (1) the glacier albedo experienced large inter-annual fluctuations, with the mean albedo being 0.552 ± 0.002 and a clear decreasing trend of 0.0443 ± 2 × 10−4 dec−1 in the WNM. The fastest decline was observed in autumn and in the vicinity of the equilibrium line altitude, indicating an extended melt season and an expansion of the ablation region to higher elevation; (2) local meteorology and LAIs deposition are the main drivers of glacier albedo change, but their effects on seasonal albedos are different due to different glacier processes. Both air temperature and the balance between liquid and solid precipitation affect summer and autumn albedos due to glacier ablation. Air temperature is the main driver of spring and winter albedos due to sublimation and metamorphism of snow, while snowfall carried by westerlies has limited influence on these two seasonal albedos due to less snowfall. LAIs mainly affect spring albedo due to high concentration coupled with the southerly wind in spring. These findings highlight the significance of changes in glacier albedo and the key role of local meteorology and LAIs deposition in determining such changes, which play an important role in glaciological and cryosphere processes.

Long-term trends in albedo as seen from a lunar observatory

The Earth’s albedo is the fraction of short-wave solar radiation that is reflected back to space, and is key to understand the observed trends in climate change. Although there have been many observational approaches to estimate the Earth’s albedo, different methods have their own drawbacks, for example, artificial satellites have a finite life time, and are operating in a hard environment that could quickly degrade the detectors. The Moon, the only natural satellite of Earth, offers an additional platform for monitoring the Earth’s albedo. In this paper, we calculate the global TOA (top-of-atmosphere) albedo that would be observed by a theoretical observatory on the Moon, and compare it with long-term trends derived from CERES (Clouds and the Earth’s Radiant Energy System, 2000–2020) and earthshine data (1999–2017). We find that the global hourly mean albedo observed in the direction of the Moon is more variable because of the orbital movement of the Moon. However, the regional and long-term global mean albedo anomalies that would be observed by CERES and has a good general agreement by a lunar observer over 20 years the data spans. Similarly, earthshine data show a steady decline during two decades of about 0.7 W/m2 which is in line with the decline of 0.5 W/m2 that would be observed from the Moon. Besides, to compare the regional changes of albedo with CERES, the spatially-resolved decadal anomalies in the albedo are also calculated for analysis. We find that a lunar-based observatory would be capable of detecting similar changes seen from CERES. Thus, it is a a practical option to monitor the long-term trends in albedo from the point of view of capturing the variability in the TOA fluxes of the Earth’s atmosphere.

Monitoring of land surface albedo and its impact on land surface temperature (LST) using time series of remote sensing data

Urbanization and urban population growth are increasing every day across the world. The replacement of natural surfaces with artificial surfaces such as bitumen, asphalt, and cement reduces albedo, increases the land surface temperature (LST), and contributes to creating urban heat islands (UHI). In this study, Landsat satellite time-series images were used to produce land use/land cover (LULC) and calculate albedo, LST, and normalized differential vegetation index (NDVI) in the 1985–2018 period of Tabriz. The results demonstrated an over 170% increase in the area of impervious surfaces. Monitoring of albedo and LST in the 1996–2018 period showed that reflective surfaces could reduce the mean temperature of impervious surfaces in the entire city by 4.42 °C and increase the mean albedo by 0.0647. Meanwhile, LST was decreased by 7.97 °C and albedo was increased by 0.1633 in densely populated urban areas. The Pearson correlation coefficient between LST and albedo in the impervious surface class was −0.6 for the entire city, which is higher than the correlation between NDVI and LST parameters in the vegetation class. Therefore, reflective surfaces can reduce the surface temperature more efficiently than vegetation. It is worth mentioning that this correlation reaches up to −0.8 in urban districts. The research findings showed that urban growth and the increasing area of impervious surfaces could create urban cold islands instead of urban heat islands if reflective surfaces are used in the rooftops.

A comparative study of long-time series of global-scale albedo products

ABSTRACT Albedo is a key variable in the study of global or regional earth system models. High-quality albedo products are helpful for the accurate analysis and prediction of the Earth’s environment and climate. This paper analyzes the similarities and differences in several global-scale albedo products. The conclusions are as follows: (1) Ignoring the downward radiation weight leads to a maximum deviation of ±0.2 in the mean albedo in space and time; (2) Most of the products have good consistency at the global scale, especially after 2000, the consistency in the middle latitudes is better than that in the low latitudes and high latitudes; (3) Although there are obvious inter-annual variations and zonal differences in global mean albedo data from 2000 to 2020, the overall trend is not significant. The complex spatio-temporal variation of albedo requires high-quality remote sensing products to characterize its details. However, existing datasets do not show good agreement in these details, and more efforts are needed in this area.

