White-sky Albedo Research Articles

Evaluating the Performance of the Enhanced Ross-Li Models in Characterizing BRDF/Albedo/NBAR Characteristics for Various Land Cover Types in the POLDER Database

The latest versions of the Ross-Li model include kernels that represent isotropic reflection of the surface, describe backward reflection of soil and vegetation systems, characterize strong forward reflection of snow, and adequately consider the hotspot effect (i.e., RossThick-LiSparseReciprocalChen-Snow, RTLSRCS), theoretically able to effectively characterize BRDF/Albedo/NBAR features for various land surface types. However, a systematic evaluation of the RTLSRCS model is still lacking for various land cover types. In this paper, we conducted a thorough assessment of the RTLSRCS and RossThick-LiSparseReciprocalChen (RTLSRC) models in characterizing BRDF/Albedo/NBAR characteristics by using the global POLDER BRDF database. The primary highlights of this paper include the following: (1) Both models demonstrate high accuracy in characterizing the BRDF characteristics across 16 IGBP types. However, the accuracy of the RTLSRC model is notably reduced for land cover types with high reflectance and strong forward reflection characteristics, such as Snow and Ice (SI), Deciduous Needleleaf Forests (DNF), and Barren or Sparsely Vegetated (BSV). In contrast, the RTLSRCS model shows a significant improvement in accuracy for these land cover types. (2) These two models exhibit highly consistent albedo inversion across various land cover types (R2 > 0.9), particularly in black-sky and blue-sky albedo, except for SI. However, significant differences in white-sky albedo inversion persist between these two models for Evergreen Needleleaf Forests (ENF), Evergreen Broadleaf Forests (EBF), Urban Areas (UA), and SI (p < 0.05). (3) The NBAR values inverted by these two models are nearly identical across the other 15 land cover types. However, the consistency of NBAR results is relatively poor for SI. The RTLSRC model tends to overestimate compared to the RTLSRCS model, with a noticeable bias of approximately 0.024. This study holds significant importance for understanding different versions of Ross-Li models and improving the accuracy of satellite BRDF/Albedo/NBAR products.

Classifying seasonal patterns of clear-sky surface urban heat island worldwide and investigating impacts from surface energy variations

Variations and controls of surface urban heat island (SUHI) drawn great attention since its close association with environmental issues and heat risk. However, three issues remained neglect, namely, the mismatch and insignificant variations, seasonal patterns for SUHII DNC (day-and-night contrast) and impacts from surface energy variations. Therefore, this paper classifies seasonal patterns of SUHII based on ATCS (annual temperature cycle with seasonal adjustment) into five typical patterns, and further investigates impacts from surface energy variations. There are three major findings. (1) Approximately 70% of global cities are identified as the spring-summer and summer-autumn patterns at daytime, while global cities identified as the winter-spring and insignificant patterns account for 36% and 24%. The seasonal patterns of DNC are significantly affected by that of daytime. (2) The seasonal patterns of SUHII indicate opposite seasonal variations to ∆EVI (enhanced vegetation index) at daytime and ∆WSA (white sky albedo) at nighttime. (3) The cities identified as the spring-summer and summer-autumn patterns of SUHII are corresponded to the opposite patterns of latent heat flux at daytime, but similar patterns of net shortwave radiation at both day and night.

CLARA-A3: The third edition of the AVHRR-based CM SAF climate data record on clouds, radiation and surface albedo covering the period 1979 to 2023

Abstract. This paper presents the third edition of The Satellite Application Facility on Climate Monitoring's (CM SAF) cloud, albedo, and surface radiation dataset from advanced very-high-resolution radiometer (AVHRR) data, CLARA-A3. The content of earlier CLARA editions, namely cloud, surface albedo, and surface radiation products, has been extended with two additional surface albedo products (blue- and white-sky albedo), three additional surface radiation products (net shortwave and longwave radiation, and surface radiation budget), and two top of atmosphere radiation budget products (reflected solar flux and outgoing longwave radiation). The record length is extended to 42 years (1979–2020) by also incorporating results from the first version of the advanced very high resolution radiometer imager (AVHRR/1). A continuous extension of the climate data record (CDR) has also been implemented by processing an interim climate data record (ICDR) based on the same set of algorithms but with slightly changed ancillary input data. All products are briefly described together with validation results and intercomparisons with currently existing similar CDRs. The extension of the product portfolio and the temporal coverage of the data record, together with product improvements, is expected to enlarge the potential of using CLARA-A3 for climate change studies and, in particular, studies of potential feedback effects between clouds, surface albedo, and radiation. The CLARA-A3 data record is hosted by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) CM SAF and is freely available at https://doi.org/10.5676/EUM_SAF_CM/CLARA_AVHRR/V003 (Karlsson et al., 2023b).

