scholarly journals Validation of the CERES Edition-4A Surface-Only Flux Algorithms

2020 ◽  
Vol 59 (2) ◽  
pp. 281-295 ◽  
Author(s):  
David P. Kratz ◽  
Shashi K. Gupta ◽  
Anne C. Wilber ◽  
Victor E. Sothcott
Keyword(s):  
Radiant Energy ◽  
Energy System ◽  
Surface Fluxes ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Random Errors ◽  
High Quality ◽  
Radiative Fluxes ◽  
Accuracy Requirement ◽  
Future Work

AbstractSurface radiative fluxes have been derived with the objective of supplementing top-of-atmosphere (TOA) radiative fluxes being measured under NASA’s Clouds and the Earth’s Radiant Energy System (CERES) project. This has been accomplished by using combinations of CERES TOA measurements, parameterized radiative transfer algorithms, and high-quality meteorological datasets available from reanalysis projects. Current CERES footprint-level products include surface fluxes derived from two shortwave (SW) and three longwave (LW) algorithms designated as SW models A and B and LW models A, B, and C. The SW and LW models A work for clear conditions only; the other models work for both clear and cloudy conditions. The current CERES Edition-4A computed surface fluxes from all models are validated against ground-based flux measurements from high-quality surface networks like the Baseline Surface Radiation Network and NOAA’s Surface Radiation Budget Network (SURFRAD). Validation results as systematic and random errors are provided for all models, separately for five different surface types and combined for all surface types as tables and scatterplots. Validation of surface fluxes is now a part of CERES processing and is used to continually improve the above algorithms. Since both models B work for clear and cloudy conditions alike and meet the accuracy requirement, their results are considered to be the most reliable and most likely to be retained for future work. Both models A have limited use given that they work for clear skies only. Models B will continue to undergo further improvement as more validation results become available.

scholarly journals Top-of-Atmosphere Direct Radiative Effect of Aerosols over Global Oceans from Merged CERES and MODIS Observations

2005 ◽  
Vol 18 (17) ◽  
pp. 3506-3526 ◽  
Author(s):  
Norman G. Loeb ◽  
Natividad Manalo-Smith
Keyword(s):  
Information Service ◽  
Radiant Energy ◽  
Energy System ◽  
Surface Fluxes ◽  
Radiative Effect ◽  
Distribution Models ◽  
Radiative Fluxes ◽  
Clear Sky ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Global Oceans

Abstract The direct radiative effect of aerosols (DREA) is defined as the difference between radiative fluxes in the absence and presence of aerosols. In this study, the direct radiative effect of aerosols is estimated for 46 months (March 2000–December 2003) of merged Clouds and the Earth’s Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) Terra global measurements over ocean. This analysis includes the contribution from clear regions in both clear and partly cloudy CERES footprints. MODIS–CERES narrow-to-broadband regressions are developed to convert clear-sky MODIS narrowband radiances to broadband shortwave (SW) radiances, and CERES clear-sky angular distribution models (ADMs) are used to estimate the corresponding top-of-atmosphere (TOA) radiative fluxes that are needed to determine the DREA. Clear-sky MODIS pixels are identified using two independent cloud masks: (i) the NOAA/National Environmental Satellite, Data, and Information Service (NESDIS) algorithm that is used for inferring aerosol properties from MODIS on the CERES Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product (NOAA SSF); and (ii) the standard algorithm that is used by the MODIS aerosol group to produce the MODIS aerosol product (MOD04). Over global oceans, direct radiative cooling by aerosols for clear scenes that are identified from MOD04 is estimated to be 40% larger than for clear scenes from NOAA SSF (5.5 compared to 3.8 W m−2). Regionally, differences are largest in areas that are affected by dust aerosol, such as oceanic regions that are adjacent to the Sahara and Saudi Arabian deserts, and in northern Pacific Ocean regions that are influenced by dust transported from Asia. The net total-sky (clear and cloudy) DREA is negative (cooling) and is estimated to be −2.0 W m−2 from MOD04, and −1.6 W m−2 from NOAA SSF. The DREA is shown to have pronounced seasonal cycles in the Northern Hemisphere and large year-to-year fluctuations near deserts. However, no systematic trend in deseasonalized anomalies of the DREA is observed over the 46-month time series that is considered.

scholarly journals Uncertainty in Satellite-Derived Surface Irradiances and Challenges in Producing Surface Radiation Budget Climate Data Record

