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Item Surface Shortwave Net Radiation Estimation from FengYun-3 MERSI Data(MDPI, 2015-05-19) Wang, Dongdong; Liang, Shunlin; He, Tao; Cao, Yunfeng; Jiang, BoThe Medium-Resolution Spectral Imager (MERSI) is one of the major payloads of China’s second-generation polar-orbiting meteorological satellite, FengYun-3 (FY-3), and it is similar to the Moderate-Resolution Imaging Spectroradiometer (MODIS). The MERSI data are suitable for mapping terrestrial, atmospheric and oceanographic variables at continental to global scales. This study presents a direct-estimation method to retrieve surface shortwave net radiation (SSNR) data from MERSI top-of-atmosphere (TOA) reflectance and cloud mask products. This study is the first attempt to use the MERSI to retrieve SSNR data. Several critical issues concerning remote sensing of SSNR were investigated, including scale effects in validating SSNR data, impacts of the MERSI calibration update on the estimation of SSNR and the dependency of the retrieval accuracy of SSNR data on view geometry. We also incorporated data from twin MODIS sensors to assess how time and the number of satellite overpasses affect the retrieval of SSNR data. Validation against one-year data over seven Surface Radiation Budget Network (SURFRAD) stations showed that the presented algorithm estimated daily SSNR at the original resolution of the MERSI with a root mean square error (RMSE) of 41.9 W/m2 and a bias of −1.6 W/m2. Aggregated to a spatial resolution of 161 km, the RMSE of MERSI retrievals can be reduced by approximately 10 W/m2. Combined with MODIS data, the RMSE of daily SSNR estimation can be further reduced to 22.2 W/m2. Compared with that of daily SSNR, estimation of monthly SSNR is less affected by the number of satellite overpasses per day. The RMSE of monthly SSNR from a single MERSI sensor is as small as 13.5 W/m2.Item A New Set of MODIS Land Products (MCD18): Downward Shortwave Radiation and Photosynthetically Active Radiation(MDPI, 2020-01-03) Wang, Dongdong; Liang, Shunlin; Zhang, Yi; Gao, Xueyuan; Brown, Meredith G. L.; Jia, AolinSurface downward shortwave radiation (DSR) and photosynthetically active radiation (PAR), its visible component, are key parameters needed for many land process models and terrestrial applications. Most existing DSR and PAR products were developed for climate studies and therefore have coarse spatial resolutions, which cannot satisfy the requirements of many applications. This paper introduces a new global high-resolution product of DSR (MCD18A1) and PAR (MCD18A2) over land surfaces using the MODIS data. The current version is Collection 6.0 at the spatial resolution of 5 km and two temporal resolutions (instantaneous and three-hour). A look-up table (LUT) based retrieval approach was chosen as the main operational algorithm so as to generate the products from the MODIS top-of-atmosphere (TOA) reflectance and other ancillary data sets. The new MCD18 products are archived and distributed via NASA’s Land Processes Distributed Active Archive Center (LP DAAC). The products have been validated based on one year of ground radiation measurements at 33 Baseline Surface Radiation Network (BSRN) and 25 AmeriFlux stations. The instantaneous DSR has a bias of −15.4 W/m2 and root mean square error (RMSE) of 101.0 W/m2, while the instantaneous PAR has a bias of −0.6 W/m2 and RMSE of 45.7 W/m2. RMSE of daily DSR is 32.3 W/m2, and that of the daily PAR is 13.1 W/m2. The accuracy of the new MODIS daily DSR data is higher than the GLASS product and lower than the CERES product, while the latter incorporates additional geostationary data with better capturing DSR diurnal variability. MCD18 products are currently under reprocessing and the new version (Collection 6.1) will provide improved spatial resolution (1 km) and accuracy.Item Intercomparison of Machine-Learning Methods for Estimating Surface Shortwave and Photosynthetically Active Radiation(MDPI, 2020-01-23) Brown, Meredith G. L.; Skakun, Sergii; He, Tao; Liang, ShunlinSatellite-derived estimates of downward surface shortwave radiation (SSR) and photosynthetically active radiation (PAR) are a part of the surface radiation budget, an essential climate variable (ECV) required by climate and vegetation models. Ground measurements are insufficient for generating long-term, global measurements of surface radiation, primarily due to spatial limitations; however, remotely sensed Earth observations offer freely available, multi-day, global coverage of radiance that can be used to derive SSR and PAR estimates. Satellite-derived SSR and PAR estimates are generated by computing the radiative transfer inversion of