Evaluation of Albedo Schemes in WRF Coupled with Noah-MP on the Parlung No. 4 Glacier

Meteorological variables (e.g., air temperature (T2), radiation flux, and precipitation) determine the evolution of glacier mass and characteristics. Observations of these variables are not available with adequate spatial coverage and spatiotemporal resolution over the Tibetan Plateau. Albedo is the key factor of net radiation and is determined by the land cover and snow-related variables. This study focuses on evaluating the performance of the albedo parameterization scheme in WRF coupled with Noah-MP in terms of glacio-meteorological variables, by conducting experiments applying the standard surface albedo scheme with the default vegetation and corrected to ice cover and the modified glacial albedo scheme to the Parlung No. 4 Glacier in the 2016 ablation season. In situ glacio-meteorological element observations and MODIS-retrieved albedo are selected to assess the performance of the model. The key results are as follows. First, compared to the air temperature bias of 1.56 °C in WRF applying the standard surface albedo scheme and the default vegetation cover, realistic land-use categories considerably reduce the model warm bias on the glacier. The model using realistic land-use categories yields similar T2 diurnal patterns to the observations, with a mean bias of only −0.5 °C, no matter which glacial albedo scheme is implemented. Second, the default glacial albedo scheme gives a rather high albedo value of 0.68, causing an apparent underestimation of the net shortwave radiation and net radiation; the modified glacial albedo scheme gives a mean albedo value of 0.35, close to the in situ observations, helping to relieve underestimations of net shortwave radiation and net radiation. Compared with the MODIS albedo of the glacier, WRF applying the default glacial albedo scheme apparently overestimates the albedo with a mean error of 0.18, while WRF applying the modified glacial albedo scheme slightly underestimates the albedo with a mean error of only −0.08. Third, the mean net radiation flux (142 W m−2) and high ground heat flux (182 W m−2) values that were estimated by WRF applying the corrected land cover and the modified glacial albedo scheme result in the heating of the glacier surface and subsurface, causing ice melt and the liquid water content to increase more quickly and preferentially, equating to an estimated ice thickness decrease of 1 m by mid-June in the ablation region. Our study confirms the ability of the WRF model to reproduce glacio-meteorological variables as long as a reasonable glacial albedo scheme and the corrected land cover is applied and provides a theoretical reference for researchers that are committed to further improvement of the glacial albedo scheme.

Albedo impacts of current agricultural land use: Crop-specific albedo from MODIS data and inclusion in LCA of crop production

Agricultural land use and management practices affect the global climate due to greenhouse gas (GHG) fluxes and changes in land surface properties. Increased albedo has the potential to counteract the radiative forcing and warming effect of emitted GHGs. Thus considering albedo could be important to evaluate and improve agricultural systems in light of climate change, but the albedo of individual practices is usually not known. This study quantified the albedo of individual crops under regional conditions, and evaluated the importance of albedo change for the climate impact of current crop production using life cycle assessment (LCA). Seven major crops in southern Sweden were assessed relative to a land reference without cultivation, represented by semi-natural grassland. Crop-specific albedo data were obtained from a MODIS product (MCD43A1 v6), by combining its spatial response pattern with geodata on agricultural land use 2011–2020. Fluxes of GHGs were estimated using regional data and models, including production of inputs, field operations, and soil nitrogen and carbon balances. Ten-year mean albedo was 6–11% higher under the different crops than under the reference. Crop-specific albedo varied between years due to weather fluctuations, but differences between crops were largely consistent. Increased albedo countered the GHG impact from production of inputs and field operations by 17–47% measured in GWP100, and the total climate impact was warming. Using a time-dependent metric, all crops had a net cooling impact on global mean surface temperature on shorter timescales due to albedo (3–12 years under different crops), but a net warming impact on longer timescales due to GHG emissions. The methods and data presented in this study could support increasingly comprehensive assessments of agricultural systems. Further research is needed to integrate climatic effects of land use on different spatial and temporal scales, and direct and indirect consequences from a systems perspective.

Filling gaps of black-sky surface albedo of the Arctic sea ice using gradient boosting and brightness temperature data

Surface albedo is a necessary parameter for climate studies and modeling. There is a need for a full spatial coverage of albedo data, but clouds and high solar zenith angle cause missing values to the optical satellite products, especially around the polar areas. Therefore, our motivation is to develop gap filling models. For that purpose, we will apply monthly gradient boosting (GB) based models to the Arctic sea ice area of the 34 years long albedo time series of the Satellite Application Facility on Climate Monitoring (CM SAF) project. We demonstrate the ability of the GB models to accurately fill missing data using albedo monthly mean, brightness temperature, and sea ice concentration as model inputs. Monthly GB models produce the most unbiased, precise, and robust estimates when compared to alternative estimates presented, such as monthly mean albedo values or estimates from monthly linear regression (LR) models. The mean relative differences between GB based estimates and original pentad values vary from −20% to 20% with RMSE being 0.048, compared to relative differences varying from −20% to over 60% with RMSE varying from 0.054 to 0.074 between other estimates and original pentad values. Pixelwise mean differences and standard deviations (std) over the whole Arctic sea ice area show that GB based estimates are more accurate (mean differences from −0.02 to 0.02) and more precise (std from 0.02 to 0.08) than other estimates (mean differences varying between −0.05 to over 0.05, and std varying from around 0.03 to over 0.1). Also, albedo of the melting sea ice is predicted better by the GB model, with negligible mean differences, compared to the LR model. Based on these results, we show that GB method is a useful technique to fill missing data, and the brightness temperature and sea ice concentration are useful additional model input data sources.

