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

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.

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

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-15-0238.1 ◽

2017 ◽

Vol 34 (3) ◽

pp. 643-655 ◽

Cited By ~ 3

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.

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The Climate Monitoring SAF Outgoing Longwave Radiation from AVHRR

Remote Sensing ◽

10.3390/rs12060929 ◽

2020 ◽

Vol 12 (6) ◽

pp. 929 ◽

Cited By ~ 1

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.

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Decadal Changes of Earth’s Outgoing Longwave Radiation

Remote Sensing ◽

10.3390/rs10101539 ◽

2018 ◽

Vol 10 (10) ◽

pp. 1539 ◽

Cited By ~ 3

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.

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

Remote Sensing ◽

10.3390/rs11050589 ◽

2019 ◽

Vol 11 (5) ◽

pp. 589 ◽

Cited By ~ 4

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.

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

Atmospheric Measurement Techniques ◽

10.5194/amt-10-4659-2017 ◽

2017 ◽

Vol 10 (12) ◽

pp. 4659-4685 ◽

Cited By ~ 6

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.

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Evaluation of Surface Upward Longwave Radiation in the CMIP6 Models with Ground and Satellite Observations

Remote Sensing ◽

10.3390/rs13214464 ◽

2021 ◽

Vol 13 (21) ◽

pp. 4464

Author(s):

Jiawen Xu ◽

Xiaotong Zhang ◽

Chunjie Feng ◽

Shuyue Yang ◽

Shikang Guan ◽

...

Keyword(s):

General Circulation ◽

Bayesian Model Averaging ◽

Mean Squared Error ◽

Radiant Energy ◽

Coupled Model ◽

Model Averaging ◽

Longwave Radiation ◽

Energy System ◽

General Circulation Models ◽

The Individual

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).

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Global maps of aerosol single scattering albedo using combined CERES-MODIS retrieval

10.5194/acp-2021-521 ◽

2021 ◽

Author(s):

Archana Devi ◽

Sreedharan Krishnakumari Satheesh

Keyword(s):

Climate Models ◽

Radiant Energy ◽

Energy System ◽

Single Scattering ◽

Global Scale ◽

Single Scattering Albedo ◽

Accurate Information ◽

Climatic Impact ◽

Aerosol Absorption ◽

Moderate Resolution Imaging Spectroradiometer

Abstract. Single Scattering Albedo (SSA) is a leading contributor to the uncertainty in aerosol radiative impact assessments. Therefore accurate information on aerosol absorption is required on a global scale. In this study, we have applied a multi-satellite algorithm to retrieve SSA using the concept of ‘critical optical depth.’ Global maps of SSA were generated following this approach using spatially and temporally collocated data from Clouds and the Earth’s Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on board Terra and Aqua satellites. The method has been validated using the data from aircraft-based measurements of various field campaigns. The retrieval uncertainty is ±0.03 and depends on both the surface albedo and aerosol absorption. Global mean SSA estimated over land and ocean is 0.93 and 0.97, respectively. Seasonal and spatial distribution of SSA over various regions are also presented. The global maps of SSA, thus derived with improved accuracy, provide important input to climate models for assessing the climatic impact of aerosols on regional and global scales.

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

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-11-00066.1 ◽

2012 ◽

Vol 29 (3) ◽

pp. 375-381 ◽

Cited By ~ 2

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.

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Can IASI be used to simulate the total spectrum of outgoing longwave radiation?