2020 ◽  
Vol 12 (12) ◽  
pp. 1950
Author(s):  
Seiji Kato ◽  
David A. Rutan ◽  
Fred G. Rose ◽  
Thomas E. Caldwell ◽  
Seung-Hee Ham ◽  
...  
Keyword(s):  
Sensible Heat Flux ◽  
Radiant Energy ◽  
Energy System ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Climate Data ◽  
Surface Irradiance ◽  
Uncertainty Estimates ◽  
The Difference ◽  
Global Mean

The Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Edition 4.1 data product provides global surface irradiances. Uncertainties in the global and regional monthly and annual mean all-sky net shortwave, longwave, and shortwave plus longwave (total) irradiances are estimated using ground-based observations. Error covariance is derived from surface irradiance sensitivity to surface, atmospheric, cloud and aerosol property perturbations. Uncertainties in global annual mean net shortwave, longwave, and total irradiances at the surface are, respectively, 5.7 Wm−2, 6.7 Wm−2, and 9.7 Wm−2. In addition, the uncertainty in surface downward irradiance monthly anomalies and their trends are estimated based on the difference derived from EBAF surface irradiances and observations. The uncertainty in the decadal trend suggests that when differences of decadal global mean downward shortwave and longwave irradiances are, respectively, greater than 0.45 Wm−2 and 0.52 Wm−2, the difference is larger than 1σ uncertainties. However, surface irradiance observation sites are located predominately over tropical oceans and the northern hemisphere mid-latitude. As a consequence, the effect of a discontinuity introduced by using multiple geostationary satellites in deriving cloud properties is likely to be excluded from these trend and decadal change uncertainty estimates. Nevertheless, the monthly anomaly timeseries of radiative cooling in the atmosphere (multiplied by −1) agrees reasonably well with the anomaly time series of diabatic heating derived from global mean precipitation and sensible heat flux with a correlation coefficient of 0.46.

Validation of Clear-Sky Global LAnd Surface Satellite (GLASS) Longwave Radiation Product

2020 ◽  
Author(s):  
Qi Zeng ◽  
Jie Cheng ◽  
Feng Yang
Keyword(s):  
Land Surface ◽  
Water Cycle ◽  
Radiant Energy ◽  
Remote Sensing Data ◽  
Longwave Radiation ◽  
Energy System ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Clear Sky ◽  
Global Land

<p>Surface longwave (LW) radiation plays an important rolein global climatic change, which is consist of surface longwave upward radiation (LWUP), surface longwave downward radiation (LWDN) and surface longwave net radiation (LWNR). Numerous studies have been carried out to estimate LWUP or LWDN from remote sensing data, and several satellite LW radiation products have been released, such as the International Satellite Cloud Climatology Project‐Flux Data (ISCCP‐FD), the Global Energy and Water cycle Experiment‐Surface Radiation Budget (GEWEX‐SRB) and the Clouds and the Earth’s Radiant Energy System‐Gridded Radiative Fluxes and Clouds (CERES‐FSW). But these products share the common features of coarse spatial resolutions (100-280 km) and lower validation accuracy.</p><p>Under such circumstance, we developed the methods of estimating long-term high spatial resolution all sky  instantaneous LW radiation, and produced the corresponding products from MODIS data from 2000 through 2018 (Terra and Aqua), named as Global LAnd Surface Satellite (GLASS) Longwave Radiation product, which can be free freely downloaded from the website (http://glass.umd.edu/Download.html).</p><p>In this article, ground measurements collected from 141 sites in six independent networks (AmerciFlux, AsiaFlux, BSRN, CEOP, HiWATER-MUSOEXE and TIPEX-III) are used to evaluate the clear-sky GLASS LW radiation products at global scale. The bias and RMSE is -4.33 W/m<sup>2 </sup>and 18.15 W/m<sup>2 </sup>for LWUP, -3.77 W/m<sup>2 </sup>and 26.94 W/m<sup>2</sup> for LWDN, and 0.70 W/m<sup>2 </sup>and 26.70 W/m<sup>2</sup> for LWNR, respectively. Compared with validation results of the above mentioned three LW radiation products, the overall accuracy of GLASS LW radiation product is much better. We will continue to improve the retrieval algorithms and update the products accordingly.</p>

scholarly journals Two MODIS Aerosol Products over Ocean on the Terra and Aqua CERES SSF Datasets

2005 ◽  
Vol 62 (4) ◽  
pp. 1008-1031 ◽  
Author(s):  
Alexander Ignatov ◽  
Patrick Minnis ◽  
Norman Loeb ◽  
Bruce Wielicki ◽  
Walter Miller ◽  
...  
Keyword(s):  
Single Channel ◽  
Radiant Energy ◽  
Cloud Amount ◽  
Energy System ◽  
Poor Quality ◽  
Radiation Budget ◽  
Quality Data ◽  
Radiative Fluxes ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Impact

