scholarly journals Estimation of Land Surface Albedo from MODIS and VIIRS Data: A Multi-Sensor Strategy Based on the Direct Estimation Algorithm and Statistical-Based Temporal Filter

2020 ◽  
Vol 12 (24) ◽  
pp. 4131
Author(s):  
Mengsi Wang ◽  
Xianlei Fan ◽  
Xijia Li ◽  
Qiang Liu ◽  
Ying Qu
Keyword(s):  
Temporal Resolution ◽  
Land Surface ◽  
Surface Albedo ◽  
Estimation Algorithm ◽  
Radiation Budget ◽  
Estimation Accuracy ◽  
High Temporal Resolution ◽  
Direct Estimation ◽  
Temporal Continuity ◽  
Temporal Filter

Land surface albedo is an important variable for Earth’s radiation and energy budget. Over the past decades, many surface albedo products have been derived from a variety of remote sensing data. However, the estimation accuracy, temporal resolution, and temporal continuity of these datasets still need to be improved. We developed a multi-sensor strategy (MSS) based on the direct-estimation algorithm (DEA) and Statistical-Based Temporal Filter (STF) to improve the quality of land surface albedo datasets. The moderate-resolution imaging spectroradiometer (MODIS) data onboard Terra and Aqua and the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi-National Polar-orbiting Partnership (NPP) were used as multi-sensor data. The MCD43A3 product and in situ measurements from the Surface Radiation Budget Network (SURFRAD) and FLUXNET sites were employed for validation and comparison. The results showed that the proposed MSS method significantly improved the temporal continuity and estimation accuracy during the snow-covered period, which was more consistent with the measurements of SURFRAD (R = 0.9498, root mean square error (RMSE) = 0.0387, and bias = −0.0017) and FLUXNET (R = 0.9421, RMSE = 0.0330, and bias = 0.0002) sites. Moreover, this is a promising method to generate long-term, spatiotemporal continuous land surface albedo datasets with high temporal resolution.

scholarly journals A statistics-based temporal filter algorithm to map spatiotemporally continuous shortwave albedo from MODIS data

2013 ◽  
Vol 17 (6) ◽  
pp. 2121-2129 ◽  
Author(s):  
N. F. Liu ◽  
Q. Liu ◽  
L. Z. Wang ◽  
S. L. Liang ◽  
J. G. Wen ◽  
...  
Keyword(s):  
Time Series ◽  
Temporal Resolution ◽  
Land Surface ◽  
Surface Albedo ◽  
Critical Role ◽  
Radiant Energy ◽  
High Temporal Resolution ◽  
Land Surface Parameter ◽  
Temporal Filter ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Land-surface albedo plays a critical role in the earth's radiant energy budget studies. Satellite remote sensing provides an effective approach to acquire regional and global albedo observations. Owing to cloud coverage, seasonal snow and sensor malfunctions, spatiotemporally continuous albedo datasets are often inaccessible. The Global LAnd Surface Satellite (GLASS) project aims at providing a suite of key land surface parameter datasets with high temporal resolution and high accuracy for a global change study. The GLASS preliminary albedo datasets are global daily land-surface albedo generated by an angular bin algorithm (Qu et al., 2013). Like other products, the GLASS preliminary albedo datasets are affected by large areas of missing data; beside, sharp fluctuations exist in the time series of the GLASS preliminary albedo due to data noise and algorithm uncertainties. Based on the Bayesian theory, a statistics-based temporal filter (STF) algorithm is proposed in this paper to fill data gaps, smooth albedo time series, and generate the GLASS final albedo product. The results of the STF algorithm are smooth and gapless albedo time series, with uncertainty estimations. The performance of the STF method was tested on one tile (H25V05) and three ground stations. Results show that the STF method has greatly improved the integrity and smoothness of the GLASS final albedo product. Seasonal trends in albedo are well depicted by the GLASS final albedo product. Compared with MODerate resolution Imaging Spectroradiometer (MODIS) product, the GLASS final albedo product has a higher temporal resolution and more competence in capturing the surface albedo variations. It is recommended that the quality flag should be always checked before using the GLASS final albedo product.

scholarly journals Using the anomaly forcing Community Land Model (CLM 4.5) for crop yield projections

2020 ◽  
Author(s):  
Yaqiong Lu ◽  
Xianyu Yang
Keyword(s):  
Crop Yield ◽  
Temporal Resolution ◽  
Land Surface ◽  
Crop Yields ◽  
Surface Model ◽  
High Temporal Resolution ◽  
Climate Scenarios ◽  
Climate Data ◽  
Land Surface Models ◽  
Surface Models

