Estimation of Near-Real-Time Outgoing Longwave Radiation from Cross-Track Infrared Sounder (CrIS) Radiance Measurements

2017 ◽  
Vol 34 (3) ◽  
pp. 643-655 ◽  
Author(s):  
Kexin Zhang ◽  
Mitchell D. Goldberg ◽  
Fengying Sun ◽  
Lihang Zhou ◽  
Walter W. Wolf ◽  
...  
Keyword(s):  
Real Time ◽  
Outgoing Longwave Radiation ◽  
Radiant Energy ◽  
Longwave Radiation ◽  
Energy System ◽  
Regression Coefficients ◽  
Radiation Budget ◽  
Least Squares Regression ◽  
Time Basis ◽  
Cross Track

AbstractThis study describes the algorithm for deriving near-real-time outgoing longwave radiation (OLR) from Cross-Track Infrared Sounder (CrIS) hyperspectral infrared sounder radiance measurements. The estimation of OLR on a near-real-time basis provides a unique perspective for studying the variability of Earth’s current atmospheric radiation budget. CrIS-derived OLR values are estimated as a weighted linear combination of CrIS-adjusted “pseudochannel” radiances. The algorithm uses the Atmospheric Infrared Sounder (AIRS) as the transfer instrument, and a least squares regression algorithm is applied to generate two sets of regression coefficients. The first set of regression coefficients is derived from collocated Clouds and the Earth’s Radiant Energy System (CERES) OLR on Aqua and pseudochannel radiances calculated from AIRS radiances. The second set of coefficients is derived to adjust the CrIS pseudochannel radiance to account for the differences in pseudochannel radiances between AIRS and CrIS. The CrIS-derived OLR is then validated by using a limited set of available CERES SNPP OLR observations over 1° × 1° global grids, as well as monthly OLR mean and interannual differences against CERES OLR datasets from SNPP and Aqua. The results show that the bias of global CrIS OLR estimation is within ±2 W m−2 and that the standard deviation is within 5 W m−2 for all conditions, and ±1 and 3 W m−2 for homogeneous scenes. The interannual CrIS-derived OLR differences agree well with Aqua CERES interannual OLR differences on a 1° × 1° spatial scale, with only a small drift of the global mean of these two datasets of around 0.004 W m−2.

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 Decadal Changes of Earth’s Outgoing Longwave Radiation

2018 ◽  
Vol 10 (10) ◽  
pp. 1539 ◽  
Author(s):  
Steven Dewitte ◽  
Nicolas Clerbaux
Keyword(s):  
Outgoing Longwave Radiation ◽  
Radiant Energy ◽  
Longwave Radiation ◽  
Energy System ◽  
Radiation Budget ◽  
The Arctic ◽  
Regional Patterns ◽  
The Earth ◽  
Earth Radiation Budget ◽  
Earth Radiation

The Earth Radiation Budget (ERB) at the top of the atmosphere quantifies how the earth gains energy from the sun and loses energy to space. Its monitoring is of fundamental importance for understanding ongoing climate change. In this paper, decadal changes of the Outgoing Longwave Radiation (OLR) as measured by the Clouds and Earth’s Radiant Energy System from 2000 to 2018, the Earth Radiation Budget Experiment from 1985 to 1998, and the High-resolution Infrared Radiation Sounder from 1985 to 2018 are analysed. The OLR has been rising since 1985, and correlates well with the rising global temperature. An observational estimate of the derivative of the OLR with respect to temperature of 2.93 +/− 0.3 W/m 2 K is obtained. The regional patterns of the observed OLR change from 1985–2000 to 2001–2017 show a warming pattern in the Northern Hemisphere in particular in the Arctic, as well as tropical cloudiness changes related to a strengthening of La Niña.

scholarly journals Validation of Near-Real-Time NOAA-20 CrIS Outgoing Longwave Radiation with Multi-Satellite Datasets on Broad Timescales

2021 ◽  
Vol 13 (19) ◽  
pp. 3912
Author(s):  
Tianyuan Wang ◽  
Lihang Zhou ◽  
Changyi Tan ◽  
Murty Divakarla ◽  
Ken Pryor ◽  
...  
Keyword(s):  
Real Time ◽  
Outgoing Longwave Radiation ◽  
Radiant Energy ◽  
Processing System ◽  
Longwave Radiation ◽  
Energy System ◽  
Satellite System ◽  
Global Scale ◽  
Atmospheric Processing ◽  
Validation Tests