Abstract Understanding the impact of aerosols on the earth’s radiation budget and the long-term climate record requires consistent measurements of aerosol properties and radiative fluxes. The Clouds and the Earth’s Radiant Energy System (CERES) Science Team combines satellite-based retrievals of aerosols, clouds, and radiative fluxes into Single Scanner Footprint (SSF) datasets from the Terra and Aqua satellites. Over ocean, two aerosol products are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) using different sampling and aerosol algorithms. The primary, or M, product is taken from the standard multispectral aerosol product developed by the MODIS aerosol group while a simpler, secondary [Advanced Very High Resolution Radiometer (AVHRR) like], or A, product is derived by the CERES Science Team using a different cloud clearing method and a single-channel aerosol algorithm. Two aerosol optical depths (AOD), τA1 and τA2, are derived from MODIS bands 1 (0.644 μm) and 6 (1.632 μm) resembling the AVHRR/3 channels 1 and 3A, respectively. On Aqua the retrievals are made in band 7 (2.119 μm) because of poor quality data from band 6. The respective Ångström exponents can be derived from the values of τ. The A product serves as a backup for the M product. More importantly, the overlap of these aerosol products is essential for placing the 20+ year heritage AVHRR aerosol record in the context of more advanced aerosol sensors and algorithms such as that used for the M product. This study documents the M and A products, highlighting their CERES SSF specifics. Based on 2 weeks of global Terra data, coincident M and A AODs are found to be strongly correlated in both bands. However, both domains in which the M and A aerosols are available, and the respective τ/α statistics significantly differ because of discrepancies in sampling due to differences in cloud and sun-glint screening. In both aerosol products, correlation is observed between the retrieved aerosol parameters (τ/α) and ambient cloud amount, with the dependence in the M product being more pronounced than in the A product.

scholarly journals Validation of the CERES Edition 2B Surface-Only Flux Algorithms

2010 ◽  
Vol 49 (1) ◽  
pp. 164-180 ◽  
Author(s):  
David P. Kratz ◽  
Shashi K. Gupta ◽  
Anne C. Wilber ◽  
Victor E. Sothcott
Keyword(s):  
Meteorological Data ◽  
High Surface ◽  
Radiant Energy ◽  
Energy System ◽  
Systematic Errors ◽  
Surface Fluxes ◽  
Random Errors ◽  
Radiative Forcings ◽  
Climate Research ◽  
Clear Sky

Abstract The Clouds and the Earth’s Radiant Energy System (CERES) project uses two shortwave (SW) and two longwave (LW) algorithms to derive surface radiative fluxes on an instantaneous footprint basis from a combination of top-of-atmosphere fluxes, ancillary meteorological data, and retrieved cloud properties. Since the CERES project examines the radiative forcings and feedbacks for Earth’s entire climate system, validation of these models for a wide variety of surface conditions is paramount. The present validation effort focuses upon the ability of these surface-only flux algorithms to produce accurate CERES Edition 2B single scanner footprint data from the Terra and Aqua spacecraft measurements. To facilitate the validation process, high-quality radiometric surface observations have been acquired that were coincident with the CERES-derived surface fluxes. For both SW models, systematic errors range from −20 to −12 W m−2 (from −2.8% to −1.6%) for global clear-sky cases, while for the all-sky SW model, the systematic errors range from 14 to 21 W m−2 (3.2%–4.8%) for global cloudy-sky cases. Larger systematic errors were seen for the individual surface types, and significant random errors where observed, especially for cloudy-sky cases. While the SW models nearly achieved the 20 W m−2 accuracy requirements established for climate research, further improvements are warranted. For the clear-sky LW model, systematic errors were observed to fall within ±5.4 W m−2 (±1.9%) except for the polar case in which systematic errors on the order from −15 to −11 W m−2 (from −13% to −7.2%) occurred. For the all-sky LW model, systematic errors were less than ±9.2 W m−2 (±7.6%) for both the clear-sky and cloudy-sky cases. The random errors were less than 17 W m−2 (6.2%) for clear-sky cases and 28 W m−2 (13%) for cloudy-sky cases, except for the desert cases in which very high surface skin temperatures caused an overestimation in the model-calculated surface fluxes. Overall, however, the LW models met the accuracy requirements for climate research.

