scholarly journals Assessing Stability of CERES-FM3 Daytime Longwave Unfiltered Radiance with AIRS Radiances

2012 ◽  
Vol 29 (3) ◽  
pp. 375-381 ◽  
Author(s):  
Xianglei Huang ◽  
Norman G. Loeb ◽  
Huiwen Chuang

Abstract Clouds and the Earth’s Radiant Energy System (CERES) daytime longwave (LW) radiances are determined from the difference between a total (TOT) channel (0.3–200 μm) measurement and a shortwave (SW) channel (0.3–5 μm) measurement, while nighttime LW radiances are obtained directly from the TOT channel. This means that a drift in the SW channel or the SW portion of the TOT channel could impact the daytime longwave radiances, but not the nighttime ones. This study evaluates daytime and nighttime CERES LW radiances for a possible secular drift in CERES LW observations using spectral radiances observed by Atmospheric Infrared Sounder (AIRS). By examining the coincidental AIRS and CERES Flight Model 3 (FM3) measurements over the tropical clear-sky oceans for all of January and July months since 2005, a secular drift of about −0.11% yr−1 in the daytime CERES-FM3 longwave unfiltered radiance can be identified in the CERES Single Scanner Footprint (SSF) Edition 2 product. This provides an upper-bound estimation for the drift in daytime outgoing longwave radiation, which is approximately −0.323 W m−2 yr−1. This estimation is consistent with the independent assessment concluded by the CERES calibration team. Such secular drift has been greatly reduced in the latest CERES SSF Edition 3 product. Comparisons are conducted for the CERES window channel as well, and it shows essentially no drift. This study serves as a practical example illustrating how the measurements of spectrally resolved radiances can be used to help evaluate data products from other narrowband or broadband measurements.

2016 ◽  
Vol 9 (12) ◽  
pp. 6013-6023 ◽  
Author(s):  
Xiuhong Chen ◽  
Xianglei Huang

Abstract. Previous studies have shown that longwave (LW) spectral fluxes have unique merit in climate studies. Using Atmospheric Infrared Sounder (AIRS) radiances as a case study, this study presents an algorithm to derive the entire LW clear-sky spectral fluxes from spaceborne hyperspectral observations. No other auxiliary observations are needed in the algorithm. A clear-sky scene is identified using a three-step detection method. The identified clear-sky scenes are then categorized into different sub-scene types using information about precipitable water, lapse rate and surface temperature inferred from the AIRS radiances at six selected channels. A previously established algorithm is then used to invert AIRS radiances to spectral fluxes over the entire LW spectrum at 10 cm−1 spectral interval. Accuracy of the algorithms is evaluated against collocated Clouds and the Earth's Radiant Energy System (CERES) observations. For nadir-view observations, the mean difference between outgoing longwave radiation (OLR) derived by this algorithm and the collocated CERES OLR is 1.52 Wm−2 with a standard deviation of 2.46 Wm−2. When the algorithm is extended for viewing zenith angle up to 45°, the performance is comparable to that for nadir-view results.


2016 ◽  
Author(s):  
Xiuhong Chen ◽  
Xianglei Huang

Abstract. Previous studies have shown that longwave (LW) spectral fluxes have unique merit in climate studies. Using Atmospheric Infrared Sounder (AIRS) radiances as a case study, this study presents an algorithm to derive the entire LW clear-sky spectral fluxes solely from hyperspectral observations. No other auxiliary observations are needed in the algorithm. A clear-sky scene is identified using a three-step detection method. The identified clear-sky scenes are then categorized into different sub-scene types using AIRS radiances at six selected channels. A previously established algorithm is then used to invert AIRS radiances to spectral fluxes over the entire LW spectrum at 10 cm−1 spectral interval. Accuracy of the algorithms is evaluated against collocated Clouds and the Earth's Radiant Energy System (CERES) observations. For nadir-view observations, the mean difference between outgoing longwave radiation (OLR) derived by this algorithm and the collocated CERES OLR is 1.52 Wm−2 with a standard deviation of 2.46 Wm−2. When the algorithm is extended for viewing zenith angle up to 45°, the performance is comparable to that for nadir-view results.