Upgrade of LSA-SAF Meteosat Second Generation daily surface albedo (MDAL) retrieval algorithm incorporating aerosol correction and other improvements

Abstract. MDAL is the operational Meteosat Second Generation (MSG)-derived daily surface albedo product that has been generated and disseminated in near real time by EUMETSAT Satellite Application Facility for Land Surface Analysis (LSA-SAF) since 2005. We propose and evaluate an update to the MDAL retrieval algorithm which introduces the accounting for aerosol effects as well as other scientific developments: pre-processing recalibration of radiances acquired by the SEVIRI instrument aboard MSG and improved coefficients for atmospheric correction as well as for albedo conversion from narrow- to broadband. We compare the performance of MDAL broadband albedos pre- and post-upgrade with respect to three types of reference data: the EPS Ten-Day Albedo product ETAL is used as the primary reference, while albedo derived from in situ flux measurements acquired by ground stations and MODIS MCD43D albedo data are used to complete the validation. For the comparison to ETAL – conducted over the whole coverage area of SEVIRI – we see a reduction in average white-sky albedo mean bias error (MBE) from −0.02 to negligible levels (<0.001) and a reduction in average mean absolute error (MAE) from 0.034 to 0.026 (−24 %). Improvements can be seen for black-sky albedo as well, albeit less pronounced (14 % reduction in MAE). Further analysis distinguishing individual seasons, regions and land covers show that performance changes have spatial and temporal dependence: for white-sky albedo we see improvements over almost all regions and seasons relative to ETAL, except for Eurasia in winter; resolved by land cover we see a similar effect with improvements for all types for all seasons except winter, where some types exhibit slightly worse results (crop-, grass- and shrublands). For black-sky albedo we similarly see improvements for all seasons when averaged over the full data set, although sub-regions exhibit clear seasonal dependence: the performance of the upgraded MDAL version is generally diminished in local winter but better in local summer. The comparison with in situ observations is less conclusive due to the well-known problem of the spatial representativeness of near-ground observations with respect to satellite pixel footprint sizes. Comparison with MODIS at the same locations shows mixed results in terms of change in performance following the proposed upgrade but proves the good quality of the MDAL products in general. Based on the evidence presented in this study, we consider the updated algorithm version to be able to deliver a valuable improvement of the operational MDAL product. This improvement is two-fold: primarily, there is the refinement of the albedo values themselves; secondarily, the increased alignment with the ETAL product is beneficial for those who wish to exploit synergies between EUMETSAT's geostationary and polar satellites to generate data sets based on the LSA-SAF albedo products from the two different missions.

Calibration of ground surface albedo models

The emergence of bifacial photovoltaics as a serious option for large-scale power generation makes the accuracy of the in-situ estimation of ground surface albedo increasingly critical. Recent studies have evaluated the performance of different models but an investigation of how these models should be calibrated is missing. This paper proposes geographically generalised parametrisations for time-variant albedo models of vegetated and desert surfaces based on a worldwide database and reports their performance compared to site-specific, unbiased parametrisations. These geographically generalised formulations can be used as an alternative for lengthy calibration campaigns as their only parameters can be easily measured. The paper also presents a simple method for deriving white-sky albedo without the need for diffuse irradiance data. The method is founded both theoretically and empirically. If on-site measurements can be collected to calibrate a model, the duration of the campaign is usually a few weeks at the maximum. This paper first shows evidence of the strong impact of the timing on calibration performance and accordingly gives practical guidelines on the most suitable measurement seasons and weather conditions. In general, early-summer months appear to be the most appropriate time for calibrating most models. Atmospheric turbidity during the campaign period, however, should be either minimised or maximised depending on the site and the model. Finally, in case no flexibility exists in timing the calibration, simple models with few parameters should be deployed. Geometric mean shows the most robust performance at most sites.

