scholarly journals Comparisons of Clear-Sky Outgoing Far-IR Flux Inferred from Satellite Observations and Computed from the Three Most Recent Reanalysis Products

2013 ◽  
Vol 26 (2) ◽  
pp. 478-494 ◽  
Author(s):  
Xiuhong Chen ◽  
Xianglei Huang ◽  
Norman G. Loeb ◽  
Heli Wei
Keyword(s):  
Land Surface ◽  
Radiant Energy ◽  
Longwave Radiation ◽  
Precipitable Water ◽  
Energy System ◽  
High Elevation ◽  
Radiation Budget ◽  
Distribution Models ◽  
Atmospheric Infrared Sounder ◽  
Clear Sky

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.

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 Deriving clear-sky longwave spectral flux from spaceborne hyperspectral radiance measurements: a case study with AIRS observations

2016 ◽  
Vol 9 (12) ◽  
pp. 6013-6023 ◽  
Author(s):  
Xiuhong Chen ◽  
Xianglei Huang
Keyword(s):  
Radiant Energy ◽  
Longwave Radiation ◽  
Precipitable Water ◽  
Energy System ◽  
Lapse Rate ◽  
Spectral Interval ◽  
Atmospheric Infrared Sounder ◽  
Clear Sky ◽  
Spectral Flux

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.

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
Keyword(s):  
Radiant Energy ◽  
Longwave Radiation ◽  
Energy System ◽  
Atmospheric Infrared Sounder ◽  
Clear Sky ◽  
The Difference ◽  
Spectrally Resolved ◽  
Independent Assessment ◽  
Flight Model ◽  
Bound Estimation

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.

scholarly journals Developing Clear-Sky Flux Products for the Geostationary Earth Radiation Budget Experiment

2005 ◽  
Vol 44 (9) ◽  
pp. 1361-1374 ◽  
Author(s):  
J. M. Futyan ◽  
J. E. Russell
Keyword(s):  
Diurnal Cycle ◽  
Radiant Energy ◽  
Longwave Radiation ◽  
Energy System ◽  
Radiation Budget ◽  
Sampling Errors ◽  
Clear Sky ◽  
Temporal Sampling ◽  
Earth Radiation Budget ◽  
Earth Radiation

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.

scholarly journals Deriving clear-sky longwave spectral flux solely from hyperspectral radiance: a case study with AIRS observations

2016 ◽  
Author(s):  
Xiuhong Chen ◽  
Xianglei Huang
Keyword(s):  
Radiant Energy ◽  
Longwave Radiation ◽  
Energy System ◽  
Spectral Interval ◽  
Atmospheric Infrared Sounder ◽  
Clear Sky ◽  
Spectral Flux ◽  
The Mean ◽  
Climate Studies

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.

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 The Climate Monitoring SAF Outgoing Longwave Radiation from AVHRR

2020 ◽  
Vol 12 (6) ◽  
pp. 929 ◽  
Author(s):  
Nicolas Clerbaux ◽  
Tom Akkermans ◽  
Edward Baudrez ◽  
Almudena Velazquez Blazquez ◽  
William Moutier ◽  
...  
Keyword(s):  
Outgoing Longwave Radiation ◽  
Radiant Energy ◽  
Longwave Radiation ◽  
Energy System ◽  
Radiation Budget ◽  
Climate Data ◽  
Night Time ◽  
Cloud Properties ◽  
Climate Monitoring ◽  
Orbital Drift

Data from the Advanced Very High Resolution Radiometer (AVHRR) have been used to create several long-duration data records of geophysical variables describing the atmosphere and land and water surfaces. In the Climate Monitoring Satellite Application Facility (CM SAF) project, AVHRR data are used to derive the Cloud, Albedo, and Radiation (CLARA) climate data records of radiation components (i.a., surface albedo) and cloud properties (i.a., cloud cover). This work describes the methodology implemented for the additional estimation of the Outgoing Longwave Radiation (OLR), an important Earth radiation budget component, that is consistent with the other CLARA variables. A first step is the estimation of the instantaneous OLR from the AVHRR observations. This is done by regressions on a large database of collocated observations between AVHRR Channel 4 (10.8 µm) and 5 (12 µm) and the OLR from the Clouds and Earth’s Radiant Energy System (CERES) instruments. We investigate the applicability of this method to the first generation of AVHRR instrument (AVHRR/1) for which no Channel 5 observation is available. A second step concerns the estimation of daily and monthly OLR from the instantaneous AVHRR overpasses. This step is especially important given the changes in the local time of the observations due to the orbital drift of the NOAA satellites. We investigate the use of OLR in the ERA5 reanalysis to estimate the diurnal variation. The developed approach proves to be valuable to model the diurnal change in OLR due to day/night time warming/cooling over clear land. Finally, the resulting monthly mean AVHRR OLR product is intercompared with the CERES monthly mean product. For a typical configuration with one morning and one afternoon AVHRR observation, the Root Mean Square (RMS) difference with CERES monthly mean OLR is about 2 Wm−2 at 1° × 1° resolution. We quantify the degradation of the OLR product when only one AVHRR instrument is available (as is the case for some periods in the 1980s) and also the improvement when more instruments are available (e.g., using METOP-A, NOAA-15, NOAA-18, and NOAA-19 in 2012). The degradation of the OLR product from AVHRR/1 instruments is also quantified, which is done by “masking” the Channel 5 observations.

