A predictor analysis framework for surface radiation budget reprocessing using satellite data

2021 ◽  
Vol 17 (1) ◽  
pp. 1
Author(s):  
Paul W. Stackhouse ◽  
Stephen J. Cox ◽  
Patricia A. Quigley ◽  
Resit Unal
Keyword(s):  
Satellite Data ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Analysis Framework ◽  
Surface Radiation Budget

A predictor analysis framework for surface radiation budget reprocessing using satellite data

2021 ◽  
Vol 17 (1) ◽  
pp. 71
Author(s):  
Patricia A. Quigley ◽  
Resit Unal ◽  
Paul W. Stackhouse Junior ◽  
Stephen J. Cox
Keyword(s):  
Satellite Data ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Analysis Framework ◽  
Surface Radiation Budget

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

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).

scholarly journals A Climatology of Surface Radiation Budget Derived from Satellite Data

1999 ◽  
Vol 12 (8) ◽  
pp. 2691-2710 ◽  
Author(s):  
Shashi K. Gupta ◽  
Nancy A. Ritchey ◽  
Anne C. Wilber ◽  
Charles H. Whitlock ◽  
Gary G. Gibson ◽  
...  
Keyword(s):  
Satellite Data ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Surface Radiation Budget

scholarly journals Retrieval of surface radiative fluxes on the marginal zone of sea ice from operational satellite data

1993 ◽  
Vol 17 ◽  
pp. 201-206 ◽  
Author(s):  
Claude Kergomard ◽  
Bernard Bonnel ◽  
Yves Fouquart
Keyword(s):  
Satellite Data ◽  
Optical Thickness ◽  
Field Measurements ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Radiative Transfer Model ◽  
Cloud Base ◽  
Transfer Model ◽  
Liquid Water Path ◽  
Surface Radiation Budget

With the development of coupled atmosphere–ocean models for the polar seas, there will be a great need of surface radiation budget data over partially ice-covered sea surfaces of the marginal ice zones. This paper presents an attempt to retrieve the surface radiation budget components over the Fram Strait area from operational satellite data, i.e. AVHRR visible and infrared radiances and SSM/I passive microwave brightness temperatures. The cloud optical thickness, which is the main modulator for the incoming solar flux, is retrieved from AVHRR visible radiances through a radiative transfer model, assuming surface conditions deduced from the SSM/I ice concentrations. The cloud base emissivity, required for the downwelling infrared flux computation, is linked to the optical thickness through the liquid water path. The results presented show a good agreement with field measurements and little sensitivity to the cloud and aerosol properties extracted from the literature rather than from the satellite data. Infrared fluxes retrievals would however require a better knowledge of the atmosphere temperature profile and cloud base altitude.

scholarly journals Retrieval of surface radiative fluxes on the marginal zone of sea ice from operational satellite data

1993 ◽  
Vol 17 ◽  
pp. 201-206 ◽  
Author(s):  
Claude Kergomard ◽  
Bernard Bonnel ◽  
Yves Fouquart
Keyword(s):  
Satellite Data ◽  
Optical Thickness ◽  
Field Measurements ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Radiative Transfer Model ◽  
Cloud Base ◽  
Transfer Model ◽  
Liquid Water Path ◽  
Surface Radiation Budget

With the development of coupled atmosphere–ocean models for the polar seas, there will be a great need of surface radiation budget data over partially ice-covered sea surfaces of the marginal ice zones. This paper presents an attempt to retrieve the surface radiation budget components over the Fram Strait area from operational satellite data, i.e. AVHRR visible and infrared radiances and SSM/I passive microwave brightness temperatures. The cloud optical thickness, which is the main modulator for the incoming solar flux, is retrieved from AVHRR visible radiances through a radiative transfer model, assuming surface conditions deduced from the SSM/I ice concentrations. The cloud base emissivity, required for the downwelling infrared flux computation, is linked to the optical thickness through the liquid water path. The results presented show a good agreement with field measurements and little sensitivity to the cloud and aerosol properties extracted from the literature rather than from the satellite data. Infrared fluxes retrievals would however require a better knowledge of the atmosphere temperature profile and cloud base altitude.

EFFECTS OF A SMALL SCRUB FIRE ON THE SURFACE RADIATION BUDGET

Weather ◽  
1980 ◽  
Vol 35 (7) ◽  
pp. 212-215 ◽  
Author(s):  
D. G. Steyn ◽  
T. R. Oke
Keyword(s):  
Surface Radiation ◽  
Radiation Budget ◽  
Surface Radiation Budget
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