scholarly journals Comparison of the Diurnal Cycle of Outgoing Longwave Radiation from a Climate Model with Results from ERBE

2008 ◽  
Vol 47 (12) ◽  
pp. 3188-3201 ◽  
Author(s):  
G. Louis Smith ◽  
Pamela E. Mlynczak ◽  
David A. Rutan ◽  
Takmeng Wong

Abstract The diurnal cycle of outgoing longwave radiation (OLR) computed by a climate model provides a powerful test of the numerical description of various physical processes. Diurnal cycles of OLR computed by version 3 of the Hadley Centre Atmospheric Model (HadAM3) are compared with those observed by the Earth Radiation Budget Satellite (ERBS) for the boreal summer season (June–August). The ERBS observations cover the domain from 55°S to 55°N. To compare the observed and modeled diurnal cycles, the principal component (PC) analysis method is used over this domain. The analysis is performed separately for the land and ocean regions. For land over this domain, the diurnal cycle computed by the model has a root-mean-square (RMS) of 11.4 W m−2, as compared with 13.3 W m−2 for ERBS. PC-1 for ERBS observations and for the model are similar, but the ERBS result has a peak near 1230 LST and decreases very slightly during night, whereas the peak of the model result is an hour later and at night the OLR decreases by 7 W m−2 between 2000 and 0600 LST. Some of the difference between the ERBS and model results is due to the computation of convection too early in the afternoon by the model. PC-2 describes effects of morning/afternoon cloudiness on OLR, depending on the sign. Over ocean in the ERBS domain, the model RMS of the OLR diurnal cycle is 2.8 W m−2, as compared with 5.9 W m−2 for ERBS. Also, for the model, PC-1 accounts for 66% of the variance, while for ERBS, PC-1 accounts for only 16% of the variance. Thus, over ocean, the ERBS results show a greater variety of OLR diurnal cycles than the model does.

2003 ◽  
Vol 60 (13) ◽  
pp. 1529-1542 ◽  
Author(s):  
G. Louis Smith ◽  
David A. Rutan

Abstract The diurnal cycle of outgoing longwave radiation (OLR) from the earth is analyzed by decomposing satellite observations into a set of empirical orthogonal functions (EOFs). The observations are from the Earth Radiation Budget Experiment (ERBE) scanning radiometer aboard the Earth Radiation Budget Satellite, which had a precessing orbit with 57° inclination. The diurnal cycles of land and ocean differ considerably. The first EOF for land accounts for 73% to 85% of the variance, whereas the first EOF for ocean accounts for only 16% to 20% of the variance, depending on season. The diurnal cycle for land is surprisingly symmetric about local noon for the first EOF, which is approximately a half-sine during day and flat at night. The second EOF describes lead–lag effects due to surface heating and cloud formation. For the ocean, the first EOF and second EOF are similar to that of land, except for spring, when the first ocean EOF is a semidiurnal cycle and the second ocean EOF is the half-sine. The first EOF for land has a daytime peak of about 50 W m−2, whereas the first ocean EOF peaks at about 25 W m−2. The geographical and seasonal patterns of OLR diurnal cycle provide insights into the interaction of radiation with the atmosphere and surface and are useful for validating and upgrading circulation models.


2014 ◽  
Vol 53 (12) ◽  
pp. 2747-2760 ◽  
Author(s):  
David A. Rutan ◽  
G. Louis Smith ◽  
Takmeng Wong

AbstractFive years of measurements from the Earth Radiation Budget Satellite (ERBS) have been analyzed to define the diurnal cycle of albedo from 55°N to 55°S. The ERBS precesses through all local times every 72 days so as to provide data regarding the diurnal cycles for Earth radiation. Albedo together with insolation at the top of the atmosphere is used to compute the heating of the Earth–atmosphere system; thus its diurnal cycle is important in the energetics of the climate system. A principal component (PC) analysis of the diurnal variation of top-of-atmosphere albedo using these data is presented. The analysis is done separately for ocean and land because of the marked differences of cloud behavior over ocean and over land. For ocean, 90%–92% of the variance in the diurnal cycle is described by a single component; for land, the first PC accounts for 83%–89% of the variance. Some of the variation is due to the increase of albedo with increasing solar zenith angle, which is taken into account in the ERBS data processing by a directional model, and some is due to the diurnal cycle of cloudiness. The second PC describes 2%–4% of the variance for ocean and 5% for land, and it is primarily due to variations of cloudiness throughout the day, which are asymmetric about noon. These terms show the response of the atmosphere to the cycle of solar heating. The third PC for ocean is a two-peaked curve, and the associated map shows high values in cloudy regions.


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.