Abstract. Crop growth in land surface models normally requires high temporal resolution climate data (3-hourly or 6-hourly), but such high temporal resolution climate data are not provided by many climate model simulations due to expensive storage, which limits modeling choice if there is an interest in a particular climate simulation that only saved monthly outputs. The Community Land Surface Model (CLM) has proposed an alternative approach for utilizing monthly climate outputs as forcing data since version 4.5, and it is called the anomaly forcing CLM. However, such an approach has never been validated for crop yield projections. In our work, we created anomaly forcing datasets for three climate scenarios (1.5 °C warming, 2.0 °C warming, and RCP4.5) and validated crop yields against the standard CLM forcing with the same climate scenarios using 3-hourly data. We found that the anomaly forcing CLM could not produce crop yields identical to the standard CLM due to the different submonthly variations, and crop yields were underestimated by 5–8 % across the three scenarios (1.5 °C, 2.0 °C, and RCP4.5) for the global average, and 28–41 % of cropland showed significantly different yields. However, the anomaly forcing CLM effectively captured the relative changes between scenarios and over time, as well as regional crop yield variations. We recommend that such an approach be used for qualitative analysis of crop yields when only monthly outputs are available. Our approach can be adopted by other land surface models to expand their capabilities for utilizing monthly climate data.

scholarly journals The Estimation of Surface Albedo from DSCOVR EPIC

2020 ◽  
Vol 12 (11) ◽  
pp. 1897
Author(s):  
Qiuyue Tian ◽  
Qiang Liu ◽  
Jie Guang ◽  
Leiku Yang ◽  
Hanwei Zhang ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Surface Albedo ◽  
Climate Models ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
High Temporal Resolution ◽  
Observation Data ◽  
Climate Change Research ◽  
Narrow Channels ◽  
The Earth

Surface albedo is an important parameter in climate models. The main way to obtain continuous surface albedo for large areas is satellite remote sensing. However, the existing albedo products rarely meet daily-scale requirements, which has a large impact on climate change research and rapid dynamic changes of surface analysis. The Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory (DSCOVR) platform, which was launched into the Sun–Earth’s first Lagrange Point (L1) orbit, can provide spectral images of the entire sunlit face of Earth with 10 narrow channels (from 317 to 780 nm). As EPIC can provide high-temporal resolution data, it is beneficial to explore the feasibility of EPIC to estimate high-temporal resolution surface albedo. In this study, hourly surface albedo was calculated based on EPIC observation data. Then, the estimated albedo results were validated by ground-based observations of different land cover types. The results show that the EPIC albedo is basically consistent with the trend of the ground-based observations in the whole time series variation. The diurnal variation of the surface albedo from the hourly EPIC albedo exhibits a “U” shape curve, which has the same trend as the ground-based observations. Therefore, EPIC is helpful to enhance the temporal resolution of surface albedo to diurnal. Surfaces with a three-dimensional structure that casts shadows display the hotspot effect, producing a reflectance peak in the retro-solar direction and lower reflectance at viewing angles away from the solar direction. DSCOVR observes the entire sunlit face of the Earth, which is helpful to make up for the deficiency in the observations of traditional satellites in the hotspot direction in bidirectional reflectance distribution function (BRDF) research, and can help to improve the underestimation of albedo in the direction of hotspot observation.

Direct Estimation of Land Surface Albedo From Simultaneous MISR Data

2017 ◽  
Vol 55 (5) ◽  
pp. 2605-2617 ◽  
Author(s):  
Tao He ◽  
Shunlin Liang ◽  
Dongdong Wang
Keyword(s):  
Land Surface ◽  
Surface Albedo ◽  
Direct Estimation

scholarly journals DSCOVR/EPIC-derived global hourly and daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution

2020 ◽  
Vol 12 (3) ◽  
pp. 2209-2221
Author(s):  
Dalei Hao ◽  
Ghassem R. Asrar ◽  
Yelu Zeng ◽  
Qing Zhu ◽  
Jianguang Wen ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Photosynthetically Active Radiation ◽  
Spatial Scales ◽  
Radiant Energy ◽  
Surface Radiation ◽  
Radiation Budget ◽  
High Temporal Resolution ◽  
Active Radiation ◽  
Global Coverage ◽  
Mean Square Errors