top-of-atmosphere (TOA) measurements, and require ancillary data on the atmospheric condition. To reduce computational costs, often the radiative transfer calculations are done offline and large look-up tables (LUTs) are generated to derive estimates more quickly. Recently studies have begun exploring the use of machine-learning techniques, such as neural networks, to try to improve computational efficiency. Here, nine machine-learning methods were tested to model SSR and PAR using minimal input data from the Moderate Resolution Imaging Spectrometer (MODIS) observations at 1 km spatial resolution. The aim was to reduce the input data requirements to create the most robust model possible. The bootstrap aggregated decision tree (Bagged Tree), Gaussian Process Regression, and Neural Network yielded the best results with minimal training data requirements: an 𝑅2 of 0.77, 0.78, and 0.78 respectively, a bias of 0 ± 6, 0 ± 6, and 0 ± 5 W/m2, and an RMSE of 140 ± 7, 135 ± 8, and 138 ± 7 W/m2, respectively, for all-sky condition total surface shortwave radiation and viewing angles less than 55°. Viewing angles above 55° were excluded because the residual analysis showed exponential error growth above 55°. A simple, robust model for estimating SSR and PAR using machine-learning methods is useful for a variety of climate system studies. Future studies may focus on developing high temporal resolution direct and diffuse estimates of SSR and PAR as most current models estimate only total SSR or PAR.Item A Direct Algorithm for Estimating Land Surface Broadband Albedos From MODIS Imagery(Institute of Electrical and Electronics Engineers, 2003-01) Liang, ShunlinLand surface albedo is a critical variable needed in land surface modeling. The conventional methods for estimating broadband albedos rely on a series of steps in the processing chain, including atmospheric correction, surface angular modeling, and narrowband-to-broadband albedo conversions. Unfortunately, errors associated with each procedure may be accumulated and significantly impact the accuracy of the final albedo products. In an earlier study, we developed a new direct procedure that links the top-of-atmosphere spectral albedos with land surface broadband albedos without performing atmospheric correction and other processes. In this paper, this method is further improved in several aspects and implemented using actual Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Several case studies indicated that this new method can predict land surface broadband albedos very accurately and eliminate aerosol effects effectively. It is very promising for global applications and is particularly suitable for nonvegetated land surfaces. Note that a Lambertian surface has been assumed in the radiative transfer simulation in this paper as a first-order approximation; this assumption can be easily removed as long as a global bidirectional reflectance distribution function climatology is available,Item Estimation of Systematic Errors of MODIS Thermal Infrared Bands(Institute of Electrical and Electronics Engineers, 2006-10) Liang, Shunlin; Liu, Ronggao G.; Liu, Jiyuan Y.This letter reports a statistical method to estimate detector-dependent systematic error in Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared (TIR) Bands 20–25 and 27–36. There exist scan-to-scan overlapped pixels in MODIS data. By analyzing a sufficiently large amount of those most overlapped pixels, the systematic error of each detector in the TIR bands can be estimated. The results show that the Aqua MODIS data are generally better than the Terra MODIS data in 160 MODIS TIR detectors. There are no detector-dependent systematic errors in Bands 31 and 32 for both Terra and Aqua MODIS data. The maximum detector errors are 3.00 K in Band 21 of Terra and −8.15 K in that of Aqua for brightness temperatures of more than 250 K.Item Consistency of MODIS surface bidirectional reflectance distribution function and albedo retrievals: 2. Validation(American Geophysical Union, 2003-03-08) Liang, Shunlin; Lucht, Wolfgang; Jin, Yufang; Schaaf, Crystal B.; Woodcock, Curtis E.; Gao, Feng; Li, XiaowenThe evaluation of the first available satellite-based global albedo product at 1-km resolution is essential for its application in climate studies. We evaluate the accuracy of the Moderate-Resolution Imaging Spectroradiometer (MODIS) albedo product using available field measurements at Surface Radiation Budget Network (SURFRAD) and Cloud and Radiation Testbed–Southern Great Plains (CART/SGP) stations and examine the consistency between the MODIS surface albedos and the Clouds and Earth’s Radiant Energy System (CERES) top-of-the-atmosphere albedos as well as historical