Does urban climate follow urban form? Analysing intraurban LST trajectories versus urban form trends in 3 cities with different background climates

The current climate change trend urges the application of efficient spatial planning to mitigate the effects of urbanization on local urban warming. Nevertheless, how urban temperatures respond to urban form changes inside cities is still insufficiently understood. In this paper, we explored the relationship between urban form and diurnal space-time land surface temperature (LST) trends (2003–2019) in Beijing (continental climate), Cairo (arid) and Santiago (temperate). We analysed changes in land cover, white sky albedo (WSA), night-time lights (NL) and the enhanced vegetation index (EVI) inside areas representing clustered thermal performance (steady cold and hot spots and warming cold and hot spots). The structure of local climate zones (LCZs) was assessed for each LST trend. To test the relevance of other urban form dimensions, we analysed the hierarchical influence of the employed 2D metrics (i.e., built-up cover, WSA, NL and EVI) and additional 3D indicators (i.e., height and volume) on LST, applying machine learning classification and regression trees (CARTs) to Beijing's data. Despite diverse patterns of urban form change, cities in our sample present common LST trends, with thermal differences as a consequence of local climate. LCZs are composed of highly heterogeneous built-up areas inside LST trend categories. In the case of Beijing, LST is hierarchically driven by footprint, WSA and EVI. Moreover, by adding height and volume, urban form differences between LST trend classes that are not evident with 2D data were found. Our findings suggest that a compact green urban tissue is necessary to cope with the current trends of urban warming, taking into account city-specific measures based on the local background climate.

Local climate impacts from ongoing restoration of a peatland

AbstractWe hypothesize that peatlands represent a cool humid island in their landscape context and that this cool humid island effect could be brought about by successful peatland restoration. This study used 20 years of Earth observation data for land surface temperature (day‐ and night‐ time LST), albedo (near infra‐red white sky albedo) and vegetation indices measured for 42 one km2 grid squares across two peatlands and their surrounding arable fields. The peatlands have undergone restoration (re‐vegetation and raising of water tables) since 2004. The results show that over the restored peatlands: Day time temperatures over the peatlands cooled relative to the surrounding arable‐land by up to 1.1 K (°C), but there was no significant change in night time temperatures. Over the peatlands the average amplitude of the diurnal temperature cycle decreased by up to 2.4 K (°C) over the period of the restoration. Comparison to vegetation indices and albedo shows the cooling effect of increasing albedo was smaller than warming effect of changes aerodynamic resistance brought about by development of shrubby vegetation. The presence of an overall cooling effect, despite a warming effect due to vegetation development, means that a rising water table led to a lowering of the Bowen ratio. Peatlands revegetated to, or dominated by, moss carpets rather than shrubby vegetation will maximise the potential cooling effect, whereas shrub development across peatlands without a rise in water table would lead to warming.

Air Contaminants and Atmospheric Black Carbon Association with White Sky Albedo at Hindukush Karakorum and Himalaya Glaciers

Environmental contaminants are becoming a growing issue due to their effects on the cryosphere and their impact on the ecosystem. Mountain glaciers are receding in the HKH region and are anticipated to diminish further as black carbon (BC) concentrations rise along with other pollutants in the air, increasing global warming. Air contaminants and BC concentrations were estimated (June 2017–May 2018). An inventory of different pollutants at three glaciers in Karakoram, Hindukush, and the Himalayas has been recorded with Aeroqual 500 and TSI DRX 8533, which are as follows: ozone (28.14 ± 3.58 µg/m3), carbon dioxide (208.58 ± 31.40 µg/m3), sulfur dioxide (1.73 ± 0.33 µg/m3), nitrogen dioxide (2.84 ± 0.37 µg/m3), PM2.5 (15.90 ± 3.32 µg/m3), PM10 (28.05 ± 2.88 µg/m3), total suspended particles (76.05 ± 10.19 µg/m3), BC in river water (88.74 ± 19.16 µg/m3), glaciers (17.66 ± 0.82 µg/m3), snow/rain (57.43 ± 19.66 ng/g), and air (2.80 ± 1.20 µg/m3). BC was estimated by using DRI Model 2015, Multi-Wavelength Thermal/Optical Carbon Analyzer, in conjunction with satellite-based white-sky albedo (WSA). The average BC concentrations in the Karakoram, Himalaya, and Hindukush were 2.35 ± 0.94, 4.38 ± 1.35, and 3.32 ± 1.09 (µg/m3), whereas WSA was 0.053 ± 0.024, 0.045 ± 0.015, and 0.045 ± 0.019 (µg/m3), respectively. Regression analysis revealed the inverse relationship between WSA and BC. The resulting curves provide a better understanding of the non-empirical link between BC and WSA. Increased BC will inherit ecological consequences for the region, ultimately resulting in biodiversity loss.

