Evaluation of MODIS albedo product (MCD43A) over grassland, agriculture and forest surface types during dormant and snow-covered periods

Wang, Zhuosen; Schaaf, Crystal B.; Strahler, Alan H.; Chopping, Mark; Román, M. O.; Shuai, Yanmin; Woodcock, Curtis E.; Hollinger, David Y.; Fitzjarrald, David R.

doi:10.1016/j.rse.2013.08.025

Cited by 213 publications

(172 citation statements)

References 80 publications

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“…The MCD43 product is validated to stage 3 signifying that the high-quality retrievals are within 5 % of field measurements. Additionally, a very recent field evaluation of the MCD43A product (the standard 500 m MCD43 product from which the MCD43D is derived) found root mean square errors of less than 0.03 over agricultural and grassland sites, and less than 0.02 over forested sites, during dormant snow-free periods (Wang et al, 2014). To avoid interpreting results that are within observational uncertainty, we only show differences between the MODIS and the simulated albedo which are greater than 0.05.…”

Section: Modis Albedomentioning

confidence: 98%

Implementation of a soil albedo scheme in the CABLEv1.4b land surface model and evaluation against MODIS estimates over Australia

et al. 2014

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Abstract. Land surface albedo, the fraction of incoming solar radiation reflected by the land surface, is a key component of the Earth system. This study evaluates snow-free surface albedo simulations by the Community Atmosphere Biosphere Land Exchange (CABLEv1.4b) model with the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Satellite Pour L'Observation de la Terre (SPOT) albedo. We compare results from offline simulations over the Australian continent. The control simulation has prescribed background snow-free and vegetation-free soil albedo derived from MODIS whilst the experiments use a simple parameterisation based on soil moisture and colour, originally from the Biosphere Atmosphere Transfer Scheme (BATS), and adopted in the Common Land Model (CLM). The control simulation, with prescribed soil albedo, shows that CABLE simulates overall albedo over Australia reasonably well, with differences compared to MODIS and SPOT albedos within ±0.1. Application of the original BATS scheme, which uses an eight-class soil classification, resulted in large differences of up to −0.25 for the near-infrared (NIR) albedo over large parts of the desert regions of central Australia. The use of a recalibrated 20-class soil colour classification from the CLM, which includes a higher range for saturated and VIS (visible) and NIR soil albedos, reduced the underestimation of the NIR albedo. However, this soil colour mapping is tuned to CLM soil moisture, a quantity which is not necessarily transferrable between land surface models. We therefore recalibrated the soil color map using CABLE's climatological soil moisture, which further reduced the underestimation of the NIR albedo to within ±0.15 over most of the continent as compared to MODIS and SPOT albedos. Small areas of larger differences of up to −0.25 remained within the central arid parts of the continent during summer; however, the spatial extent of these large differences is substantially reduced as compared to the simulation using the default eight-class uncalibrated soil colour map. It is now possible to use CABLE coupled to atmospheric models to investigate soil-moisture-albedo feedbacks, an important enhancement of the model.

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Section: Modis Albedomentioning

confidence: 98%

Implementation of a soil albedo scheme in the CABLEv1.4b land surface model and evaluation against MODIS estimates over Australia

et al. 2014

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“…Aksai Chin Lake Nam Co Lake Jingyu Lake Zhari Namco Lake Ngoring Lake Qinghai Lake Surface area (km 2 From 3 to 6 January 2014, a short-term field experiment aimed at measuring the ice surface radiation balance was carried out over the west of Ngoring Lake (Figure 2a). The field observation was forced to terminate on 6 January due to a huge ice crack between the lakeshore and the observation site (34.92°N, 97.58°E).…”

Section: Lake Namesmentioning

confidence: 99%

“…The Tibetan Plateau (TP) contains numerous lakes with a total area of 4.7 × 10 4 km 2 [1], and approximately 389 lakes are larger than 10 km 2 [2]. Over the past 82,000 years, there has been a good correlation between the shrinking of lakes in the TP and the weakening of the Asian monsoon [3].…”

