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

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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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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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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Sunlight, clouds, sea ice, albedo, and the radiative budget: the umbrella versus the blanket

The Cryosphere ◽

10.5194/tc-12-2159-2018 ◽

2018 ◽

Vol 12 (6) ◽

pp. 2159-2165 ◽

Cited By ~ 7

Author(s):

Donald K. Perovich

Keyword(s):

Sea Ice ◽

Surface Albedo ◽

Radiative Heat ◽

Radiation Flux ◽

Surface Radiation ◽

Radiation Budget ◽

The Arctic ◽

Net Radiation ◽

Ice Melt ◽

Surface Radiation Budget

Abstract. The surface radiation budget of the Arctic Ocean plays a central role in summer ice melt and is governed by clouds and surface albedo. I calculated the net radiation flux for a range of albedos under sunny and cloudy skies and determined the break-even value, where the net radiation is the same for cloudy and sunny skies. Break-even albedos range from 0.30 in September to 0.58 in July. For snow-covered or bare ice, sunny skies always result in less radiative heat input. In contrast, leads always have, and ponds usually have, more radiative input under sunny skies than cloudy skies. Snow-covered ice has a net radiation flux that is negative or near zero under sunny skies, resulting in radiative cooling. Areally averaged albedos for sea ice in July result in a smaller net radiation flux under cloudy skies. For May, June, August, and September, the net radiation is smaller under sunny skies.

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Solar Radiation Partitioning and Surface Albedo Parameterization in the Hinterland of Taklimakan Desert

Advances in Meteorology ◽

10.1155/2019/9098576 ◽

2019 ◽

Vol 2019 ◽

pp. 1-8 ◽

Cited By ~ 1

Author(s):

Chunlei Meng ◽

Huoqing Li

Keyword(s):

Solar Radiation ◽

Zenith Angle ◽

Land Surface ◽

Solar Zenith Angle ◽

Surface Albedo ◽

Near Infrared ◽

Surface Radiation ◽

Parameterization Scheme ◽

Taklimakan Desert ◽

Near Surface

Surface albedo is one of the key parameters of land surface radiation and energy balance. As surface albedoes for visible and near-infrared solar radiation are quite different, solar radiation partitioning is important to parameterize the total surface albedo and upward solar radiation. In this paper, a surface albedo parameterization scheme was introduced and a solar radiation partitioning method was developed to improve the simulation of the upward solar radiation. The simulation results were validated in a hinterland site of the Taklimakan Desert. The surface albedo is not only associated with the soil moisture, but associated with the solar zenith angle. The solar radiation partitioning method considers the joint influences of cloud cover, near-surface air pressure, and solar zenith angle and was compared with the method using the Simple Biosphere Model version 3 (SiB3). The total albedo depends on the partitioning of the total visible and near-infrared radiations. The results indicate the surface albedo parameterization scheme is important to parameterize the upward solar radiation. The new solar radiation partitioning method could improve the simulation result.

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Sunlight, Clouds, Sea Ice and Albedo: The Umbrella Versus the Blanket

10.5194/tc-2018-47 ◽

2018 ◽

Author(s):

Donald K. Perovich

Keyword(s):

Sea Ice ◽

Surface Albedo ◽

Radiative Heat ◽

Radiation Flux ◽

The Other ◽

Surface Radiation ◽

Radiation Budget ◽

Net Radiation ◽

Ice Melt ◽

Surface Radiation Budget

Abstract. The surface radiation budget plays a central role in summer ice melt and is governed by clouds and surface albedo. I calculated the net radiation flux for a range of albedos under sunny and cloudy skies and determined the break-even value, where the net radiation is the same for cloudy and sunny skies. Break-even albedos range from 0.30 in September to 0.58 in July. For snow covered or bare ice, sunny skies always result in less radiative heat input. In contrast, leads always have, and ponds usually have, more radiative input under sunny skies than cloudy skies. Snow covered ice has a net radiation flux that is negative or near zero under sunny skies, resulting in radiative cooling. Areally averaged albedos for sea ice in July result in a smaller net radiation flux under cloudy skies. For the other four months, the net radiation is smaller under sunny skies.