Estimating Surface BRDF/Albedo Over Rugged Terrain Using an Extended Multisensor Combined BRDF Inversion (EMCBI) Model

Land surface albedo is a crucial variable of earth energy budget and global climate change. Rugged terrain significantly impacts surface bidirectional reflectance distribution function (BRDF) and the subsequent albedo retrieval using satellite remote sensing. Existing studies of estimating surface BRDF/albedo from satellite observations are limited to neglecting topographic impacts, resulting in large uncertainty in satellite albedo product, especially for low spatial resolution satellite sensors that are primarily regulated by subpixel-scale topographic effects. To fill this knowledge gap, we proposed an extended multisensor combined BRDF inversion (EMCBI) model to characterize subpixel-scale topographic effects, and applied this model to estimate BRDF/albedo from the Himawari-8 Advanced Himawari Imager (AHI) and Terra/Aqua moderate resolution imaging spectroradiometer (MODIS) data and finally validated the satellite-derived albedo with ground measurements of two stations located in Tibet plateau. Our results show that: 1) EMCBI can generate a daily BRDF/albedo dataset with more than 90% spatial coverage and 2) EMCBI-derived albedo agrees well with the referenced albedo corrected from ground measurement, with a root-mean-square-error (RMSE) of 0.0537 and 0.0608 for black-sky albedo (BSA) and white-sky albedo (WSA), and a mean absolute percentage error (MAPE) of 21.93% and 25.13% for BSA and WSA, respectively. These results demonstrate EMCBI has great potential for mapping large-scale high temporal resolution BRDF/albedo product over rugged terrain.

Errata Erratum to “Validation of the MCD43A3 Collection 6 and GLASS V04 Snow-Free Albedo Products Over Rugged Terrain”

A comprehensive assessment of satellite-derived albedo products is undeniably essential for better use consideration and the further refinement of the retrieval algorithm. Although satellite albedo products have been extensively validated over spatially homogeneous areas, it remains a challenge to validate them over rugged terrain. Consequently, the accuracy of satellite albedo products over rugged terrain is still unknown. This study for the first time systematically evaluated two widely used satellite albedo products (i.e., MCD43A3 C6 and Global Land Surface Satellite (GLASS) V04 albedo) over mountainous areas with a mountain radiation transfer (MRT) coupled multiscale validation strategy. Fine-scale albedo was first generated with a root-mean-square error (RMSE) smaller than 0.0317. Then, they were upscaled to the coarse pixel and as the reference data for validation. The validation results indicated that the accuracy of the two products tends to decrease with the increase of means slopes. The RMSE and relative RMSE (RMSE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> ) of full retrieval MCD43A3 C6 black-sky albedo (BSA) and white-sky albedo (WSA) over abrupt slopes (mean slope >10°) increase to 0.0432 and 31.87% and to 0.0436 and 32.21%, respectively. The RMSE and RMSE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> of high-quality GLASS V04 were 0.0452 and 33.71% of BSA and 0.0458 and 33.92% of WSA, respectively, over abrupt slopes. In particular, if the backup retrievals were included over the abrupt slopes, the RMSE and RMSE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> of MCD43A3 C6 can reach 0.0600 and 36.92% for BSA and 0.0613 and 37.67% for WSA, respectively, and those of GLASS V04 can reach 0.0567 and 36.28% for BSA and 0.0540 and 35.72%, respectively.