global albedos from advanced very high resolution radiometer (AVHRR) and Earth Radiation Budget Experiment (ERBE) observations. A comparison with the field measurements shows that the MODIS surface albedo generally meets an absolute accuracy requirement of 0.02 for our study sites during April–September 2001, with the root mean square errors less than 0.018. Larger differences appear in the winter season probably due to the increased heterogeneity of surface reflectivity in the presence of snow. To examine the effect of spatial heterogeneity on the validation of the MODIS albedos using fine resolution field measurements, we derive an intermediate albedo product from four Landsat Enhanced Thematic Mapper Plus (ETM+) images at 30-m spatial resolution as a surrogate for the distributed field measurements. The surface albedo is relatively homogeneous over the study stations in growing seasons, and therefore the validation during April–September is supported. A case study over three SURFRAD stations reveals that the MODIS bidirectional reflectance distribution function model is able to capture the solar zenith angle dependence of surface albedo as shown by the field measurements. We also find that the MODIS surface shortwave albedo is consistent with the contemporary and collocated CERES top-of atmosphere albedos derived directly from broadband observations. The MODIS albedo is also well correlated with historical surface albedos derived from AVHRR and ERBE observations, and a high bias of 0.016 and a low bias of 0.034 compared to those of the latter albedos are reasonable considering the differences in instruments and retrieval algorithms as well as environmental changes.Item Consistency of MODIS surface BRDF/Albedo retrievals 1. Algorithm performance(American Geophysical Union, 2003-03-08) Liang, Shunlin; Jin, Yufang; Lucht, Wolfgang; Schaaf, Crystal B.; Gao, Feng; Li, Xiaowen; Strahler, Alan H.The first consistent year (November 2000 to November 2001) of global albedo product was produced at 1-km resolution every 16 days from the observations of the Moderate- Resolution Imaging Spectroradiometer (MODIS) instrument aboard NASA’s Terra spacecraft.We evaluated the quality of the operational albedo retrievals in two ways: (1) by examining the algorithm performance using the product quality assurance (QA) fields (this paper) and (2) by comparing retrieved albedos with those observed at ground stations and by other satellite instruments (in a companion paper). The internal diagnostics of the retrieval algorithm adequately reflect the goodness of the model fit and the random noise amplification in the retrieved albedo. Global QA statistics show that the RossThick- LiSparse-Reciprocal model fits the atmospherically corrected surface reflectances very well, and the random noise amplification factors for white sky albedo and reflectance are generally less than 1.0. Cloud obscuration is the main reason for the activation of the backup magnitude retrieval algorithm. Over the 60°S to 60°N latitude band, 50% of the land pixels acquire more than six clear looks during 14–29 September 2001, and only 5% of these pixels are inverted with the backup algorithm. The latitude dependence and temporal distribution of the QA fields further demonstrate that the retrieval status mainly follows the pattern of angular sampling determined by cloud climatology and the instrument/orbit characteristics. A case study over the west coast of the United States shows that white sky shortwave albedos retrieved from magnitude inversions agree on average with those from full inversions to within 0.033 in reflectance units and have a slightly lower bias ranging from 0.014 to 0.023. We also explored the effect of residual cloud and aerosol contamination in the atmospherically corrected surface reflectance inputs in another case study over southern Africa. The quality assurance procedure of the operational MODIS bidirectional reflectance distribution function and albedo algorithm compensates for some of these residual effects and improves the albedo retrieval results by an order of 0.005 (10%) in the visible for more than 12% of pixels.Item Mapping daily snow/ice shortwave broadband albedo from Moderate Resolution Imaging Spectroradiometer (MODIS): The improved direct retrieval algorithm and validation with Greenland in situ measurement(American Geophysical Union, 2005-05-26) Liang, Shunlin; Stroeve, Julienne; Box, Jason E.Snow/ice albedo is a critical variable in surface energy balance calculations. The Moderate Resolution Imaging Spectroradiometer (MODIS) data have been used routinely to provide global land surface albedo. The MODIS algorithm includes atmospheric correction, surface