Abstract. Downward shortwave radiation (SW) and photosynthetically active radiation (PAR) play crucial roles in Earth system dynamics. Spaceborne remote sensing techniques provide a unique means for mapping accurate spatiotemporally continuous SW–PAR, globally. However, any individual polar-orbiting or geostationary satellite cannot satisfy the desired high temporal resolution (sub-daily) and global coverage simultaneously, while integrating and fusing multisource data from complementary satellites/sensors is challenging because of co-registration, intercalibration, near real-time data delivery and the effects of discrepancies in orbital geometry. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR), launched in February 2015, offers an unprecedented possibility to bridge the gap between high temporal resolution and global coverage and characterize the diurnal cycles of SW–PAR globally. In this study, we adopted a suite of well-validated data-driven machine-learning models to generate the first global land products of SW–PAR, from June 2015 to June 2019, based on DSCOVR/EPIC data. The derived products have high temporal resolution (hourly) and medium spatial resolution (0.1∘×0.1∘), and they include estimates of the direct and diffuse components of SW–PAR. We used independently widely distributed ground station data from the Baseline Surface Radiation Network (BSRN), the Surface Radiation Budget Network (SURFRAD), NOAA's Global Monitoring Division and the U.S. Department of Energy's Atmospheric System Research (ASR) program to evaluate the performance of our products, and we further analyzed and compared the spatiotemporal characteristics of the derived products with the benchmarking Clouds and the Earth's Radiant Energy System Synoptic (CERES) data. We found both the hourly and daily products to be consistent with ground-based observations (e.g., hourly and daily total SWs have low biases of −3.96 and −0.71 W m−2 and root-mean-square errors (RMSEs) of 103.50 and 35.40 W m−2, respectively). The developed products capture the complex spatiotemporal patterns well and accurately track substantial diurnal, monthly, and seasonal variations in SW–PAR when compared to CERES data. They provide a reliable and valuable alternative for solar photovoltaic applications worldwide and can be used to improve our understanding of the diurnal and seasonal variabilities of the terrestrial water, carbon and energy fluxes at various spatial scales. The products are freely available at https://doi.org/10.25584/1595069 (Hao et al., 2020).

scholarly journals Modeling the Summertime Climate of Southwest Asia: The Role of Land Surface Processes in Shaping the Climate of Semiarid Regions

2012 ◽  
Vol 25 (2) ◽  
pp. 704-719 ◽  
Author(s):  
Marc P. Marcella ◽  
Elfatih A. B. Eltahir
Keyword(s):  
Vapor Pressure ◽  
Land Surface ◽  
Surface Albedo ◽  
Incident Radiation ◽  
Radiation Budget ◽  
Surface Processes ◽  
Southwest Asia ◽  
Land Surface Processes ◽  
Semiarid Regions

Abstract Presented is a study on the role of land surface processes in determining the summertime climate over the semiarid region of southwest Asia. In this region, a warm surface air temperature bias of 3.5°C is simulated in the summer by using the standard configuration of Regional Climate Model version 3 (RegCM3). Biases are also simulated in surface albedo (underestimation), shortwave incident radiation (overestimation), and vapor pressure (underestimation). Based on satellite measurements documented in NASA’s surface radiation budget (SRB) dataset, a correction in surface albedo by 4% is introduced in RegCM3 to match the observed SRB data. Increasing albedo values results in a nearly 1°C cooling over the region. In addition, by incorporating RegCM3’s dust module and including subgrid variability for surface wind, shortwave incident radiation bias originally of about 45 W m−2 is reduced by 30 W m−2. As a result, the reduction of shortwave incident radiation cools the surface by 0.6°C. Finally, including a representation for the irrigation and marshlands of Mesopotamia produces surface relative humidity values closer to observations, thus eliminating a nearly 5-mb vapor pressure dry bias over some of the region. Consequently, the representation of irrigation and marshlands results in cooling of nearly 1°C in areas downwind of the actual land-cover change. Along with identified biases in observational datasets, these combined processes explain the 3.5°C warm bias in RegCM3 simulations. Therefore, it is found that accurate representations of surface albedo, dust emissions, and irrigation are important in correctly modeling summertime climates of semiarid regions.

scholarly journals Evaluating land surface albedo estimation from Landsat MSS, TM, ETM +, and OLI data based on the unified direct estimation approach

2018 ◽  
Vol 204 ◽  
pp. 181-196 ◽  
Author(s):  
Tao He ◽  
Shunlin Liang ◽  
Dongdong Wang ◽  
Yunfeng Cao ◽  
Feng Gao ◽  
...  
Keyword(s):  
Land Surface ◽  
Surface Albedo ◽  
Direct Estimation

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

2008 ◽  
Vol 21 (18) ◽  
pp. 4723-4748 ◽  
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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