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 October 24. 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.

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Validation of Clear-Sky Global LAnd Surface Satellite (GLASS) Longwave Radiation Product

10.5194/egusphere-egu2020-2036 ◽

2020 ◽

Author(s):

Qi Zeng ◽

Jie Cheng ◽

Feng Yang

Keyword(s):

Land Surface ◽

Water Cycle ◽

Radiant Energy ◽

Remote Sensing Data ◽

Longwave Radiation ◽

Energy System ◽

Surface Radiation ◽

Radiation Budget ◽

Clear Sky ◽

Global Land

Surface longwave (LW) radiation plays an important rolein global climatic change, which is consist of surface longwave upward radiation (LWUP), surface longwave downward radiation (LWDN) and surface longwave net radiation (LWNR). Numerous studies have been carried out to estimate LWUP or LWDN from remote sensing data, and several satellite LW radiation products have been released, such as the International Satellite Cloud Climatology Project&#8208;Flux Data (ISCCP&#8208;FD), the Global Energy and Water cycle Experiment&#8208;Surface Radiation Budget (GEWEX&#8208;SRB) and the Clouds and the Earth&#8217;s Radiant Energy System&#8208;Gridded Radiative Fluxes and Clouds (CERES&#8208;FSW). But these products share the common features of coarse spatial resolutions (100-280 km) and lower validation accuracy.Under such circumstance, we developed the methods of estimating long-term high spatial resolution all sky&#160; instantaneous LW radiation, and produced the corresponding products from MODIS data from 2000 through 2018 (Terra and Aqua), named as Global LAnd Surface Satellite (GLASS) Longwave Radiation product, which can be free freely downloaded from the website (http://glass.umd.edu/Download.html).In this article, ground measurements collected from 141 sites in six independent networks (AmerciFlux, AsiaFlux, BSRN, CEOP, HiWATER-MUSOEXE and TIPEX-III) are used to evaluate the clear-sky GLASS LW radiation products at global scale. The bias and RMSE is -4.33 W/m2 and 18.15 W/m2 for LWUP, -3.77 W/m2 and 26.94 W/m2 for LWDN, and 0.70 W/m2 and 26.70 W/m2 for LWNR, respectively. Compared with validation results of the above mentioned three LW radiation products, the overall accuracy of GLASS LW radiation product is much better. We will continue to improve the retrieval algorithms and update the products accordingly.

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Evaluation of the Surface Radiation Budget in the Atmospheric Component of the Hadley Centre Global Environmental Model (HadGEM1)

Journal of Climate ◽

10.1175/2008jcli2097.1 ◽

2008 ◽

Vol 21 (18) ◽

pp. 4723-4748 ◽

Cited By ~ 34

Author(s):

A. Bodas-Salcedo ◽

M. A. Ringer ◽

A. Jones

Keyword(s):

Land Surface ◽

Surface Albedo ◽

Longwave Radiation ◽

Surface Radiation ◽

Radiation Budget ◽

Surface Radiation Budget ◽

Global Environmental ◽

Downward Longwave Radiation ◽

Global Dimming ◽

Hadley Centre

Abstract The partitioning of the earth radiation budget (ERB) between its atmosphere and surface components is of crucial interest in climate studies as it has a significant role in the oceanic and atmospheric general circulation. An analysis of the present-day climate simulation of the surface radiation budget in the atmospheric component of the new Hadley Centre Global Environmental Model version 1 (HadGEM1) is presented, and the simulations are assessed by comparing the results with fluxes derived from satellite data from the International Satellite Cloud Climatology Project (ISCCP) and ground measurements from the Baseline Surface Radiation Network (BSRN). Comparisons against radiative fluxes from satellite and ground observations show that the model tends to overestimate the surface incoming solar radiation (Ss,d). The model simulates Ss,d very well over the polar regions. Consistency in the comparisons against BSRN and ISCCP-FD suggests that the ISCCP-FD database is a good test for the performance of the surface downwelling solar radiation in climate model simulations. Overall, the simulation of downward longwave radiation is closer to observations than its shortwave counterpart. The model underestimates the downward longwave radiation with respect to BSRN measurements by 6.0 W m−2. Comparisons of land surface albedo from the model and estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) show that HadGEM1 overestimates the land surface albedo over deserts and over midlatitude landmasses in the Northern Hemisphere in January. Analysis of the seasonal cycle of the land surface albedo in different regions shows that the amplitude and phase of the seasonal cycle are not well represented in the model, although a more extensive validation needs to be carried out. Two decades of coupled model simulations of the twentieth-century climate are used to look into the model’s simulation of global dimming/brightening. The model results are in line with the conclusions of the studies that suggest that global dimming is far from being a uniform phenomenon across the globe.