2007 ◽  
Vol 24 (12) ◽  
pp. 2029-2047 ◽  
Author(s):  
Hai-Tien Lee ◽  
Arnold Gruber ◽  
Robert G. Ellingson ◽  
Istvan Laszlo

Abstract The Advanced Very High Resolution Radiometer (AVHRR) outgoing longwave radiation (OLR) product, which NOAA has been operationally generating since 1979, is a very long data record that has been used in many applications, yet past studies have shown its limitations and several algorithm-related deficiencies. Ellingson et al. have developed the multispectral algorithm that largely improved the accuracy of the narrowband-estimated OLR as well as eliminated the problems in AVHRR. NOAA has been generating High Resolution Infrared Radiation Sounder (HIRS) OLR operationally since September 1998. In recognition of the need for a continuous and long OLR data record that would be consistent with the earth radiation budget broadband measurements in the National Polar-orbiting Operational Environmental Satellite System (NPOESS) era, and to provide a climate data record for global change studies, a vigorous reprocessing of the HIRS radiance for OLR derivation is necessary. This paper describes the development of the new HIRS OLR climate dataset. The HIRS level 1b data from the entire Television and Infrared Observation Satellite N-series (TIROS-N) satellites have been assembled. A new radiance calibration procedure was applied to obtain more accurate and consistent HIRS radiance measurements. The regression coefficients of the HIRS OLR algorithm for all satellites were rederived from calculations using an improved radiative transfer model. Intersatellite calibrations were performed to remove possible discontinuity in the HIRS OLR product from different satellites. A set of global monthly diurnal models was constructed consistent with the HIRS OLR retrievals to reduce the temporal sampling errors and to alleviate an orbital-drift-induced artificial trend. These steps significantly improved the accuracy, continuity, and uniformity of the HIRS monthly mean OLR time series. As a result, the HIRS OLR shows a comparable stability as in the Earth Radiation Budget Satellite (ERBS) nonscanner OLR measurements. HIRS OLR has superb agreement with the broadband observations from Earth Radiation Budget Experiment (ERBE) and Clouds and the Earth’s Radiant Energy System (CERES) in the ENSO-monitoring regions. It shows compatible ENSO-monitoring capability with the AVHRR OLR. Globally, HIRS OLR agrees with CERES with an accuracy to within 2 W m−2 and a precision of about 4 W m−2. The correlation coefficient between HIRS and CERES global monthly mean is 0.997. Regionally, HIRS OLR agrees with CERES to within 3 W m−2 with precisions better than 3 W m−2 in most places. HIRS OLR could be used for constructing climatology for applications that plan to use NPOESS ERBS and previously used AVHRR OLR observations. The HIRS monthly mean OLR data have high accuracy and precision with respect to the broadband observations of ERBE and CERES. It can be used as an independent validation data source. The uniformity and continuity of HIRS OLR time series suggest that it could be used as a reliable transfer reference for the discontinuous broadband measurements from ERBE, CERES, and ERBS.


2013 ◽  
Vol 13 (8) ◽  
pp. 4057-4072 ◽  
Author(s):  
K. W. Bowman ◽  
D. T. Shindell ◽  
H. M. Worden ◽  
J.F. Lamarque ◽  
P. J. Young ◽  
...  

Abstract. We use simultaneous observations of tropospheric ozone and outgoing longwave radiation (OLR) sensitivity to tropospheric ozone from the Tropospheric Emission Spectrometer (TES) to evaluate model tropospheric ozone and its effect on OLR simulated by a suite of chemistry-climate models that participated in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The ensemble mean of ACCMIP models show a persistent but modest tropospheric ozone low bias (5–20 ppb) in the Southern Hemisphere (SH) and modest high bias (5–10 ppb) in the Northern Hemisphere (NH) relative to TES ozone for 2005–2010. These ozone biases have a significant impact on the OLR. Using TES instantaneous radiative kernels (IRK), we show that the ACCMIP ensemble mean tropospheric ozone low bias leads up to 120 mW m−2 OLR high bias locally but zonally compensating errors reduce the global OLR high bias to 39 ± 41 m Wm−2 relative to TES data. We show that there is a correlation (R2 = 0.59) between the magnitude of the ACCMIP OLR bias and the deviation of the ACCMIP preindustrial to present day (1750–2010) ozone radiative forcing (RF) from the ensemble ozone RF mean. However, this correlation is driven primarily by models whose absolute OLR bias from tropospheric ozone exceeds 100 m Wm−2. Removing these models leads to a mean ozone radiative forcing of 394 ± 42 m Wm−2. The mean is about the same and the standard deviation is about 30% lower than an ensemble ozone RF of 384 ± 60 m Wm−2 derived from 14 of the 16 ACCMIP models reported in a companion ACCMIP study. These results point towards a profitable direction of combining satellite observations and chemistry-climate model simulations to reduce uncertainty in ozone radiative forcing.


2016 ◽  
Vol 29 (19) ◽  
pp. 7009-7025 ◽  
Author(s):  
Li Deng ◽  
Tim Li

Abstract The interannual variability of the boreal summer intraseasonal oscillation (BSISO) is investigated using observed outgoing longwave radiation (OLR) and ERA-Interim data for the period of 1980–2012. It is found that the interannual variability of BSISO intensity is much stronger in the tropical western Pacific (TWP) than the tropical Indian Ocean (TIO). A BSISO intensity index is defined based on a multivariate EOF analysis in TWP. It is found that strong BSISO years are associated with El Niño–like sea surface temperature anomalies in the tropical Pacific, anomalous easterly shear, and enhanced background moisture condition in the region. Using a 2.5-layer atmospheric model with a specified idealized background mean state, the authors further examine the relative roles of background moisture and vertical shear fields in modulating the BSISO intensity. Sensitivity numerical experiments indicate that the background moisture change is most important in regulating the BSISO intensity, whereas the background vertical shear change also plays a role.


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