scholarly journals Advances in Geostationary-Derived Longwave Fluxes for the CERES Synoptic (SYN1deg) Product

2016 ◽  
Vol 33 (3) ◽  
pp. 503-521 ◽  
Author(s):  
David R. Doelling ◽  
Moguo Sun ◽  
Le Trang Nguyen ◽  
Michele L. Nordeen ◽  
Conor O. Haney ◽  
...  

AbstractThe Clouds and the Earth’s Radiant Energy System (CERES) project has provided the climate community 15 years of globally observed top-of-the-atmosphere fluxes critical for climate and cloud feedback studies. To accurately monitor the earth’s radiation budget, the CERES instrument footprint fluxes must be spatially and temporally averaged properly. The CERES synoptic 1° (SYN1deg) product incorporates derived fluxes from the geostationary satellites (GEOs) to account for the regional diurnal flux variations in between Terra and Aqua CERES measurements. The Edition 4 CERES reprocessing effort has provided the opportunity to reevaluate the derivation of longwave (LW) fluxes from GEO narrowband radiances by examining the improvements from incorporating 1-hourly versus 3-hourly GEO data, additional GEO infrared (IR) channels, and multichannel GEO cloud properties. The resultant GEO LW fluxes need to be consistent across the 16-satellite climate data record. To that end, the addition of the water vapor channel, available on all GEOs, was more effective than using a reanalysis dataset’s column-weighted relative humidity combined with the window channel radiance. The benefit of the CERES LW angular directional model to derive fluxes was limited by the inconsistency of the GEO cloud retrievals. Greater success was found in the direct conversion of window and water vapor channel radiances into fluxes. Incorporating 1-hourly GEO fluxes had the greatest impact on improving the accuracy of high-temporal-resolution fluxes, and normalizing the GEO LW fluxes with CERES greatly reduced the monthly regional LW flux bias.

2020 ◽  
Vol 12 (6) ◽  
pp. 929 ◽  
Author(s):  
Nicolas Clerbaux ◽  
Tom Akkermans ◽  
Edward Baudrez ◽  
Almudena Velazquez Blazquez ◽  
William Moutier ◽  
...  

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.


2018 ◽  
Vol 31 (24) ◽  
pp. 10039-10058 ◽  
Author(s):  
Tyler J. Thorsen ◽  
Seiji Kato ◽  
Norman G. Loeb ◽  
Fred G. Rose

The Clouds and the Earth’s Radiant Energy System (CERES)–partial radiative perturbation [PRP (CERES-PRP)] methodology applies partial-radiative-perturbation-like calculations to observational datasets to directly isolate the individual cloud, atmospheric, and surface property contributions to the variability of the radiation budget. The results of these calculations can further be used to construct radiative kernels. A suite of monthly mean observation-based inputs are used for the radiative transfer, including cloud properties from either the diurnally resolved passive-sensor-based CERES synoptic (SYN) data or the combination of the CloudSat cloud radar and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO) lidar. The CloudSat/ CALIPSO cloud profiles are incorporated via a clustering method that obtains monthly mean cloud properties suitable for accurate radiative transfer calculations. The computed fluxes are validated using the TOA fluxes observed by CERES. Applications of the CERES-PRP methodology are demonstrated by computing the individual contributions to the variability of the radiation budget over multiple years and by deriving water vapor radiative kernels. The calculations for the former are used to show that an approximately linear decomposition of the total flux anomalies is achieved. The observation-based water vapor kernels were used to investigate the accuracy of the GCM-based NCAR CAM3.0 water vapor kernel. Differences between our observation-based kernel and the NCAR one are marginally larger than those inferred by previous comparisons among different GCM kernels.


2020 ◽  
Vol 12 (12) ◽  
pp. 1950
Author(s):  
Seiji Kato ◽  
David A. Rutan ◽  
Fred G. Rose ◽  
Thomas E. Caldwell ◽  
Seung-Hee Ham ◽  
...  

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.


2013 ◽  
Vol 30 (6) ◽  
pp. 1072-1090 ◽  
Author(s):  
David R. Doelling ◽  
Norman G. Loeb ◽  
Dennis F. Keyes ◽  
Michele L. Nordeen ◽  
Daniel Morstad ◽  
...  