Constraints on Climate Sensitivity from Radiation Patterns in Climate Models

2011 ◽  
Vol 24 (4) ◽  
pp. 1034-1052 ◽  
Author(s):  
Markus Huber ◽  
Irina Mahlstein ◽  
Martin Wild ◽  
John Fasullo ◽  
Reto Knutti
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Climate Models ◽  
Radiant Energy ◽  
Carbon Dioxide Concentration ◽  
Energy System ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Radiation Patterns ◽  
Strong Constraint

Abstract The estimated range of climate sensitivity, the equilibrium warming resulting from a doubling of the atmospheric carbon dioxide concentration, has not decreased substantially in past decades. New statistical methods for estimating the climate sensitivity have been proposed and provide a better quantification of relative probabilities of climate sensitivity within the almost canonical range of 2–4.5 K; however, large uncertainties remain, in particular for the upper bound. Simple indices of spatial radiation patterns are used here to establish a relationship between an observable radiative quantity and the equilibrium climate sensitivity. The indices are computed for the Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel dataset and offer a possibility to constrain climate sensitivity by considering radiation patterns in the climate system. High correlations between the indices and climate sensitivity are found, for example, in the cloud radiative forcing of the incoming longwave surface radiation and in the clear-sky component of the incoming surface shortwave flux, the net shortwave surface budget, and the atmospheric shortwave attenuation variable β. The climate sensitivity was estimated from the mean of the indices during the years 1990–99 for the CMIP3 models. The surface radiative flux dataset from the Clouds and the Earth’s Radiant Energy System (CERES) together with its top-of-atmosphere Energy Balanced and Filled equivalent (CERES EBAF) are used as a reference observational dataset, resulting in a best estimate for climate sensitivity of 3.3 K with a likely range of 2.7–4.0 K. A comparison with other satellite and reanalysis datasets show similar likely ranges and best estimates of 1.7–3.8 (3.3 K) [Earth Radiation Budget Experiment (ERBE)], 2.9–3.7 (3.3 K) [International Satellite Cloud Climatology Project radiative surface flux data (ISCCP-FD)], 2.8–4.1 (3.5 K) [NASA’s Modern Era Retrospective-Analysis for Research and Application (MERRA)], 3.0–4.2 (3.6 K) [Japanese 25-yr Reanalysis (JRA-25)], 2.7–3.9 (3.4 K) [European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-Interim)], 3.0–4.0 (3.5 K) [ERA-40], and 3.1–4.7 (3.6 K) for the NCEP reanalysis. For each individual reference dataset, the results suggest that values for the sensitivity below 1.7 K are not likely to be consistent with observed radiation patterns given the structure of current climate models. For the aggregation of the reference datasets, the climate sensitivity is not likely to be below 2.9 K within the framework of this study, whereas values exceeding 4.5 K cannot be excluded from this analysis. While these ranges cannot be interpreted properly in terms of probability, they are consistent with other estimates of climate sensitivity and reaffirm that the current climatology provides a strong constraint on the lower bound of climate sensitivity even in a set of structurally different models.

Evaluation of net shortwave radiation over China with a regional climate model

2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Monsoon Region ◽  
Clear Sky ◽  
Sky Conditions

The regional climate model RegCM version 4.6, developed by the European Centre for Medium-Range Weather Forecasts Reanalysis, was used to simulate the radiation budget over China. Clouds and the Earth’s Radiant Energy System (CERES) satellite data were utilized to evaluate the simulation results based on 4 radiative components: net shortwave (NSW) radiation at the surface of the earth and top of the atmosphere (TOA) under all-sky and clear-sky conditions. The performance of the model for low-value areas of NSW was superior to that for high-value areas. NSW at the surface and TOA under all-sky conditions was significantly underestimated; the spatial distribution of the bias was negative in the north and positive in the south, bounded by 25°N for the annual and seasonal averaged difference maps. Compared with the all-sky condition, the simulation effect under clear-sky conditions was significantly better, which indicates that the cloud fraction is the key factor affecting the accuracy of the simulation. In particular, the bias of the TOA NSW under the clear-sky condition was <±10 W m-2 in the eastern areas. The performance of the model was better over the eastern monsoon region in winter and autumn for surface NSW under clear-sky conditions, which may be related to different levels of air pollution during each season. Among the 3 areas, the regional average biases overall were largest (negative) over the Qinghai-Tibet alpine region and smallest over the eastern monsoon region.

scholarly journals A 16-year dataset (2000–2015) of high-resolution (3 h, 10 km) global surface solar radiation