Section: Introductionmentioning

confidence: 99%

An Investigation of Ice Surface Albedo and Its Influence on the High-Altitude Lakes of the Tibetan Plateau

Lang

Lyu

et al. 2018

Remote Sensing

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Most high-altitude lakes are more sensitive to global warming than the regional atmosphere. However, most existing climate models produce unrealistic surface temperatures on the Tibetan Plateau (TP) lakes, and few studies have focused on the influence of ice surface albedo on high-altitude lakes. Based on field albedo measurements, moderate resolution imaging spectrometer (MODIS) albedo products and numerical simulation, this study evaluates the ice albedo parameterization schemes in existing lake models and investigates the characteristics of the ice surface albedo in six typical TP lakes, as well as the influence of ice albedo error in the FLake model. Compared with observations, several ice albedo schemes all clearly overestimate the lake ice albedo by 0.26 to 0.66, while the average bias of MODIS albedo products is only 0.07. The MODIS-observed albedo of a snow-covered lake varies with the snow proportion, and the lake surface albedo in a snow-free state is approximately 0.15 during the frozen period. The MODIS-observed ice surface (snow-free) albedos are concentrated within the ranges of 0.14-0.16, 0.08-0.10 and 0.10-0.12 in Aksai Chin Lake, Nam Co Lake and Ngoring Lake, respectively. The simulated lake surface temperature is sensitive to variations in lake ice albedo especially in the spring and winter.

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“…The AMBRALS is applied to generating the MODIS BRDF/Albedo products by Schaaf et al [46], which can estimate the land surface albedo of land surfaces (1-km spatial resolution, 8-day temporal resolution) with clear sky, multi-bands, multi-angular MODIS reflectance data during a 16-day observation cycle. Recently, the daily surface broadband albedo product (MCD43A) is also being generated using a 16-day rolling method [60,61]. In these studies, the Ross-Thick and Li-Sparse-R kernel functions are employed for fitting a multi-angular observed BRF.…”

Section: Brdf Angular Modelingmentioning

confidence: 99%

Mapping Surface Broadband Albedo from Satellite Observations: A Review of Literatures on Algorithms and Products

et al. 2015

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Surface albedo is one of the key controlling geophysical parameters in the surface energy budget studies, and its temporal and spatial variation is closely related to the global climate change and regional weather system due to the albedo feedback mechanism. As an efficient tool for monitoring the surfaces of the Earth, remote sensing is widely used for deriving long-term surface broadband albedo with various geostationary and polar-orbit satellite platforms in recent decades. Moreover, the algorithms for estimating surface broadband albedo from satellite observations, including narrow-to-broadband conversions, bidirectional reflectance distribution function (BRDF) angular modeling, direct-estimation algorithm and the algorithms for estimating albedo from geostationary satellite data, are developed and improved. In this paper, we present a comprehensive literature review on algorithms and products for mapping surface broadband albedo with satellite observations and provide a discussion of different algorithms and products in a historical perspective based on citation analysis of the published literature. This paper shows that the observation technologies and accuracy requirement of applications are important, and long-term, global OPEN ACCESSRemote Sens. 2015, 7 991 fully-covered (including land, ocean, and sea-ice surfaces), gap-free, surface broadband albedo products with higher spatial and temporal resolution are required for climate change, surface energy budget, and hydrological studies.

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Evaluation of MODIS albedo product (MCD43A) over grassland, agriculture and forest surface types during dormant and snow-covered periods

Cited by 213 publications

References 80 publications

Implementation of a soil albedo scheme in the CABLEv1.4b land surface model and evaluation against MODIS estimates over Australia

Implementation of a soil albedo scheme in the CABLEv1.4b land surface model and evaluation against MODIS estimates over Australia

An Investigation of Ice Surface Albedo and Its Influence on the High-Altitude Lakes of the Tibetan Plateau

Mapping Surface Broadband Albedo from Satellite Observations: A Review of Literatures on Algorithms and Products

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