reflectance angular modeling, and narrowband to broadband albedo conversion. In an earlier study, a "direct retrieval" methodology was proposed to calculate instantaneous albedo over snow and ice-covered surfaces directly from top-of-atmosphere (TOA) MODIS reflectance data. The method consists of extensive radiative transfer simulations for a variety of atmospheric and surface snow conditions and links the TOA reflectance with surface broadband albedo through regression analysis. Therefore the direct retrieval algorithm implicitly incorporates in a single step all three procedures used in the standard MODIS surface albedo algorithm. This study presents improvements to the retrieval algorithm including validation with in situ measurements distributed over the Greenland ice sheet. Comparison with surface observations demonstrates that the direct retrieval algorithm can produce very accurate daily snow/ice albedo with mean bias of less than 0.02 and residual standard error of 0.04.Item Continuous tree distribution in China: A comparison of two estimates from MODIS and Landsat data(American Geophysical Union, 2006-04-18) Liang, Shunlin; Liu, Ronggao; Liu, Jiyuan; Zhuang, DafangForest change is a major contributor to changes in carbon stocks and trace gas fluxes between terrestrial and atmospheric layers. This study compares two satellite estimates of percent tree distribution data sets over China. One estimate is from the Chinese National Land Cover Data Set (NLCD) generated by a multiyear national land cover project in China through visual interpretation of Landsat thematic mapper (TM) and the Enhanced Thematic Mapper Plus (ETM+) images primarily acquired in the year 2000. The other estimate is the Moderate-Resolution Imaging Spectroradiometer (MODIS) standard product (MOD44B) from the same year. The two products reveal some common features, but significant discrepancies exist. Detailed analyses are carried out with different land cover types and over different regions. Comparison results show that the difference of the total tree canopy area for the whole country is 159,000 km2. The pixel counts in the NLCD data set for dense forest are ~4 times those in the MODIS data set with the reverse holding for sparse forest. Generally, the percent tree canopy area of the NLCD data set is larger in eastern China and lower in the Tibetan plateau margin region. For different land cover types the percentage of tree canopy areas shows a good agreement for evergreen forests but a large discrepancy for deciduous forests. The largest variations are associated with grassland and nonvegetation classes. Regarding the spatial distributions of their differences, Inner Mongolia is the place where both data sets show a diverse result, but Guizhou and Fujian present the least divergence among those provinces with the tree canopy area being more than 20,000 km2.Item Estimation of incident Photosynthetically Active Radiation from MODIS Data(American Geophysical Union, 2006-08-08) Liang, Shunlin; Zheng, Tao; Liu, Ronggao; Fang, Hongliang; Tsay, Si-Chee; Running, StevenIncident photosynthetically active radiation (PAR) is a key variable needed by almost all terrestrial ecosystem models. Unfortunately, the current incident PAR products estimated from remotely sensed data at spatial and temporal resolutions are not sufficient for carbon cycle modeling and various applications. In this study, the authors develop a new method based on the look-up table approach for estimating instantaneous incident PAR from the polar-orbiting Moderate Resolution Imaging Spectrometer (MODIS) data. Since the top-of-atmosphere (TOA) radiance depends on both surface reflectance and atmospheric properties that largely determine the incident PAR, our first step is to estimate surface reflectance. The approach assumes known aerosol properties for the observations with minimum blue reflectance from a temporal window of each pixel. Their inverted surface reflectance is then interpolated to determine the surface reflectance of other observations. The second step is to calculate PAR by matching the computed TOA reflectance from the look-up table with the TOA values of the satellite observations. Both the direct and diffuse PAR components, as well as the total shortwave radiation, are determined in exactly the same fashion. The calculation of a daily average PAR value from one or two instantaneous PAR values is also explored. Ground measurements from seven FLUXNET sites are used for validating the algorithm. The results indicate that this approach can produce reasonable PAR product at 1 km resolution and is suitable for global applications, although more quantitative validation activities are still needed.