The Outgoing Longwave Radiation (OLR) package was first developed as a stand-alone application, and then integrated into the National Oceanic and Atmospheric Administration (NOAA) Unique Combined Atmospheric Processing System (NUCAPS) hyperspectral sounding retrieval system. An objective of this package is to provide near-real-time OLR products derived from the Cross Track Infrared Sounder (CrIS) onboard the Joint Polar Satellite System (JPSS) satellites. It was initially developed and validated with CrIS onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite, and has been expanded to JPSS-1 (renamed NOAA-20 after launch) datasets that are currently available to the public. In this paper, we provide the results of detailed validation tests with NOAA-20 CrIS for large and wide representative conditions at a global scale. In our validation tests, the observations from Clouds and Earth’s Radiant Energy System (CERES) on Aqua were treated as the absolute reference or “truth”, and those from SNPP CrIS OLR were used as the transfer standard. The tests were performed on a 1° × 1° global spatial grid over daily, monthly, and yearly timescales. We find that the CrIS OLR products from NOAA-20 agree exceptionally well with those from Aqua CERES and SNPP CrIS OLR products in all conditions: the daily bias is within ±0.6 Wm−2, and the standard deviation (STD) ranges from 4.88 to 9.1 Wm−2. The bias and the STD of OLR monthly mean are better, within 0.3 and 2.0 Wm−2, respectively. These findings demonstrate the consistency between NOAA-20 and SNPP CrIS OLR up to annual scales, and the robustness of NUCAPS CrIS OLR products.

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 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 Can Top-of-Atmosphere Radiation Measurements Constrain Climate Predictions? Part II: Climate Sensitivity

2013 ◽  
Vol 26 (23) ◽  
pp. 9367-9383 ◽  
Author(s):  
Simon F. B. Tett ◽  
Daniel J. Rowlands ◽  
Michael J. Mineter ◽  
Coralia Cartis
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Radiant Energy ◽  
Longwave Radiation ◽  
Energy System ◽  
Total Solar Irradiance ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Prior Probabilities ◽  
Internal Climate Variability

A large number of perturbed-physics simulations of version 3 of the Hadley Centre Atmosphere Model (HadAM3) were compared with the Clouds and the Earth's Radiant Energy System (CERES) estimates of outgoing longwave radiation (OLR) and reflected shortwave radiation (RSR) as well as OLR and RSR from the earlier Earth Radiation Budget Experiment (ERBE) estimates. The model configurations were produced from several independent optimization experiments in which four parameters were adjusted. Model–observation uncertainty was estimated by combining uncertainty arising from satellite measurements, observational radiation imbalance, total solar irradiance, radiative forcing, natural aerosol, internal climate variability, and sea surface temperature and that arising from parameters that were not varied. Using an emulator built from 14 001 “slab” model evaluations carried out using the climateprediction.net ensemble, the climate sensitivity for each configuration was estimated. Combining different prior probabilities for model configurations with the likelihood for each configuration and taking account of uncertainty in the emulated climate sensitivity gives, for the HadAM3 model, a 2.5%–97.5% range for climate sensitivity of 2.7–4.2 K if the CERES observations are correct. If the ERBE observations are correct, then they suggest a larger range, for HadAM3, of 2.8–5.6 K. Amplifying the CERES observational covariance estimate by a factor of 20 brings CERES and ERBE estimates into agreement. In this case the climate sensitivity range is 2.7–5.4 K. The results rule out, at the 2.5% level for HadAM3 and several different prior assumptions, climate sensitivities greater than 5.6 K.

scholarly journals On the Surface Temperature Sensitivity of the Reflected Shortwave, Outgoing Longwave, and Net Incident Radiation

2012 ◽  
Vol 25 (19) ◽  
pp. 6585-6593 ◽  
Author(s):  
Hartmut H. Aumann ◽  
Alexander Ruzmaikin ◽  
Ali Behrangi
Keyword(s):  
Surface Temperature ◽  
Radiant Energy ◽  
Longwave Radiation ◽  
Energy System ◽  
Incident Radiation ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Correlation Technique ◽  
Cloud Forcing ◽  
Global Mean

Abstract The global-mean top-of-atmosphere incident solar radiation (ISR) minus the outgoing longwave radiation (OLR) and the reflected shortwave radiation (RSW) is the net incident radiation (NET). This study analyzes the global-mean NET sensitivity to a change in the global-mean surface temperature by applying the interannual anomaly correlation technique to 9 yr of Atmospheric Infrared Sounder (AIRS) global measurements of RSW and OLR under cloudy and clear conditions. The study finds the observed sensitivity of NET that includes the effects of clouds to be −1.5 ± 0.25 (1σ) W m−2 K−1 and the clear NET sensitivity to be −2.0 ± 0.2 (1σ) W m−2 K−1, consistent with previous work using Earth Radiation Budget Experiment and Clouds and the Earth’s Radiant Energy System data. The cloud effect, +0.5 ± 0.2 (1σ) W m−2 K−1, is a positive component of the NET sensitivity. The similarity of the NET sensitivities derived from forced and unforced models invites a comparison between the observed sensitivities and the effective sensitivities calculated for the Fourth Assessment Report models, although this requires some caution: The effective model sensitivities with clouds range from −0.88 to −1.64 W m−2 K−1, the clear NET sensitivity in the models ranges from −2.32 to −1.73 W m−2 K−1, and the cloud forcing sensitivities range from +0.14 to +1.18 W m−2 K−1. The effective NET and clear NET sensitivities derived from the models are statistically consistent with those derived from the AIRS data, considering the observational and model derivation uncertainties.