Validation of the MCD43A3 Collection 6 and GLASS V04 Snow-Free Albedo Products Over Rugged Terrain

A comprehensive assessment of satellite-derived albedo products is undeniably essential for better use consideration and the further refinement of the retrieval algorithm. Although satellite albedo products have been extensively validated over spatially homogeneous areas, it remains a challenge to validate them over rugged terrain. Consequently, the accuracy of satellite albedo products over rugged terrain is still unknown. This study for the first time systematically evaluated two widely used satellite albedo products (i.e., MCD43A3 V006 and GLASS V04 albedo) over mountainous areas with a Mountain Radiation Transfer (MRT) coupled multi-scale validation strategy. Fine-scale albedo was first generated with a root mean square error (RMSE) smaller than 0.0317. Then they were upscaled to the coarse pixel and as the reference data for validation. The validation results indicated that the accuracy of the two products tends to decrease with the increase of means slopes. The RMSE and relative RMSE (RMSE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> ) of full retrieval MCD43A3 C6 black-sky albedo (BSA) and white-sky albedo (WSA) over abrupt slopes (mean slope >10°) increase to 0.0432 and 31.87% and to 0.0436 and 32.21%, respectively. The RMSE and RMSE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> of high quality GLASS V04 were 0.0452 and 33.71% of BSA and 0.0458 and 33.92 % of WSA respectively over abrupt slopes. Particularly, if the backup retrievals were included over the abrupt slopes, the RMSE and RMSER of MCD43A3 C6 can reach to 0.0600 and 36.92% for BSA and 0.0613 and 37.67% for WSA, and those of GLASS V04 can reach to 0.0567 and 36.28% for BSA and 0.0540 and 35.72% respectively.

Evaluation of BRDF Information Retrieved from Time-Series Multiangle Data of the Himawari-8 AHI

Recently, much attention has been given to using geostationary Earth orbit (GEO) meteorological satellite data for retrieving land surface parameters due to their high observation frequencies. However, their bidirectional reflectance distribution function (BRDF) information content with a single viewing angle has not been sufficiently investigated, which lays a foundation for subsequent quantitative estimation. In this study, we aim to comprehensively evaluate BRDF information from time-series observations from the Advanced Himawari Imager (AHI) onboard the GEO satellite Himawari-8. First, ~6.2 km monthly multiangle surface reflectances from POLDER onboard a low-Earth-orbiting (LEO) satellite with good angle distributions over various land types during 2008 were used as reference data, and corresponding 0.05° high-quality MODIS (i.e., onboard LEO satellites) and AHI datasets during four months in 2020 were obtained using cloud and aerosol property products. Then, indicators of angle distribution, BRDF change, and albedos were retrieved by the kernel-driven Ross-Li BRDF model from the three datasets, which were used for comparisons over different time spans. Generally, the quality of sun-viewing geometries varies dramatically for accumulated AHI observations according to the weight-of-determination, and wide-ranging anisotropic flat indices are obtained. The root-mean-square-errors of white sky albedos between AHI and MODIS half-month data are 0.018 and 0.033 in the red and near-infrared bands, respectively, achieving smaller values of 0.004 and 0.007 between the half-month and daily AHI data, respectively, due to small variances in sun-viewing geometries. The generally wide AHI BRDF variances and good consistency in albedo with MODIS show their potential for retrieving anisotropy information and albedo, while angle accumulation quality of AHI time-series observations must be considered.

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.

Surface Urban Heat Island Assessment of a Cold Desert City: A Case Study over the Isfahan Metropolitan Area of Iran

This study investigates the diurnal, seasonal, monthly and temporal variation of land surface temperature (LST) and surface urban heat island intensity (SUHII) over the Isfahan metropolitan area, Iran, during 2003–2019 using MODIS data. It also examines the driving factors of SUHII like cropland, built-up areas (BI), the urban–rural difference in enhanced vegetation index (ΔEVI), evapotranspiration (ΔET), and white sky albedo (ΔWSA). The results reveal the presence of urban cool islands during the daytime and urban heat islands at night. The maximum SUHII was observed at 22:30 p.m., while the minimum was at 10:30 a.m. The summer months (June to September) show higher SUHII compared to the winter months (February to May). The daytime SUHII demonstrates a robust positive correlation with cropland and ΔWSA, and a negative correlation with ΔET, ΔEVI, and BI. The nighttime SUHII displays a negative correlation with ΔET and ΔEVI.