Caatinga Albedo Preserved and Replaced by Pasture in Northeast Brazil

The caatinga is considered South America’s largest seasonally dry tropical forest (SDTF) and one of the most vulnerable endemic biomes in relation to climate change. The surface albedo in caatinga is relevant to understanding the role of this biome in the climate of the Northeast region of Brazil. Thus, a comparative analysis was conducted between the albedos of preserved and anthropized caatinga (pasture). Data were collected using CNR4-type net radiometers during the dry and rainy seasons. The mean albedo values were higher in the Pasture both in the dry and rainy season, with values of 0.181 and 0.177, respectively. In the caatinga, the mean albedo values were 0.137 in the dry season and 0.146 in the rainy season. The hourly average values for albedo, taken between 6:30 a.m. and 4 p.m., with intervals of 30 min, were also higher in the pasture. For convenience, this study uses local standard time (LST), which is 3 h behind from coordinated universal time (UTC). The greatest dispersions in the frequencies of the mean hourly albedo values occurred in the early morning and late afternoon. Some of the consequences of this study is the confirmation that there is an increase in albedo in caatinga replaced by pasture and this causes a reduction in the net radiation and also the finding that a region where there is adequate pasture management also enables albedo management and from solar radiation. And that further studies can indicate the impacts on temperature and precipitation, especially in warmer periods during the dry season.

Cross-Comparison of Global Surface Albedo Operational Products-MODIS, GLASS, and CGLS

Surface albedo, as an important parameter for land surface geo-biophysical and geo-biochemical processes, has been widely used in the research communities involved in surface energy balance, weather forecasting, atmospheric circulation, and land surface process models. In recent years, operational products using satellite-based surface albedo have, from time to time, been rapidly developed, contributing significantly to the estimation of energy balance at regional or global scales. The increasing number of research topics on dynamic monitoring at a decades-long scale requires a combination of albedo products generated from various sensors or programs, while the quantitative assessment of agreement or divergence among different surface albedo products still needs further understanding. In this paper, we investigated the consistency of three classical operational surface albedo products that have been frequently used by researchers globally via the official issued datasets-MODIS, GLASS (Global LAnd Surface Satellite), and CGLS (Copernicus Global Land Service). The cross-comparison was performed on all the identical dates available during 2000–2017 to represent four season-phases. We investigated the pixel-based validity of each product, consistency of global annual mean, spatial distribution and different temporal dynamics among the discussed products in white-sky (WSA) and black-sky (BSA) albedo at visible (VIS), near-infrared (NIR), and shortwave (SW) regimes. Further, varying features along with the change of seasons was also examined. In addition, the variation in accuracy of shortwave albedo magnitude was explored using ground measurements collected by the Baseline Surface Radiation Network (BSRN) and the Surface Radiation Budget Network (SUFRAD). Results show that: (1) All three products can provide valid long-term albedo for dominant land surface, while GLASS can provide additional estimation over sea surfaces, with the highest percentage of valid land surface pixels, at up to 93% in 24 October. The invalid pixels mainly existed in the 50°N–60°N latitude belt in December for GLASS, Central Africa in April and August for MODIS, and northern high latitudes for CGLS. (2) The global mean albedo of CGLS at the investigated bands has significantly higher values than those of MODIS and GLASS, with a relative difference of ~20% among the three products. The global mean albedo of MODIS and GLASS show a generally increasing trend from April to December, with an abrupt rise at NIR and SW of CGLS in June of 2014. Compared with SW and VIS bands, the linear temporal trend of the NIR global albedo mean in three products continues to increase, but the slope of CGLS is 10–100 times greater than that of the other two products. (3) The differences in albedo, which are higher in April, October, and December than in August, exhibit a small variation over the main global land surface regions, except for Central Eurasia, North Africa, and middle North America. The magnitude of global absolute difference among the three products usually varies within 0.02–0.06, but with the largest value occasionally exceeding 0.1. The relative difference is mainly within 10–20%, and can deviate more than 40% away from the baseline. In addition, CGLS has a greater opportunity to achieve the largest difference compared with MODIS and GLASS. (4) The comparison with ground measurements indicates that MODIS generally performs better than GLASS and CGLS at the sites discussed. This study demonstrates that apparent differences exist among the three investigated albedo products due to the ingested source data, algorithm, atmosphere correction etc., and also points at caution regarding data fusion when multiple albedo products were organized to serve the following applications.