Abstract The Clouds and the Earth’s Radiant Energy System (CERES) instruments on board the Terra and Aqua spacecraft continue to provide an unprecedented global climate record of the earth’s top-of-atmosphere (TOA) energy budget since March 2000. A critical step in determining accurate daily averaged flux involves estimating the flux between CERES Terra or Aqua overpass times. CERES employs the CERES-only (CO) and the CERES geostationary (CG) temporal interpolation methods. The CO method assumes that the cloud properties at the time of the CERES observation remain constant and that it only accounts for changes in albedo with solar zenith angle and diurnal land heating, by assuming a shape for unresolved changes in the diurnal cycle. The CG method enhances the CERES data by explicitly accounting for changes in cloud and radiation between CERES observation times using 3-hourly imager data from five geostationary (GEO) satellites. To maintain calibration traceability, GEO radiances are calibrated against Moderate Resolution Imaging Spectroradiometer (MODIS) and the derived GEO fluxes are normalized to the CERES measurements. While the regional (1° latitude × 1° longitude) monthly-mean difference between the CG and CO methods can exceed 25 W m−2 over marine stratus and land convection, these regional biases nearly cancel in the global mean. The regional monthly CG shortwave (SW) and longwave (LW) flux uncertainty is reduced by 20%, whereas the daily uncertainty is reduced by 50% and 20%, respectively, over the CO method, based on comparisons with 15-min Geostationary Earth Radiation Budget (GERB) data.


2020 ◽  
Vol 12 (17) ◽  
pp. 2787
Author(s):  
Mohan Shankar ◽  
Wenying Su ◽  
Natividad Manalo-Smith ◽  
Norman G. Loeb

The Clouds and the Earth’s Radiant Energy System (CERES) instruments have enabled the generation of a multi-decadal Earth radiation budget (ERB) climate data record (CDR) at the top of the Earth’s atmosphere, within the atmosphere, and at the Earth’s surface. Six CERES instruments have been launched over the course of twenty years, starting in 1999. To seamlessly continue the data record into the future, there is a need to radiometrically scale observations from newly launched instruments to observations from the existing data record. In this work, we describe a methodology to place the CERES Flight Model (FM) 5 instrument on the Suomi National Polar-orbiting Partnership (SNPP) spacecraft on the same radiometric scale as the FM3 instrument on the Aqua spacecraft. We determine the required magnitude of radiometric scaling by using spatially and temporally matched observations from these two instruments and describe the process to radiometrically scale SNPP/FM5 to Aqua/FM3 through the instrument spectral response functions. We also present validation results after application of this radiometric scaling and demonstrate the long-term consistency of the SNPP/FM5 record in comparison with the CERES instruments on Aqua and Terra.


2016 ◽  
Vol 29 (21) ◽  
pp. 7703-7722 ◽  
Author(s):  
Allison B. Marquardt Collow ◽  
Mark A. Miller

Abstract Changes in the climate system of the Amazon rain forest of Brazil can impact factors that influence the radiation budget such as clouds, atmospheric moisture, and the surface albedo. This study examines the relationships between clouds and radiation in this region using surface observations from the first year of the deployment of the Atmospheric Radiation Measurement (ARM) Program’s Mobile Facility 1 (AMF1) in Manacapuru, Brazil, and satellite measurements from the Clouds and the Earth’s Radiant Energy System (CERES). The seasonal cycles of the radiation budget and cloud radiative effects (CREs) are evaluated at the top of the atmosphere (TOA), at the surface, and within the atmospheric column using these observations and are placed into a regional context using the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Water vapor and clouds are abundant throughout the year, even though slight decreases are observed in the dry season. The column water vapor load is large enough that the longwave radiative flux divergence is nearly constant throughout the year. Clouds produce a significant shortwave CRE at the surface and TOA, exceeding 200 W m−2 during the wet season. Discrepancies, especially in column shortwave radiative absorption, between the observations and MERRA-2 are demonstrated that warrant additional analysis of the microphysical and macrophysical cloud properties in MERRA-2. More trustworthy fields in the MERRA-2 product suggest that the expansive nearby river system impacts the regional radiation budget and thereby renders AMF1 observations potentially biased relative to regions farther removed from rivers within the Amazon rain forest.


2020 ◽  
Vol 77 (2) ◽  
pp. 551-581
Author(s):  
Seung-Hee Ham ◽  
Seiji Kato ◽  
Fred G. Rose