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Dependence of Land Surface Albedo on Solar Zenith Angle: Observations and Model Parameterization

Journal of Applied Meteorology and Climatology ◽

10.1175/2008jamc1843.1 ◽

2008 ◽

Vol 47 (11) ◽

pp. 2963-2982 ◽

Cited By ~ 46

Author(s):

Fanglin Yang ◽

Kenneth Mitchell ◽

Yu-Tai Hou ◽

Yongjiu Dai ◽

Xubin Zeng ◽

...

Keyword(s):

Great Plains ◽

Zenith Angle ◽

Land Surface ◽

Solar Zenith Angle ◽

Surface Albedo ◽

Geographical Location ◽

Department Of Energy ◽

Surface Radiation ◽

Radiation Budget ◽

Direct Beam

Abstract This study examines the dependence of surface albedo on solar zenith angle (SZA) over snow-free land surfaces using the intensive observations of surface shortwave fluxes made by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program and the National Oceanic and Atmospheric Administration Surface Radiation Budget Network (SURFRAD) in 1997–2005. Results are used to evaluate the National Centers for Environmental Prediction (NCEP) Global Forecast Systems (GFS) parameterization and several new parameterizations derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) products. The influence of clouds on surface albedo and the albedo difference between morning and afternoon observations are also investigated. A new approach is taken to partition the observed upward flux so that the direct-beam and diffuse albedos can be separately computed. The study focused first on the ARM Southern Great Plains Central Facility site. It is found that the diffuse albedo prescribed in the NCEP GFS matched closely with the observations. The direct-beam albedo parameterized in the GFS is largely underestimated at all SZAs. The parameterizations derived from the MODIS product underestimated the direct-beam albedo at large SZAs and slightly overestimated it at small SZAs. Similar results are obtained from the analyses of observations at other stations. It is also found that the morning and afternoon dependencies of direct-beam albedo on SZA differ among the stations. Attempts are made to improve numerical model algorithms that parameterize the direct-beam albedo as a product of the direct-beam albedo at SZA = 60° (or the diffuse albedo), which varies with surface type or geographical location and/or season, and a function that depends only on SZA. A method is presented for computing the direct-beam albedos over these snow-free land points without referring to a particular land-cover classification scheme, which often differs from model to model.

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Estimation of the earth's albedo over some selected area the Republic of Chad

International Journal of Physical Research ◽

10.14419/ijpr.v6i2.15846 ◽

2018 ◽

Vol 6 (2) ◽

pp. 64

Author(s):

Zakaria Marouf BARKA ◽

Théophile Lealea ◽

Rene Tchinda

Keyword(s):

Land Surface ◽

Surface Albedo ◽

Ground Surface ◽

Absolute Error ◽

Surface Radiation ◽

Radiation Budget ◽

Percentage Error ◽

Surface Radiation Budget ◽

Recorded Data ◽

The Republic

Surface albedo is one parameter of the climate variables. It influences the surface radiation budget for a given site. The availability of surface albedo data at both temporally and spatially levels are needed. In the lack of ground recorded values of albedo, we have to estimate surface albedo from the climatic variables. The model generated in this study enables the continuous observation of land surface albedo through relative model established from the multivariate regression method. From satellite recorded data, we estimate the ground surface albedo for some selected sites. The result were satisfactory with the root mean square error (RMSE) is 0.035. The Mean Absolute Error (MAE) was computed and indicated to be as low as 0.027 and mean absolute percentage error (MAPE) is 7.58.