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-14-18421-2014 ◽

2014 ◽

Vol 14 (12) ◽

pp. 18421-18459

Author(s):

E. C. Turner ◽

H.-T. Lee ◽

S. F. B. Tett

Keyword(s):

High Resolution ◽

Radiative Forcing ◽

Radiant Energy ◽

Longwave Radiation ◽

Far Infrared ◽

Energy System ◽

Relative Difference ◽

High Resolution Spectrum ◽

Negative Results ◽

Mean Differences

Abstract. A new method of deriving high-resolution top-of-atmosphere spectral radiances over the entire outgoing longwave spectrum of the Earth is presented. Correlations between selected channels of the Infrared Atmospheric Sounding Interfermeter (IASI) on the MetOp-A satellite and simulated unobserved wavelengths in the far infrared are used to estimate radiances between 25.25–644.75 cm−1 at 0.5 cm−1 intervals. The same method is used in the 2760–3000 cm−1 region. Total integrated all-sky radiances are validated with broadband measurements from the Clouds and the Earth's Radiant Energy System (CERES) instrument on the Terra and Aqua satellites at simultaneous nadir overpasses, revealing mean differences that are 0.3 W m−2 sr−1 (0.5% relative difference) lower for IASI relative to CERES with significantly lower biases in nighttime – only scenes. Averaged global data over a single month produces mean differences of about 1 W m−2 sr−1 in both the all and the clear-sky (1.2% relative difference). The new high – resolution spectrum is presented for global mean all and clear skies where the far infrared is shown to contribute 47 and 44% to the total OLR respectively, which is consistent with previous estimates. In terms of spectral cloud radiative forcing, the FIR contributes 19% and in some subtropical instances appears to be negative, results that would go un-observed with a traditional broadband analysis.

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PENGEMBANGAN MODEL PREDIKSI MADDEN JULIAN OSCILLATION (MJO) BERBASIS PADA HASIL ANALISIS DATA REAL TIME MULTIVARIATE MJO (RMM1 DAN RMM2) (PREDICTION MODEL DEVELOPMENT MADDEN JULIAN OSCILLATION (MJO) BASED ON THE RESULTS OF DATA ANALYSIS ...

Agromet ◽

10.29244/j.agromet.22.2.144-159 ◽

2008 ◽

Vol 22 (2) ◽

pp. 144 ◽

Cited By ~ 1

Author(s):

Lisa Evana ◽

Sobri Effendy ◽

Eddy Hermawan

Keyword(s):

Prediction Model ◽

Real Time ◽

Outgoing Longwave Radiation ◽

Time Series Data ◽

Longwave Radiation ◽

Empirical Orthogonal Functions ◽

Wave Radiation ◽

Series Data ◽

Madden Julian Oscillation ◽

Coverage Area

Background of this research is the importance of study on the Madden Julian Oscillation, the dominant oscillation in the equator area. MJO cycle showed by cloud cluster growing in the Indian Ocean then moved to the east and form a cycle with a range of 40-50 days and the coverage area from 10N-10S. Method that used to predict RMM is Box-Jenkins based on ARIMA (Autoregressive Integrated Moving Average) statistical analysis. The data used RMM daily data period 1 Maret 1979–1 Maret 2009 (30 years). RMM1 and RMM2 is an index for monitoring MJO. This is based on two empirical orthogonal functions (EOFs) from the combined average zonal 850hPa wind, 200hPa zonal wind, and satellite-observed Outgoing Longwave Radiation (OLR) data. The results in form of the Power Spectral Density (PSD) graph Real Time Multivariate MJO (RMM) and long wave radiation (OLR = Outgoing Longwave Radiation) at the position 100° BT, 120° BT, and 140°BT that show the wave pattern (spectrum pattern) and clearly shows the oscillation periods. There is a close relation between RMM1 with OLR at the position 100oBT that characterized the PSD value about 45 day. Through Box-Jenkins method, the prediction model that close to time series data of RMM1 and RMM2 is ARIMA (2,1,2), that mean the forecasts of RMM data for the future depending on one time previously and the error one time before. Prediction model for Zt = Zt = 1,681 Zt-1 – 0,722 Zt-2 - 0,02 at-1 - 0,05 at-2.. Prediction model for RMM2 is Zt = 1,714 Zt-1 – 0,764 Zt-2 - 0,109 at-1 - 0,05 at-2.. The flood case in Jakarta January-February 1996 and 2002 are one of real evidence that made the MJO prediction important. MJO with active phase dominant cover almost the entire Indonesia west area at that moment.

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