2013 ◽  
Vol 26 (2) ◽  
pp. 478-494 ◽  
Author(s):  
Xiuhong Chen ◽  
Xianglei Huang ◽  
Norman G. Loeb ◽  
Heli Wei

Abstract The far-IR spectrum plays an important role in the earth’s radiation budget and remote sensing. The authors compare the near-global (80°S–80°N) outgoing clear-sky far-IR flux inferred from the collocated Atmospheric Infrared Sounder (AIRS) and Clouds and the Earth’s Radiant Energy System (CERES) observations in 2004 with the counterparts computed from reanalysis datasets subsampled along the same satellite trajectories. The three most recent reanalyses are examined: the ECMWF Interim Re-Analysis (ERA-Interim), NASA Modern-Era Retrospective Analysis for Research and Application (MERRA), and NOAA/NCEP Climate Forecast System Reanalysis (CFSR). Following a previous study by X. Huang et al., clear-sky spectral angular distribution models (ADMs) are developed for five of the CERES land surface scene types as well as for the extratropical oceans. The outgoing longwave radiation (OLR) directly estimated from the AIRS radiances using the authors’ algorithm agrees well with the OLR in the collocated CERES Single Satellite Footprint (SSF) dataset. The daytime difference is 0.96 ±2.02 W m−2, and the nighttime difference is 0.86 ±1.61 W m−2. To a large extent, the far-IR flux derived in this way agrees with those directly computed from three reanalyses. The near-global averaged differences between reanalyses and observations tend to be slightly positive (0.66%–1.15%) over 0–400 cm−1 and slightly negative (−0.89% to −0.44%) over 400–600 cm−1. For all three reanalyses, the spatial distributions of such differences show the largest discrepancies over the high-elevation areas during the daytime but not during the nighttime, suggesting discrepancies in the diurnal variation of such areas among different datasets. The composite differences with respect to temperature or precipitable water suggest large discrepancies for cold and humid scenes.


2020 ◽  
Author(s):  
Qi Zeng ◽  
Jie Cheng ◽  
Feng Yang

<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>


2005 ◽  
Vol 44 (9) ◽  
pp. 1361-1374 ◽  
Author(s):  
J. M. Futyan ◽  
J. E. Russell

Abstract This paper describes the planned processing of monthly mean and monthly mean diurnal cycle flux products for the Geostationary Earth Radiation Budget (GERB) experiment. The use of higher-spatial-resolution flux estimates based on multichannel narrowband imager data to improve clear-sky sampling is investigated. Significant improvements in temporal sampling are found, leading to reduced temporal sampling errors and less dependence on diurnal models for the monthly mean products. The reduction in temporal sampling errors is found to outweigh any spatial sampling errors that are introduced. The resulting flux estimates are used to develop an improved version of the half-sine model that is used for the diurnal interpolation of clear-sky longwave fluxes over land in the Earth Radiation Budget Experiment (ERBE) and Clouds and the Earth’s Radiant Energy System (CERES) missions. Maximum outgoing longwave radiation occurs from 45 min to 1.5 h after local noon for most of the GERB field of view. Use of the ERBE half-sine model for interpolation therefore results in significant distortion of the diurnal cycle shape. The model that is proposed here provides a well-constrained fit to the true diurnal shape, even for limited clear-sky sampling, making it suitable for use in the processing of both GERB and CERES second-generation monthly mean clear-sky data products.


2021 ◽  
Author(s):  
David Fillmore ◽  
David Rutan ◽  
Seiji Kato ◽  
Fred Rose ◽  
Thomas Caldwell

Abstract. Aerosol optical depths (AOD) used for the Edition 4.1 Clouds and the Earth’s Radiant Energy System (CERES) Synoptic (SYN1deg) are evaluated. AODs are derived from Moderate Resolution Imaging Spectroradiometer (MODIS) observations and assimilated by an aerosol transport model (MATCH). As a consequence, clear-sky AODs closely match with those derived from MODIS instruments. AODs under all-sky conditions are larger than AODs under clear-sky conditions, which is supported by ground-based AERONET observations. When all-sky MATCH AODs are compared with Modern-Era Retrospective Analysis for Research and Applications (MERRA2) AODs, MATCH AODs are generally larger than MERRA2 AODS especially over convective regions (e.g. Amazon, central Africa, and eastern Asia). The difference is largely caused by MODIS AODs used for assimilation. Including AODs with larger retrieval uncertainty makes AODs over the convective regions larger. When AODs are used for clear-sky irradiance computations and computed downward shortwave irradiances are compared with ground- based observations, the computed instantaneous irradiances are 1 % to 2 % larger than observed irradiances. The comparison of top-of-atmosphere clear-sky irradiances with those derived from CERES observations suggests that AODs used for surface radiation observation sites are larger by 0.01 to 0.03, which is within the uncertainty of instantaneous MODIS AODs. However, the comparison with AERONET AOD suggests AODs used for computations over desert sites are 0.08 larger. The cause of positive biases of downward shortwave irradiance and AODs for the desert sites are unknown.


2008 ◽  
Vol 25 (7) ◽  
pp. 1106-1117 ◽  
Author(s):  
N. Clerbaux ◽  
S. Dewitte ◽  
C. Bertrand ◽  
D. Caprion ◽  
B. De Paepe ◽  
...  