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Surface Albedo Assimilation and Its Impact on Surface Radiation Budget in Beijing

Advances in Meteorology ◽

10.1155/2020/8312451 ◽

2020 ◽

Vol 2020 ◽

pp. 1-14

Author(s):

Chunlei Meng

Keyword(s):

Solar Radiation ◽

Land Surface ◽

Surface Albedo ◽

Near Infrared ◽

Surface Radiation ◽

Radiation Budget ◽

Net Radiation ◽

Annual Average ◽

Data Set ◽

Surface Radiation Budget

Surface albedo is a crucial parameter in land surface radiation budget. As bias exists between the model simulated and observed surface albedo, data assimilation is an important method to improve the simulation results. Moreover, surface albedo is associated with the wavelength of the sunlight. So, solar radiation partitioning is important to parameterize the surface albedo. In this paper, the moderate resolution imaging spectroradiometer- (MODIS-) retrieved direct visible, direct near-infrared, diffuse visible, and diffuse near-infrared surface albedos were assimilated into the integrated urban land model (IUM). The solar radiation partitioning method was introduced to parameterize the surface albedo. Based on the albedo data from MODIS and the solar radiation partitioning method, the surface albedo data set for the Beijing municipal area was generated. Based on the surface albedo data set and the IUM, the impacts of the surface albedo on the surface radiation budget were discussed quantitatively. Surface albedo is inversely proportional to the net radiation. For urban areas, after assimilation, the annual average net radiation decreases about 5.6%. For cropland, grassland, and forest areas, after assimilation, the annual average net radiations increase about 20.2%, 24.3%, and 18.7%, respectively.

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Estimation of Long-Term Surface Downward Longwave Radiation over the Global Land from 2000 to 2018

Remote Sensing ◽

10.3390/rs13091848 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1848

Author(s):

Chunjie Feng ◽

Xiaotong Zhang ◽

Yu Wei ◽

Weiyu Zhang ◽

Ning Hou ◽

...

Keyword(s):

Water Vapor ◽

Spatial Resolution ◽

Land Surface ◽

Longwave Radiation ◽

Surface Radiation ◽

Radiation Budget ◽

Mean Bias Error ◽

Downward Longwave Radiation ◽

Global Land

It is of great importance for climate change studies to construct a worldwide, long-term surface downward longwave radiation (Ld, 4–100 μm) dataset. Although a number of global Ld datasets are available, their low accuracies and coarse spatial resolutions limit their applications. This study generated a daily Ld dataset with a 5-km spatial resolution over the global land surface from 2000 to 2018 using atmospheric parameters, which include 2-m air temperature (Ta), relative humidity (RH) at 1000 hPa, total column water vapor (TCWV), surface downward shortwave radiation (Sd), and elevation, based on the gradient boosting regression tree (GBRT) method. The generated Ld dataset was evaluated using ground measurements collected from AmeriFlux, AsiaFlux, baseline surface radiation network (BSRN), surface radiation budget network (SURFRAD), and FLUXNET networks. The validation results showed that the root mean square error (RMSE), mean bias error (MBE), and correlation coefficient (R) values of the generated daily Ld dataset were 17.78 W m−2, 0.99 W m−2, and 0.96 (p < 0.01). Comparisons with other global land surface radiation products indicated that the generated Ld dataset performed better than the clouds and earth’s radiant energy system synoptic (CERES-SYN) edition 4.1 dataset and ERA5 reanalysis product at the selected sites. In addition, the analysis of the spatiotemporal characteristics for the generated Ld dataset showed an increasing trend of 1.8 W m−2 per decade (p < 0.01) from 2003 to 2018, which was closely related to Ta and water vapor pressure. In general, the generated Ld dataset has a higher spatial resolution and accuracy, which can contribute to perfect the existing radiation products.