2019 ◽  
Vol 11 (4) ◽  
pp. 1905-1915 ◽  
Author(s):  
Wenjun Tang ◽  
Kun Yang ◽  
Jun Qin ◽  
Xin Li ◽  
Xiaolei Niu
Keyword(s):  
High Resolution ◽  
Solar Radiation ◽  
Radiant Energy ◽  
Reanalysis Data ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Mean Bias Error ◽  
Bias Error ◽  
Surface Solar Radiation ◽  
Global Surface

Abstract. The recent release of the International Satellite Cloud Climatology Project (ISCCP) HXG cloud products and new ERA5 reanalysis data enabled us to produce a global surface solar radiation (SSR) dataset: a 16-year (2000–2015) high-resolution (3 h, 10 km) global SSR dataset using an improved physical parameterization scheme. The main inputs were cloud optical depth from ISCCP-HXG cloud products; the water vapor, surface pressure and ozone from ERA5 reanalysis data; and albedo and aerosol from Moderate Resolution Imaging Spectroradiometer (MODIS) products. The estimated SSR data were evaluated against surface observations measured at 42 stations of the Baseline Surface Radiation Network (BSRN) and 90 radiation stations of the China Meteorological Administration (CMA). Validation against the BSRN data indicated that the mean bias error (MBE), root mean square error (RMSE) and correlation coefficient (R) for the instantaneous SSR estimates at 10 km scale were −11.5 W m−2, 113.5 W m−2 and 0.92, respectively. When the estimated instantaneous SSR data were upscaled to 90 km, its error was clearly reduced, with RMSE decreasing to 93.4 W m−2 and R increasing to 0.95. For daily SSR estimates at 90 km scale, the MBE, RMSE and R at the BSRN were −5.8 W m−2, 33.1 W m−2 and 0.95, respectively. These error metrics at the CMA radiation stations were 2.1 W m−2, 26.9 W m−2 and 0.95, respectively. Comparisons with other global satellite radiation products indicated that our SSR estimates were generally better than those of the ISCCP flux dataset (ISCCP-FD), the global energy and water cycle experiment surface radiation budget (GEWEX-SRB), and the Earth's Radiant Energy System (CERES). Our SSR dataset will contribute to the land-surface process simulations and the photovoltaic applications in the future. The dataset is available at  https://doi.org/10.11888/Meteoro.tpdc.270112 (Tang, 2019).

Cloud effects on surface radiation balance at Helheim and Jakobshavn Glaciers (Greenland) using ground-based observations 

2021 ◽  
Author(s):  
Georges Djoumna ◽  
Sebastian H. Mernild ◽  
David Holland
Keyword(s):  
Short Wave ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Wave Radiation ◽  
Radiation Balance ◽  
Short Wave Radiation ◽  
Radiative Fluxes ◽  
Long Wave ◽  
Transmittance Factor ◽  
Cloud Metrics

&lt;p&gt;The surface radiation budget is an essential component of the total energy exchange between the atmosphere and the Earth&amp;#8217;s surface. Measurements of radiative fluxes near/on ice surfaces are sparse in the polar regions, including on the Greenland Ice Sheet (GrIS), and the effects of cloud on radiative fluxes are still poorly studied. In this work, we assess the impacts of cloud on radiative fluxes using two metrics: the longwave-equivalent cloudiness, derived from long-wave radiation measurements, and the cloud transmittance factor, obtained from short-wave radiation. The metrics are applied to radiation data from two automatic weather stations located over the bare ground near the ice front of Helheim (HG) and Jakobshavn Isbr&amp;#230; (JI) on the GrIS. Comparisons of meteorological parameters, surface radiation fluxes, and cloud metrics show significant differences between the two sites. The cloud transmittance factor is higher at HG than at JI, and the incoming short-wave radiation in the summer at HG is 50.0 W m&amp;#8722;2 larger than at JI. Cloud metrics derived at the two sites reveal&amp;#160; &amp;#160;a high dependency on the wind direction. The total cloud radiative effect (CREnet) generally increases during melt season at the two stations due to long-wave CRE enhancement by cloud fraction.&amp;#160;&amp;#160;CREnet decreases from May to June and increases afterward, due to the strengthened short-wave CRE. The annually averaged CREnet were 3.0 &amp;#177; 7.4 W m-2 and 1.9 &amp;#177; 15.1 W m&amp;#8722;2 at JI and HG.&amp;#160; CREnet estimated from AWS indicates that clouds cool the JI and HG during melt season at different rates.&lt;/p&gt;

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