Quantifying diurnal and seasonal variation of surface urban heat island intensity and its associated determinants across different climatic zones over Indian cities

ABSTRACT Surface urban heat island (SUHI) is a major anthropogenic alteration of Earth’s surface and can influence the local thermal environment by altering the surface energy flux balances. Researchers have paid much attention to SUHI studies in the last decades; still, its geospatial variability over a larger area is poorly understood. Detailed research is required to understand the mechanism and dynamics of SUHI along with its different driving variables. Hence in this study, we quantified the diurnal, seasonal, and interannual variation of SUHI intensity (SUHII) over 150 major Indian cities situated over different climatic zones using MODIS data from 2003 to 2018. The results reveal urban cool islands occurrence over the hot desert, hot steppe, and tropical monsoon climatic zone during daytime in both summer (−0.25 to −0.17°C) and winter (−0.33 to 0.17°C) season. In contrast, nighttime SUHII shows clear evidence of positive urban heat island irrespective of climatic region and seasonal variation of 0.48–1°C in summer and 0.46–1.32°C in winter is seen. The Mann–Kendall and Sen’s slope estimator tests are used to detect the trend of the SUHII during the study period, which suggests a higher percentage of cities showing an increasing trend of SUHII for urban heat islands than the cities of the urban cool island. Pearson’s correlation and stepwise multiple linear regression model determine the possible SUHII controlling variable over different climatic zones. During the daytime, the SUHII’s distribution is controlled by vegetation, evapotranspiration, and thermal inertia in the summer/winter season. Whereas, it is linked tightly to built-up intensity, white sky albedo, and thermal inertia in both seasons during nighttime. Overall, we found that the stepwise multiple linear regression model can explain the SUHII variance more in the daytime (>0.8) than in nighttime (>0.7, except for tropical cities) and more in understanding the SUHII behaviors for cool cities as compared to hot cities. Moreover, this study also quantifies the significant control of thermal inertia and soil moisture in understating urban heat and cool island behavior over different climatic zones.

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.

Bi-hemispherical Canopy Reflectance Model with Surface Heterogeneity Effects for the Estimation of LAI and fAPAR from MODIS White-Sky Spectral Albedo Data

Bi-hemispherical reflectance (BHR), in the land surface research community also known as “white-sky albedo”, is independent of the directions of incidence and viewing. For vegetation canopies, it is also nearly independent of the leaf angle distribution, and therefore it can be considered an optical quantity that is only dependent on material properties. For the combination leaf canopy and soil background, the most influential material properties are the canopy LAI (leaf area index), optical properties of the leaves, and soil brightness. When the leaf and soil optical properties are known or assumed, one may estimate the canopy LAI from its white-sky spectral albedo. This is also because a simple two-stream radiative transfer (RT) model is available for the BHR of the leaf canopy and soil combination. In this contribution, crown clumping and lateral linear mixing effects are incorporated in this model. A new procedure to estimate soil brightness is introduced here, even under a moderate layer of green vegetation. The procedure uses the red and NIR spectral bands. A MODIS white-sky albedo product at a spatial resolution of 0.05° is used as a sample input to derive global maps of LAI, soil brightness, and fAPAR at the local moments of minimum and maximum NDVI over a 20-year period. These maps show a high degree of spatial coherence and demonstrate the possible utility of products that can be generated with little effort by using a direct LUT technique.