Abstract The method used to estimate the unfiltered longwave broadband radiance from the filtered radiances measured by the Geostationary Earth Radiation Budget (GERB) instrument is presented. This unfiltering method is used to generate the first released edition of the GERB-2 dataset. This method involves a set of regressions between the unfiltering factor (i.e., the ratio of the unfiltered and filtered broadband radiances) and the narrowband observations of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument. The regressions are theoretically derived from a large database of simulated spectral radiance curves obtained by radiative transfer computations. The generation of this database is fully described. Different sources of error that may affect the GERB unfiltering have been identified and the associated error magnitudes are assessed on the database. For most of the earth–atmosphere conditions, the error introduced during the unfiltering processes is well under 0.5% (RMS error of about 0.1%). For more confidence, the unfiltered radiances of GERB-2 are validated by cross comparison with collocated and coangular Clouds and the Earth’s Radiant Energy System (CERES) observations. The agreement between the unfiltered radiances is within the science goals (1% accuracy for GERB and 0.5% for CERES) for the Flight Model 2 (FM2). For the CERES Flight Model 3 (FM3) instrument, an overall difference of 1.8% is observed. The intercomparisons indicate some scene-type dependency, which is due to the unfiltering for the cloudy scenes. This should be corrected for subsequent editions of the database.


2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  

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.


2021 ◽  
Vol 13 (21) ◽  
pp. 4464
Author(s):  
Jiawen Xu ◽  
Xiaotong Zhang ◽  
Chunjie Feng ◽  
Shuyue Yang ◽  
Shikang Guan ◽  
...  

Surface upward longwave radiation (SULR) is an indicator of thermal conditions over the Earth’s surface. In this study, we validated the simulated SULR from 51 Coupled Model Intercomparison Project (CMIP6) general circulation models (GCMs) through a comparison with ground measurements and satellite-retrieved SULR from the Clouds and the Earth’s Radiant Energy System, Energy Balanced and Filled (CERES EBAF). Moreover, we improved the SULR estimations by a fusion of multiple CMIP6 GCMs using multimodel ensemble (MME) methods. Large variations were found in the monthly mean SULR among the 51 CMIP6 GCMs; the bias and root mean squared error (RMSE) of the individual CMIP6 GCMs at 133 sites ranged from −3 to 24 W m−2 and 22 to 38 W m−2, respectively, which were higher than those found between the CERES EBAF and GCMs. The CMIP6 GCMs did not improve the overestimation of SULR compared to the CMIP5 GCMs. The Bayesian model averaging (BMA) method showed better performance in simulating SULR than the individual GCMs and simple model averaging (SMA) method, with a bias of 0 W m−2 and an RMSE of 19.29 W m−2 for the 133 sites. In terms of the global annual mean SULR, our best estimation for the CMIP6 GCMs using the BMA method was 392 W m−2 during 2000–2014. We found that the SULR varied between 386 and 393 W m−2 from 1850 to 2014, exhibiting an increasing tendency of 0.2 W m−2 per decade (p < 0.05).


2016 ◽  
Vol 33 (12) ◽  
pp. 2679-2698 ◽  
Author(s):  
David R. Doelling ◽  
Conor O. Haney ◽  
Benjamin R. Scarino ◽  
Arun Gopalan ◽  
Rajendra Bhatt

AbstractThe Clouds and the Earth’s Radiant Energy System (CERES) project relies on geostationary imager–derived TOA broadband fluxes and cloud properties to account for the regional diurnal fluctuations between the Terra and Aqua CERES and MODIS measurements. The CERES project employs a ray-matching calibration algorithm in order to transfer the Aqua MODIS calibration to the geostationary (GEO) imagers, thereby allowing the derivation of consistent fluxes and cloud retrievals across the 16 GEO imagers utilized in the CERES record. The CERES Edition 4 processing scheme grants the opportunity to recalibrate the GEO record using an improved GEO/MODIS all-sky ocean ray-matching algorithm. Using a graduated angle matching method, which is most restrictive for anisotropic clear-sky ocean radiances and least restrictive for isotropic bright cloud radiances, reduces the bidirectional bias while preserving the dynamic range. Furthermore, SCIAMACHY hyperspectral radiances are used to account for both the solar incoming and Earth-reflected spectra in order to correct spectral band differences. As a result, the difference between the linear regression offset and the maintained GEO space count was reduced, and the calibration slopes computed from the linear fit and the regression through the space count agreed to within 0.4%. A deep convective cloud (DCC) ray-matching algorithm is also presented. The all-sky ocean and DCC ray-matching timeline gains are within 0.7% of one another. Because DCC are isotropic and the brightest, Earth targets with near-uniform visible spectra, the temporal standard error of GEO imager gains, are reduced by up to 60% from that of all-sky ocean targets.


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