scholarly journals Using the Himawari-8 AHI Multi-Channel to Improve the Calculation Accuracy of Outgoing Longwave Radiation at the Top of the Atmosphere

2019 ◽  
Vol 11 (5) ◽  
pp. 589 ◽  
Author(s):  
Bu-Yo Kim ◽  
Kyu-Tae Lee
Keyword(s):  
Water Vapor ◽  
Optical Thickness ◽  
Outgoing Longwave Radiation ◽  
Radiant Energy ◽  
Longwave Radiation ◽  
Energy System ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Atmospheric Conditions ◽  
Calculation Algorithm

In this study, Himawari-8 Advanced Himawari Imager (AHI) longwave channel data that is sensitive to clouds and absorption gas were used to improve the accuracy of the algorithm used to calculate outgoing longwave radiation (OLR) at the top of the atmosphere. A radiative transfer model with a variety of atmospheric conditions was run using Garand vertical profile data as input data. The results of the simulation showed that changes in AHI channels 8, 12, 15, and 16, which were used to calculate OLR, were sensitive to changes in cloud characteristics (cloud optical thickness and cloud height) and absorption gases (water vapor, O3, CO2, aerosol optical thickness) in the atmosphere. When compared to long-term analysis OLR data from 2017, as recorded by the Cloud and Earth’s Radiant Energy System (CERES), the OLR calculated in this study had an annual mean bias of 2.28 Wm−2 and a root mean square error (RMSE) of 11.03 Wm−2. The new calculation method mitigated the problem of overestimations in OLR in mostly cloudy and overcast regions and underestimated OLR in cloud-free desert regions. It is also an improvement over the result from the existing OLR calculation algorithm, which uses window and water vapor channels.

scholarly journals The link between outgoing longwave radiation and the altitude at which a spaceborne lidar beam is fully attenuated

2017 ◽  
Vol 10 (12) ◽  
pp. 4659-4685 ◽  
Author(s):  
Thibault Vaillant de Guélis ◽  
Hélène Chepfer ◽  
Vincent Noel ◽  
Rodrigo Guzman ◽  
Philippe Dubuisson ◽  
...  
Keyword(s):  
Outgoing Longwave Radiation ◽  
Climate Model ◽  
Radiant Energy ◽  
Longwave Radiation ◽  
Energy System ◽  
Lidar Measurement ◽  
Radiative Effect ◽  
Simple Formulation ◽  
Cloud Radiative Effect ◽  
Global Mean

Abstract. According to climate model simulations, the changing altitude of middle and high clouds is the dominant contributor to the positive global mean longwave cloud feedback. Nevertheless, the mechanisms of this longwave cloud altitude feedback and its magnitude have not yet been verified by observations. Accurate, stable, and long-term observations of a metric-characterizing cloud vertical distribution that are related to the longwave cloud radiative effect are needed to achieve a better understanding of the mechanism of longwave cloud altitude feedback. This study shows that the direct measurement of the altitude of atmospheric lidar opacity is a good candidate for the necessary observational metric. The opacity altitude is the level at which a spaceborne lidar beam is fully attenuated when probing an opaque cloud. By combining this altitude with the direct lidar measurement of the cloud-top altitude, we derive the effective radiative temperature of opaque clouds which linearly drives (as we will show) the outgoing longwave radiation. We find that, for an opaque cloud, a cloud temperature change of 1 K modifies its cloud radiative effect by 2 W m−2. Similarly, the longwave cloud radiative effect of optically thin clouds can be derived from their top and base altitudes and an estimate of their emissivity. We show with radiative transfer simulations that these relationships hold true at single atmospheric column scale, on the scale of the Clouds and the Earth's Radiant Energy System (CERES) instantaneous footprint, and at monthly mean 2° × 2° scale. Opaque clouds cover 35 % of the ice-free ocean and contribute to 73 % of the global mean cloud radiative effect. Thin-cloud coverage is 36 % and contributes 27 % of the global mean cloud radiative effect. The link between outgoing longwave radiation and the altitude at which a spaceborne lidar beam is fully attenuated provides a simple formulation of the cloud radiative effect in the longwave domain and so helps us to understand the longwave cloud altitude feedback mechanism.

Unfiltering of the Geostationary Earth Radiation Budget (GERB) Data. Part II: Longwave Radiation

2008 ◽  
Vol 25 (7) ◽  
pp. 1106-1117 ◽  
Author(s):  
N. Clerbaux ◽  
S. Dewitte ◽  
C. Bertrand ◽  
D. Caprion ◽  
B. De Paepe ◽  
...  
Keyword(s):  
Radiant Energy ◽  
Longwave Radiation ◽  
Energy System ◽  
Radiation Budget ◽  
Spectral Radiance ◽  
Infrared Imager ◽  
Earth Radiation Budget ◽  
Different Sources ◽  
Flight Model ◽  
Earth Radiation

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.

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