Assessment of the EUMETSAT Multi Decadal Land Surface Albedo Data Record from Meteosat Observations

Surface albedo, defined as the ratio of the surface-reflected irradiance to the incident irradiance, is one of the parameters driving the Earth energy budget and it is for this reason an essential variable in climate studies. Instruments on geostationary satellites provide suitable observations allowing long-term monitoring of surface albedo from space. In 2012, EUMETSAT published Release 1 of the Meteosat Surface Albedo (MSA) data record. The main limitation effecting the quality of this release was non-removed clouds by the incorporated cloud screening procedure that caused too high albedo values, in particular for regions with permanent cloud coverage. For the generation of Release 2, the MSA algorithm has been replaced with the Geostationary Surface Albedo (GSA) one, able to process imagery from any geostationary imager. The GSA algorithm exploits a new, improved, cloud mask allowing better cloud screening, and thus fixing the major limitation of Release 1. Furthermore, the data record has an extended temporal and spatial coverage compared to the previous release. Both Black-Sky Albedo (BSA) and White-Sky Albedo (WSA) are estimated, together with their associated uncertainties. A direct comparison between Release 1 and Release 2 clearly shows that the quality of the retrieval improved significantly with the new cloud mask. For Release 2 the decadal trend is less than 1% over stable desert sites. The validation against Moderate Resolution Imaging Spectroradiometer (MODIS) and the Southern African Regional Science Initiative (SAFARI) surface albedo shows a good agreement for bright desert sites and a slightly worse agreement for urban and rain forest locations. In conclusion, compared with MSA Release 1, GSA Release 2 provides the users with a significantly more longer time range, reliable and robust surface albedo data record.

A Spatio-Temporal Assessment and Prediction of Surface Urban Heat Island Intensity Using Multiple Linear Regression Techniques Over Ahmedabad City, Gujarat

The present study intends to understand the variability in land surface temperature and urban heat island over Ahmedabad city, Gujarat, from 2003 to 2018 using MODIS thermal data. The spatio-temporal variability of land surface temperature dynamics is understood by pixel to pixel linear regression analysis along with Mann–Kendall and Sen's slope estimator tests. A Gaussian fitting technique is employed to estimate the surface urban heat island (SUHI) signature with respect to the surrounding rural area. An overall increase in the surface urban heat island magnitude is profoundly visible during the winter season. The spatial extent of SUHI shows a uniform distribution of urban heat inside the city and its accumulation within a high dense central urban area in both summer and winter seasons. A multiple linear regression method is used to predict the SUHI magnitude in the next 16 years, i.e. in 2034, based on enhanced vegetation index, white sky albedo, and evapotranspiration as predicting variables considering two different scenarios presuming the present rate of change of predicting variables as first scenario and a double changing rate as compared to present rate in the second scenario.

A novel way to calculate shortwave black carbon direct radiative effect

Black carbon (BC) aerosol has a strong radiative forcing effect and significantly affects human beings and the environment. Therefore, it is important to quantitatively calculate its direct radiative effect (BC DRE) at the surface (SFC) and the top of the atmosphere (TOA). Current studies mainly use empirical formula methods or broadband methods to calculate BC DRE. However, these two methods do not consider the differences of sky diffuse light ratios in different wavelength bands. To overcome this problem, a new scheme named the multiband synthetic method is proposed to calculate blue sky albedo at MODIS narrow bands, and then, the blue sky albedo at the whole shortwave band is synthesized with these separate narrowband blue sky albedos. Based on BC concentration measured in Xuzhou over two years (from May 2014 to July 2016), aerosol optical depth (AOD) and microphysical parameters provided by AERONET, and the black sky albedo (BSA) and white sky albedo (WSA) provided by Google Earth Engine (GEE) products, shortwave BC DRE was calculated numerically with the use of the 6S radiative transfer model. The range of BC DRE computed by the multiband synthetic method at the TOA and SFC are 0.84 ± 0.08 to 3.27 ± 1.01W/m2 and −14.57 ± 4.53 to −4.31 ± 0.36W/m2. The shortwave BC DRE calculated by the multiband synthetic method was higher than that calculated with the broadband method and empirical formula method by 0.11% to 0.36% (at the SFC), 0.14% to 1.4% (at the SFC) and 3.4% to 10.1% (at the TOA), 5.5% to 15.8% (at the TOA), respectively. The BC DREs calculated by these three methods have small differences at the SFC. However, the difference was large at the TOA. The results of this study suggest that it is important to consider the differences between different narrow bands when calculating the broadband shortwave blue sky albedo.