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CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-5809-2017 ◽

2017 ◽

Vol 17 (9) ◽

pp. 5809-5828 ◽

Cited By ~ 88

Author(s):

Karl-Göran Karlsson ◽

Kati Anttila ◽

Jörg Trentmann ◽

Martin Stengel ◽

Jan Fokke Meirink ◽

...

Keyword(s):

Surface Albedo ◽

Surface Radiation ◽

Radiation Budget ◽

Climate Data ◽

Ground Segment ◽

Surface Radiation Budget ◽

Avhrr Data ◽

Data Record ◽

Development And Validation ◽

Climate Data Record

Abstract. The second edition of the satellite-derived climate data record CLARA (The CM SAF Cloud, Albedo And Surface Radiation dataset from AVHRR data – second edition denoted as CLARA-A2) is described. The data record covers the 34-year period from 1982 until 2015 and consists of cloud, surface albedo and surface radiation budget products derived from the AVHRR (Advanced Very High Resolution Radiometer) sensor carried by polar-orbiting, operational meteorological satellites. The data record is produced by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project as part of the operational ground segment. Its upgraded content and methodology improvements since edition 1 are described in detail, as are some major validation results. Some of the main improvements to the data record come from a major effort in cleaning and homogenizing the basic AVHRR level-1 radiance record and a systematic use of CALIPSO-CALIOP cloud information for development and validation purposes. Examples of applications studying decadal changes in Arctic summer surface albedo and cloud conditions are provided.

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A global long term (1981–2019) daily land surface radiation budget product from AVHRR satellite data using a residual convolutional neural network

10.5194/essd-2021-250 ◽

2021 ◽

Author(s):

Jianglei Xu ◽

Shunlin Liang ◽

Bo Jiang

Keyword(s):

Neural Network ◽

High Resolution ◽

Convolutional Neural Network ◽

Satellite Data ◽

Land Surface ◽

Radiant Energy ◽

Surface Radiation ◽

Radiation Budget ◽

Surface Radiation Budget

Abstract. The surface radiation budget, also known as all-wave net radiation (Rn), is a key parameter for various land surface processes including hydrological, ecological, agricultural, and biogeochemical processes. Satellite data can be effectively used to estimate Rn, but existing satellite products have coarse spatial resolutions and limited temporal coverage. In this study, a point-surface matching estimation (PSME) method is proposed to estimate surface Rn using a residual convolutional neural network (RCNN) integrating spatially adjacent information to improve the accuracy of retrievals. A global high-resolution (0.05°) long-term (1981–2019) Rn product was subsequently generated from Advanced Very High-Resolution Radiometer (AVHRR) data. Specifically, the RCNN was employed to establish a nonlinear relationship between globally distributed ground measurements from 537 sites and AVHRR top of atmosphere (TOA) observations. Extended triplet collocation (ETC) technology was applied to address the spatial scale mismatch issue resulting from the low spatial support of ground measurements within the AVHRR footprint by selecting reliable sites for model training. The overall independent validation results show that the generated AVHRR Rn product is highly accurate, with R2, root-mean-square error (RMSE), and bias of 0.84, 26.66 Wm−2 (31.66 %), and 1.59 Wm−2 (1.89 %), respectively. Inter-comparisons with three other Rn products, i.e., the 5 km Global Land Surface Satellite (GLASS), the 1° Clouds and the Earth's Radiant Energy System (CERES), and the 0.5° × 0.625° Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2), illustrate that our AVHRR Rn retrievals have the best accuracy under all of the considered surface and atmospheric conditions, especially thick cloud or hazy conditions. The spatiotemporal analyses of these four Rn datasets indicate that the AVHRR Rn product reasonably replicates the spatial pattern and temporal evolution trends of Rn observations. This dataset is freely available at https://doi.org/10.5281/zenodo.5509854 for 1981–2019 (Xu et al., 2021).

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