scholarly journals On the Use of Geophysical Parameters for the Top-of-Atmosphere Shortwave Clear-Sky Radiance-to-Flux Conversion in EarthCARE

2019 ◽  
Vol 36 (4) ◽  
pp. 717-732 ◽  
Author(s):  
F. Tornow ◽  
C. Domenech ◽  
J. Fischer
Keyword(s):  
Permutation Test ◽  
Climate Modeling ◽  
Radiant Energy ◽  
Energy System ◽  
Max Planck ◽  
Distribution Models ◽  
Dynamic Surface ◽  
Clear Sky ◽  
Fresh Snow ◽  
Bidirectional Reflectance Distribution

AbstractWe have investigated whether differences across Clouds and the Earth’s Radiant Energy System (CERES) top-of-atmosphere (TOA) clear-sky angular distribution models, estimated separately over regional (1° × 1° longitude–latitude) and temporal (monthly) bins above land, can be explained by geophysical parameters from Max Planck Institute Aerosol Climatology, version 1 (MAC-v1), ECMWF twentieth-century reanalysis (ERA-20C), and a MODIS bidirectional reflectance distribution function (BRDF)/albedo/nadir BRDF-adjusted reflectance (NBAR) Climate Modeling Grid (CMG) gap-filled products (MCD43GF) climatology. Our research aimed to dissolve binning and to isolate inherent properties or indicators of such properties, which govern the TOA radiance-to-flux conversion in the absence of clouds. We collocated over seven million clear-sky footprints from CERES Single Scanner Footprint (SSF), edition 4, data with above geophysical auxiliary data. Looking at data per surface type and per scattering direction—as perceived by the broadband radiometer (BBR) on board Earth Clouds, Aerosol and Radiation Explorer (EarthCARE)—we identified optimal subsets of geophysical parameters using two different methods: random forest regression followed by a permutation test and multiple linear regression combined with the genetic algorithm. Using optimal subsets, we then trained artificial neural networks (ANNs). Flux error standard deviations on unseen test data were on average 2.7–4.0 W m−2, well below the 10 W m−2 flux accuracy threshold defined for the mission, with the exception of footprints containing fresh snow. Dynamic surface types (i.e., fresh snow and sea ice) required simpler ANN input sets to guarantee mission-worthy flux estimates, especially over footprints consisting of several surface types.

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 A Supplementary Clear-Sky Snow and Ice Recognition Technique for CERES Level 2 Products

2013 ◽  
Vol 30 (3) ◽  
pp. 557-568 ◽  
Author(s):  
Alexander Radkevich ◽  
Konstantin Khlopenkov ◽  
David Rutan ◽  
Seiji Kato
Keyword(s):  
Confidence Intervals ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Data Series ◽  
Clear Sky ◽  
Multiple Thresholds ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Snow And Ice

Abstract Identification of clear-sky snow and ice is an important step in the production of cryosphere radiation budget products, which are used in the derivation of long-term data series for climate research. In this paper, a new method of clear-sky snow/ice identification for Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. The algorithm’s goal is to enhance the identification of snow and ice within the Clouds and the Earth’s Radiant Energy System (CERES) data after application of the standard CERES scene identification scheme. The input of the algorithm uses spectral radiances from five MODIS bands and surface skin temperature available in the CERES Single Scanner Footprint (SSF) product. The algorithm produces a cryosphere rating from an aggregated test: a higher rating corresponds to a more certain identification of the clear-sky snow/ice-covered scene. Empirical analysis of regions of interest representing distinctive targets such as snow, ice, ice and water clouds, open waters, and snow-free land selected from a number of MODIS images shows that the cryosphere rating of snow/ice targets falls into 95% confidence intervals lying above the same confidence intervals of all other targets. This enables recognition of clear-sky cryosphere by using a single threshold applied to the rating, which makes this technique different from traditional branching techniques based on multiple thresholds. Limited tests show that the established threshold clearly separates the cryosphere rating values computed for the cryosphere from those computed for noncryosphere scenes, whereas individual tests applied consequently cannot reliably identify the cryosphere for complex scenes.

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