scholarly journals Variability of Surface Radiation Budget Components over the U.S. from 1996 to 2019 – Has Brightening Ceased?

2021 ◽  
Author(s):  
John A. Augustine ◽  
Gary B. Hodges
Keyword(s):  
Surface Radiation ◽  
Radiation Budget ◽  
Surface Radiation Budget ◽  
The U.S

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

2017 ◽  
Vol 17 (9) ◽  
pp. 5809-5828 ◽  
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.

scholarly journals Clouds damp the radiative impacts of polar sea ice loss

2020 ◽  
Vol 14 (8) ◽  
pp. 2673-2686 ◽  
Author(s):  
Ramdane Alkama ◽  
Patrick C. Taylor ◽  
Lorea Garcia-San Martin ◽  
Herve Douville ◽  
Gregory Duveiller ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Surface Radiation ◽  
Radiation Budget ◽  
The Arctic ◽  
Cloud Properties ◽  
Surface Radiation Budget ◽  
Cloud Radiative Effect ◽  
Radiative Impact ◽  
The Impact

Abstract. Clouds play an important role in the climate system: (1) cooling Earth by reflecting incoming sunlight to space and (2) warming Earth by reducing thermal energy loss to space. Cloud radiative effects are especially important in polar regions and have the potential to significantly alter the impact of sea ice decline on the surface radiation budget. Using CERES (Clouds and the Earth's Radiant Energy System) data and 32 CMIP5 (Coupled Model Intercomparison Project) climate models, we quantify the influence of polar clouds on the radiative impact of polar sea ice variability. Our results show that the cloud short-wave cooling effect strongly influences the impact of sea ice variability on the surface radiation budget and does so in a counter-intuitive manner over the polar seas: years with less sea ice and a larger net surface radiative flux show a more negative cloud radiative effect. Our results indicate that 66±2% of this change in the net cloud radiative effect is due to the reduction in surface albedo and that the remaining 34±1 % is due to an increase in cloud cover and optical thickness. The overall cloud radiative damping effect is 56±2 % over the Antarctic and 47±3 % over the Arctic. Thus, present-day cloud properties significantly reduce the net radiative impact of sea ice loss on the Arctic and Antarctic surface radiation budgets. As a result, climate models must accurately represent present-day polar cloud properties in order to capture the surface radiation budget impact of polar sea ice loss and thus the surface albedo feedback.

scholarly journals Daily Radiation Budget of the Baltic Sea Surface from Satellite Data

2015 ◽  
Vol 22 (3) ◽  
pp. 50-56 ◽  
Author(s):  
Tomasz Zapadka ◽  
Adam Krężel ◽  
Marcin Paszkuta ◽  
Mirosław Darecki
Keyword(s):  
Baltic Sea ◽  
Empirical Data ◽  
Statistical Error ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Satellite Monitoring ◽  
The Baltic Sea ◽  
Surface Radiation Budget ◽  
The Baltic ◽  
Oil Rig

Abstract Recently developed system for assessment of radiation budget for the Baltic Sea has been presented and verified. The system utilizes data from various sources: satellite, model and in situ measurements. It has been developed within the SatBałtyk project (Satellite Monitoring of the Baltic Sea Environment - www.satbaltyk.eu) where the energy radiation budget is one of the key element. The SatBałtyk system generates daily maps of the all components of radiation budget on every day basis. We show the scheme of making daily maps, applied algorithms and empirical data collection within the system. An empirical verification of the system has been carried out based on empirical data collected on the oil rig placed on the Baltic Sea. This verification concerned all the components of the surface radiation budget. The average daily NET products are estimated with statistical error ca. 13 Wm-2. The biggest absolute statistical error is for LWd component and equals 14 Wm-2. The relative error in relation to the average annual values for whole Baltic is the biggest for SWu and reaches 25%. All estimated components have correlation coefficient above 0.91.

scholarly journals Effects of clouds and precipitation disturbance on the surface radiation budget and energy balance over loess plateau semi-arid grassland in China

2013 ◽  
Vol 62 (20) ◽  
pp. 209201
Author(s):  
Yue Ping ◽  
Zhang Qiang ◽  
Zhao Wen ◽  
Wang Jin-Song ◽  
Wang Run-Yuan ◽  
...  
Keyword(s):  
Energy Balance ◽  
Loess Plateau ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Surface Radiation Budget ◽  
Semi Arid

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 Evaluation of Six High-Spatial Resolution Clear-Sky Surface Upward Longwave Radiation Estimation Methods with MODIS

2020 ◽  
Vol 12 (11) ◽  
pp. 1834
Author(s):  
Boxiong Qin ◽  
Biao Cao ◽  
Hua Li ◽  
Zunjian Bian ◽  
Tian Hu ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Hybrid Methods ◽  
Longwave Radiation ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Estimation Methods ◽  
Mean Bias Error ◽  
Clear Sky ◽  
Surface Radiation Budget

Surface upward longwave radiation (SULR) is a critical component in the calculation of the Earth’s surface radiation budget. Multiple clear-sky SULR estimation methods have been developed for high-spatial resolution satellite observations. Here, we comprehensively evaluated six SULR estimation methods, including the temperature-emissivity physical methods with the input of the MYD11/MYD21 (TE-MYD11/TE-MYD21), the hybrid methods with top-of-atmosphere (TOA) linear/nonlinear/artificial neural network regressions (TOA-LIN/TOA-NLIN/TOA-ANN), and the hybrid method with bottom-of-atmosphere (BOA) linear regression (BOA-LIN). The recently released MYD21 product and the BOA-LIN—a newly developed method that considers the spatial heterogeneity of the atmosphere—is used initially to estimate SULR. In addition, the four hybrid methods were compared with simulated datasets. All the six methods were evaluated using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Surface Radiation Budget Network (SURFRAD) in situ measurements. Simulation analysis shows that the BOA-LIN is the best one among four hybrid methods with accurate atmospheric profiles as input. Comparison of all the six methods shows that the TE-MYD21 performed the best, with a root mean square error (RMSE) and mean bias error (MBE) of 14.0 and −0.2 W/m2, respectively. The RMSE of BOA-LIN, TOA-NLIN, TOA-LIN, TOA-ANN, and TE-MYD11 are equal to 15.2, 16.1, 17.2, 21.2, and 18.5 W/m2, respectively. TE-MYD21 has a much better accuracy than the TE-MYD11 over barren surfaces (NDVI < 0.3) and a similar accuracy over non-barren surfaces (NDVI ≥ 0.3). BOA-LIN is more stable over varying water vapor conditions, compared to other hybrid methods. We conclude that this study provides a valuable reference for choosing the suitable estimation method in the SULR product generation.

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