A high-resolution record of coastal clouds and fog and their role in plant distributions over San Clemente Island, California

San Clemente Island (SCI), located in the Southern California Bight, is owned and operated by the U.S. Navy and is home to endemic species, including federally threatened or endangered plants and birds. The SCI ecosystem is influenced by the presence of warm season low-level clouds that shade, cool and, especially when in the form of fog, moisten the environment. We created a new cloud and fog satellite-derived albedo product for SCI at a higher resolution than previous datasets. The record spans 23 summers (1996–2018, May - Sep). The spatial resolution is ∼1 km and the temporal resolution is half hourly (nominally 0600 to 1800 PST). Using Geostationary Operational Environmental Satellite (GOES)-WEST visible band measurements, it was discovered that small (typically on the order of less than 5 km) geographical misalignment of the satellite images was common. The biological ramifications of such a shift could be significant. Thus, to provide a useful 1 km product for a narrow island such as SCI it was necessary to correct misalignments. Misalignment of albedo was easily apparent in clear sky images at the interface of land and water. This concept was used in the automated correction. The northwest coast of SCI is the cloudiest/foggiest area. June, on average, is the cloudiest month on SCI. The intra-day variability reaches ∼20% cloud albedo while interannual and monthly variability are ∼10%. To demonstrate the records’ utility in understanding ecological phenomena and patterns, we used the dataset to model plant distributions. We found monthly mean cloud albedo values, a proxy for cloud frequency and persistence, were among the most important environmental variables in understanding plant distributions. The vegetation models indicate locations with appropriate conditions, including clouds and fog during critical periods of the year, for particular vegetation types and thus, can inform restoration and management activities.

Urban thermal environment and surface energy balance in 3D high-rise compact urban models: Scaled outdoor experiments

This study investigates the diurnal characteristics of air-surface temperatures and surface energy balance (SEB) of outdoor scaled arrays under different sky conditions from October to December 2017 in Guangzhou. Key geometrical parameters of the arrays include aspect ratio H/W = 2.4 (building height H = 1.2 m, street width W = 0.5 m), building area density λp = 0.25, and frontal area density λf = 0.6. Two types of buildings are investigated: “hollow” model means hollow concrete buildings and “water” model filled with water.Direct solar radiation, wall height, and wall orientation are significant factors that affect the diurnal variations of air-wall surface temperatures. The wall temperature shows a common declining trend from the upper heights to the lower heights. The water model experiences a smaller mean daily temperature range (DTR) of about 10 °C than the hollow model (mean DTR = 15.5 °C) due to heat storage. Moreover, 50%~60% net radiation (Q*) are partitioned into heat storage (estimated by the element surface temperature method) for the water model, which is about two times for the hollow model between 10:00 to 16:00. For the hollow model, the sum of sensible and latent heat fluxes contributes to the majority fraction of Q*. On clear sky days, the diurnal variation of short-wave radiation shows a single peak, while more complicated variations in occasionally cloudy days. The mean albedo is mainly affected by solar altitude angle, sky conditions which ranged from 0.21 to 0.23 with H/W = 2.4 in current study. The present study may provide experimental data to validate numerical and theoretical models for urban climate studies.

Surface albedo spatial variability in North America: Gridded data vs. local measurements

Considering the current booming interest for the large-scale deployment of bifacial photovoltaic modules, the solar industry now requires accurate estimates of broadband surface albedo at high spatial resolution. In this context, the present study evaluates the adequacy and performance over North America of two Moderate Resolution Imaging Spectroradiometer (MODIS) white-sky albedo products (at 500-m and 1-km resolution) and the National Solar Radiation Database (NSRDB) product at 4-km resolution. Two variations of the 500-m MODIS product are also considered: black-sky albedo and all-sky albedo. Albedo observations from 36 radiometric stations during 2011–2015 are analyzed while considering the apparent homogeneity of the surface characteristics over the 4x4 km NSRDB pixel in which they are located. Even at sites where the albedo around the station has been found “homogeneous” in the literature, marked differences are found between the daily observations and the gridded estimates at any spatial resolution. Differences in seasonal behavior and between the three different albedo types also impact the accuracy of the albedo estimates, with overtones caused by local specificities and inhomogeneities. All this precludes the desirable evaluation of the local albedo at a specific site of relatively small size compared to its corresponding 4x4-km pixel if only the mean albedo over that pixel is known. Significant discrepancies are also found at snow-impacted sites, most importantly in the case of the NSRDB albedo estimates, which are typically much too high.