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MAPPING GLOBAL OCEAN SURFACE ALBEDO FROM SATELLITE OBSERVATIONS: MODELS, ALGORITHMS, AND DATASETS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-3-967-2018 ◽

2018 ◽

Vol XLII-3 ◽

pp. 967-970

Author(s):

X. Li ◽

X. Fan ◽

H. Yan ◽

A. Li ◽

M. Wang ◽

...

Keyword(s):

Land Surface ◽

Surface Albedo ◽

Global Climate ◽

Estimation Method ◽

Ocean Surface ◽

Satellite Observations ◽

Surface Radiation ◽

Radiation Budget ◽

Global Ocean ◽

Ocean Water

Ocean surface albedo (OSA) is one of the important parameters in surface radiation budget (SRB). It is usually considered as a controlling factor of the heat exchange among the atmosphere and ocean. The temporal and spatial dynamics of OSA determine the energy absorption of upper level ocean water, and have influences on the oceanic currents, atmospheric circulations, and transportation of material and energy of hydrosphere. Therefore, various parameterizations and models have been developed for describing the dynamics of OSA. However, it has been demonstrated that the currently available OSA datasets cannot full fill the requirement of global climate change studies. In this study, we present a literature review on mapping global OSA from satellite observations. The models (parameterizations, the coupled ocean-atmosphere radiative transfer (COART), and the three component ocean water albedo (TCOWA)), algorithms (the estimation method based on reanalysis data, and the direct-estimation algorithm), and datasets (the cloud, albedo and radiation (CLARA) surface albedo product, dataset derived by the TCOWA model, and the global land surface satellite (GLASS) phase-2 surface broadband albedo product) of OSA have been discussed, separately.

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Retrieving Crop Albedo Based on Radar Sentinel-1 and Random Forest Approach

Remote Sensing ◽

10.3390/rs13163181 ◽

2021 ◽

Vol 13 (16) ◽

pp. 3181

Author(s):

Abdelhakim Amazirh ◽

El Houssaine Bouras ◽

Luis Enrique Olivera-Guerra ◽

Salah Er-Raki ◽

Abdelghani Chehbouni

Keyword(s):

Energy Balance ◽

Random Forest ◽

Water Surface ◽

Surface Albedo ◽

Surface Energy Balance ◽

Growing Season ◽

Surface Radiation ◽

Radiation Budget ◽

Surface Radiation Budget ◽

Semi Arid

Monitoring agricultural crops is of paramount importance for preserving water resources and increasing water efficiency over semi-arid areas. This can be achieved by modelling the water resources all along the growing season through the coupled water–surface energy balance. Surface albedo is a key land surface variable to constrain the surface radiation budget and hence the coupled water–surface energy balance. In order to capture the hydric status changes over the growing season, optical remote sensing becomes impractical due to cloud cover in some periods, especially over irrigated winter crops in semi-arid regions. To fill the gap, this paper aims to generate cloudless surface albedo product from Sentinel-1 data that offers a source of high spatio-temporal resolution images. This can help to better capture the vegetation development along the growth season through the surface radiation budget. Random Forest (RF) algorithm was implemented using Sentinel-1 backscatters as input. The approach was tested over an irrigated semi-arid zone in Morocco, which is known by its heterogeneity in term of soil conditions and crop types. The obtained results are evaluated against Landsat-derived albedo with quasi-concurrent Landsat/Sentinel-1 overpasses (up to one day offset), while a further validation was investigated using in situ field scale albedo data. The best model-hyperparameters selection was dependent on two validation approaches (K-fold cross-validation ‘k = 10’, and holdout). The more robust and accurate model parameters are those that represent the best statistical metrics (root mean square error ‘RMSE’, bias and correlation coefficient ‘R’). Coefficient values ranging from 0.70 to 0.79 and a RMSE value between 0.0002 and 0.00048 were obtained comparing Landsat and predicted albedo by RF method. The relative error ratio equals 4.5, which is acceptable to predict surface albedo.

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