Abstract Shortwave irradiance biases due to two- and four-stream approximations have been studied for the last couple of decades, but biases in estimating Earth’s radiation budget have not been examined in earlier studies. To quantify biases in diurnally averaged irradiances, we integrate the two- and four-stream biases using realistic diurnal variations of cloud properties from Clouds and the Earth’s Radiant Energy System (CERES) synoptic (SYN) hourly product. Three approximations are examined in this study: delta-two-stream-Eddington (D2strEdd), delta-two-stream-quadrature (D2strQuad), and delta-four-stream-quadrature (D4strQuad). Irradiances computed by the Discrete Ordinate Radiative Transfer model (DISORT) and Monte Carlo (MC) methods are used as references. The MC noises are further examined by comparing with DISORT results. When the biases are integrated with one day of solar zenith angle variation, regional biases of D2strEdd and D2strQuad reach up to 8 W m−2, while biases of D4strQuad reach up to 2 W m−2. When the biases are further averaged monthly or annually, regional biases of D2strEdd and D2strQuad can reach −1.5 W m−2 in SW top-of-atmosphere (TOA) upward irradiances and +3 W m−2 in surface downward irradiances. In contrast, regional biases of D4strQuad are within +0.9 for TOA irradiances and −1.2 W m−2 for surface irradiances. Except for polar regions, monthly and annual global mean biases are similar, suggesting that the biases are nearly independent to season. Biases in SW heating rate profiles are up to −0.008 K day−1 for D2strEdd and −0.016 K day−1 for D2strQuad, while the biases of the D4strQuad method are negligible.


2021 ◽  
Author(s):  
Maria Z. Hakuba ◽  
Peter Pilewskie ◽  
Graeme Stephens ◽  

<p>The recently selected NASA mission Libera, named for the daughter of Ceres in Roman mythology, will provide continuity of the Clouds and the Earth’s Radiant Energy System (CERES) Earth radiation budget (ERB) observations from space.</p><p>Seamless extension of the ERB climate data record is achieved by acquiring integrated radiances over the CERES FM6-heritage broad spectral bands in the shortwave (0.3 to 5 μm), longwave (5 to 50 μm) and total (0.3 to beyond 100 μm). To gain deeper insight into shortwave energy deposition, Libera adds a split-shortwave band (0.7 to 5 μm) that allows to provide deeper insight into shortwave energy deposition.</p><p>Libera’s advanced detector technologies is based on vertically aligned black-carbon nanotubes with closed-loop electrical substitution radiometry to achieve radiometric uncertainty of approximately 0.2%. Additionally, a wide field-of-view camera is employed to provide scene context and explore pathways for separating future ERB missions from complex imagers.</p><p>This presentation will summarize Libera’s attributes and mission goals, as well as some of the applications of the camera radiances, and the role of the additional split-shortwave channel that splits the shortwave band into its visible and near-IR contributions. This split is vital for the better understanding of shortwave absorption, feedbacks, and planetary albedo variability. The hemispheric symmetry of planetary albedo, as observed by CERES, is not achieved by most state-of-the-art climate models and is associated with long-standing biases in circulation and cloud properties. We will exemplify the study of processes relevant to albedo symmetry by means of CMIP6 simulations that provide the visible and near-IR fluxes.</p>


2014 ◽  
Vol 31 (4) ◽  
pp. 843-859 ◽  
Author(s):  
Alok K. Shrestha ◽  
Seiji Kato ◽  
Takmeng Wong ◽  
David A. Rutan ◽  
Walter F. Miller ◽  
...  

Abstract The NOAA-9 Earth Radiation Budget Experiment (ERBE) scanner measured broadband shortwave, longwave, and total radiances from February 1985 through January 1987. These scanner radiances are reprocessed using the more recent Clouds and the Earth’s Radiant Energy System (CERES) unfiltering algorithm. The scene information, including cloud properties, required for reprocessing is derived using Advanced Very High Resolution Radiometer (AVHRR) data on board NOAA-9, while no imager data were used in the original ERBE unfiltering. The reprocessing increases the NOAA-9 ERBE scanner unfiltered longwave radiances by 1.4%–2.0% during daytime and 0.2%–0.3% during nighttime relative to those derived from the ERBE unfiltering algorithm. Similarly, the scanner unfiltered shortwave radiances increase by ~1% for clear ocean and land and decrease for all-sky ocean, land, and snow/ice by ~1%. The resulting NOAA-9 ERBE scanner unfiltered radiances are then compared with NOAA-9 nonscanner irradiances by integrating the ERBE scanner radiance over the nonscanner field of view. The comparison indicates that the integrated scanner radiances are larger by 0.9% for shortwave and 0.7% smaller for longwave. A sensitivity study shows that the one-standard-deviation uncertainties in the agreement are ±2.5%, ±1.2%, and ±1.8% for the shortwave, nighttime longwave, and daytime longwave irradiances, respectively. The NOAA-9 and ERBS nonscanner irradiances are also compared using 2 years of data. The comparison indicates that the NOAA-9 nonscanner shortwave, nighttime longwave, and daytime longwave irradiances are 0.3% larger, 0.6% smaller, and 0.4% larger, respectively. The longer observational record provided by the ERBS nonscanner plays a critical role in tying the CERES-like NOAA-9 ERBE scanner dataset from the mid-1980s to the present-day CERES scanner data record.


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